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Connectivity (40)

by Stephanie Overby

What's next for edge computing, and how should it shape your strategy? Experts weigh in on edge trends and talk workloads, cloud partnerships, security, and related issues


All year, industry analysts have been predicting that that edge computing – and complimentary 5G network offerings ­­– will see significant growth, as major cloud vendors are deploying more edge servers in local markets and telecom providers pushing ahead with 5G deployments.

The global pandemic has not significantly altered these predictions. In fact, according to IDC’s worldwide IT predictions for 2021, COVID-19’s impact on workforce and operational practices will be the dominant accelerator for 80 percent of edge-driven investments and business model change across most industries over the next few years.

First, what exactly do we mean by edge? Here’s how Rosa Guntrip, senior principal marketing manager, cloud platforms at Red Hat, defines it: “Edge computing refers to the concept of bringing computing services closer to service consumers or data sources. Fueled by emerging use cases like IoT, AR/VR, robotics, machine learning, and telco network functions that require service provisioning closer to users, edge computing helps solve the key challenges of bandwidth, latency, resiliency, and data sovereignty. It complements the hybrid computing model where centralized computing can be used for compute-intensive workloads while edge computing helps address the requirements of workloads that require processing in near real time.”

Moving data infrastructure, applications, and data resources to the edge can enable faster response to business needs, increased flexibility, greater business scaling, and more effective long-term resilience.

“Edge computing is more important than ever and is becoming a primary consideration for organizations defining new cloud-based products or services that exploit local processing, storage, and security capabilities at the edge of the network through the billions of smart objects known as edge devices,” says Craig Wright, managing director with business transformation and outsourcing advisory firm Pace Harmon.

“In 2021 this will be an increasing consideration as autonomous vehicles become more common, as new post-COVID-19 ways of working require more distributed compute and data processing power without incurring debilitating latency, and as 5G adoption stimulates a whole new generation of augmented reality, real-time application solutions, and gaming experiences on mobile devices,” Wright adds.

8 key edge computing trends in 2021


Noting the steady maturation of edge computing capabilities, Forrester analysts said, “It’s time to step up investment in edge computing,” in their recent Predictions 2020: Edge Computing report. As edge computing emerges as ever more important to business strategy and operations, here are eight trends IT leaders will want to keep an eye on in the year ahead.

1. Edge meets more AI/ML


Until recently, pre-processing of data via near-edge technologies or gateways had its share of challenges due to the increased complexity of data solutions, especially in use cases with a high volume of events or limited connectivity, explains David Williams, managing principal of advisory at digital business consultancy AHEAD. “Now, AI/ML-optimized hardware, container-packaged analytics applications, frameworks such as TensorFlow Lite and tinyML, and open standards such as the Open Neural Network Exchange (ONNX) are encouraging machine learning interoperability and making on-device machine learning and data analytics at the edge a reality.” 

Machine learning at the edge will enable faster decision-making. “Moreover, the amalgamation of edge and AI will further drive real-time personalization,” predicts Mukesh Ranjan, practice director with management consultancy and research firm Everest Group.

“But without proper thresholds in place, anomalies can slowly become standards,” notes Greg Jones, CTO of IoT solutions provider Kajeet. “Advanced policy controls will enable greater confidence in the actions made as a result of the data collected and interpreted from the edge.” 

 

2. Cloud and edge providers explore partnerships


IDC predicts a quarter of organizations will improve business agility by integrating edge data with applications built on cloud platforms by 2024. That will require partnerships across cloud and communications service providers, with some pairing up already beginning between wireless carriers and the major public cloud providers.

According to IDC research, the systems that organizations can leverage to enable real-time analytics are already starting to expand beyond traditional data centers and deployment locations. Devices and computing platforms closer to end customers and/or co-located with real-world assets will become an increasingly critical component of this IT portfolio. This edge computing strategy will be part of a larger computing fabric that also includes public cloud services and on-premises locations.

In this scenario, edge provides immediacy and cloud supports big data computing.

 

3. Edge management takes center stage


“As edge computing becomes as ubiquitous as cloud computing, there will be increased demand for scalability and centralized management,” says Wright of Pace Harmon. IT leaders deploying applications at scale will need to invest in tools to “harness step change in their capabilities so that edge computing solutions and data can be custom-developed right from the processor level and deployed consistently and easily just like any other mainstream compute or storage platform,” Wright says.

The traditional approach to data center or cloud monitoring won’t work at the edge, notes Williams of AHEAD. “Because of the rather volatile nature of edge technologies, organizations should shift from monitoring the health of devices or the applications they run to instead monitor the digital experience of their users,” Williams says. “This user-centric approach to monitoring takes into consideration all of the components that can impact user or customer experience while avoiding the blind spots that often lie between infrastructure and the user.”

As Stu Miniman, director of market insights on the Red Hat cloud platforms team, recently noted, “If there is any remaining argument that hybrid or multi-cloud is a reality, the growth of edge solidifies this truth: When we think about where data and applications live, they will be in many places.”

“The discussion of edge is very different if you are talking to a telco company, one of the public cloud providers, or a typical enterprise,” Miniman adds. “When it comes to Kubernetes and the cloud-native ecosystem, there are many technology-driven solutions competing for mindshare and customer interest. While telecom giants are already extending their NFV solutions into the edge discussion, there are many options for enterprises. Edge becomes part of the overall distributed nature of hybrid environments, so users should work closely with their vendors to make sure the edge does not become an island of technology with a specialized skill set.“

 

4. IT and operational technology begin to converge


Resiliency is perhaps the business term of the year, thanks to a pandemic that revealed most organizations’ weaknesses in this area. IoT-enabled devices (and other connected equipment) drive the adoption of edge solutions where infrastructure and applications are being placed within operations facilities. This approach will be “critical for real-time inference using AI models and digital twins, which can detect changes in operating conditions and automate remediation,” IDC’s research says.

IDC predicts that the number of new operational processes deployed on edge infrastructure will grow from less than 20 percent today to more than 90 percent in 2024 as IT and operational technology converge. Organizations will begin to prioritize not just extracting insight from their new sources of data, but integrating that intelligence into processes and workflows using edge capabilities.

Mobile edge computing (MEC) will be a key enabler of supply chain resilience in 2021, according to Pace Harmon’s Wright. “Through MEC, the ecosystem of supply chain enablers has the ability to deploy artificial intelligence and machine learning to access near real-time insights into consumption data and predictive analytics as well as visibility into the most granular elements of highly complex demand and supply chains,” Wright says. “For organizations to compete and prosper, IT leaders will need to deliver MEC-based solutions that enable an end-to-end view across the supply chain available 24/7 – from the point of manufacture or service  throughout its distribution.”

 

5. Edge eases connected ecosystem adoption


Edge not only enables and enhances the use of IoT, but it also makes it easier for organizations to participate in the connected ecosystem with minimized network latency and bandwidth issues, says Manali Bhaumik, lead analyst at technology research and advisory firm ISG. “Enterprises can leverage edge computing’s scalability to quickly expand to other profitable businesses without incurring huge infrastructure costs,” Bhaumik says. “Enterprises can now move into profitable and fast-streaming markets with the power of edge and easy data processing.”

 

6. COVID-19 drives innovation at the edge


“There’s nothing like a pandemic to take the hype out of technology effectiveness,” says Jason Mann, vice president of IoT at SAS. Take IoT technologies such as computer vision enabled by edge computing: “From social distancing to thermal imaging, safety device assurance and operational changes such as daily cleaning and sanitation activities, computer vision is an essential technology to accelerate solutions that turn raw IoT data (from video/cameras) into actionable insights,” Mann says. Retailers, for example, can use computer vision solutions to identify when people are violating the store’s social distance policy.

 

7. Private 5G adoption increases


“Use cases such as factory floor automation, augmented and virtual reality within field service management, and autonomous vehicles will drive the adoption of private 5G networks,” says Ranjan of Everest Group. Expect more maturity in this area in the year ahead, Ranjan says.

 

8. Edge improves data security


“Data efficiency is improved at the edge compared with the cloud, reducing internet and data costs,” says ISG’s Bhaumik. “The additional layer of security at the edge enhances the user experience.” Edge computing is also not dependent on a single point of application or storage, Bhaumik says. “Rather, it distributes processes across a vast range of devices.”

As organizations adopt DevSecOps and take a “design for security” approach, edge is becoming a major consideration for the CSO to enable secure cloud-based solutions, says Pace Harmon’s Wright. “This is particularly important where cloud architectures alone may not deliver enough resiliency or inherent security to assure the continuity of services required by autonomous solutions, by virtual or augmented reality experiences, or big data transaction processing,” Wright says. “However, IT leaders should be aware of the rate of change and relative lack of maturity of edge management and monitoring systems; consequently, an edge-based security component or solution for today will likely need to be revisited in 18 to 24 months’ time.”

Originally posted here.

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By Natallia Babrovich

My experience shows that most of the visits to doctors are likely to become virtual in the future. Let’s see how IoT solutions make the healthcare environment more convenient for patients and medical staff.

What are IoT and IoMT?

My colleague Alex Grizhnevich, IoT consultant at ScienceSoft, defines Internet of Things as a network of physical devices with sensors and actuators, software, and network connectivity that enable devices to gather and transmit data and fulfill users' tasks. Today, IoT becomes a key component of the digital transformation of healthcare, so we can distinguish a separate group of initiatives, the so-called IoHT (Internet of Health Things) or IoMT (Internet of Medical Things).

Popular IoMT Use Cases

IoT-based patient care

Medication intake tracking

IoT-based medication tracking allows doctors to monitor the impact of a prescribed medication’s dosage on a patient’s condition. In their turn, patients can control medication intake, e.g., by using in-app reminders and note in the app how their symptoms change for their doctor’s further analysis. The patient app can be connected to smart devices, (e.g., a smart pill bottle) for easier management of multiple medications.

Remote health monitoring

Among examples of employing IoT in healthcare, this use case is especially viable for chronic disease management. Patients can use connected medical devices or body-worn biosensors to allow doctors or nurses to check their vitals (blood pressure, glucose level, heart rate, etc.) via doctor/nurse-facing apps. Health professionals can monitor this data 24/7 and study app-generated reports to get insights into health trends. Patients who show signs of deteriorating health are scheduled for in-person visits.

IoT- and RFID-based medical asset monitoring

Medical inventory and equipment tracking

All medical tools and durable assets (beds, medical equipment) are equipped with RFID (radio frequency identification) tags. Fixed RFID readers (e.g., on the walls) collect the info about the location of assets. Medical staff can view it using a mobile or web application with a map.

Drug tracking

RFID-enabled drug tracking helps pharmacies and hospitals verify the authenticity of medication packages and timely spot medication shortages.

Smart hospital space

Cloud-connected ward sensors (e.g., a light switch, door and window contacts) and ambient sensors (e.g., hydrometers, noise detectors) allow patients to control their environment for a comfortable hospital stay.

Advantages of using IoT technology in healthcare

Patient-centric care

Medical IoT helps turn patients into active participants of the treatment process, thus improving care outcomes. Besides, IoMT helps increase patient satisfaction with care delivery, from communication with medical staff to physical comfort (smart lighting, climate control, etc.).

Reduced care-related costs

Non-critical patients can stay at home and use cloud-connected medical IoT devices, which gather, track and send health data to the medical facility. And with the help of telehealth technology, patients can schedule e-visits with nurses and doctors without traveling to the hospital.

Reduced readmissions

Patient apps connected to biosensors help ensure compliance with a discharge plan, enable prompt detection of health state deviations, and provide an opportunity to timely contact a health professional remotely.

Challenges of IoMT and how to address them

Potential health data security breaches

The connected nature of IoT brings about information security challenges for healthcare providers and patients.

Tip from ScienceSoft

We recommend implementing HIPAA-compliant IoMT solutions and conduct vulnerability assessment and penetration testing regularly to ensure the highest level of protection.

Integration difficulties

Every medical facility has its unique set of applications to be integrated with an IoMT solution (e.g., EHR, EMR). Some of these applications may be heavily customized or outdated.

Tip from ScienceSoft

Develop the integrations strategy from the start of your IoMT project, including the scope and the nature of custom integrations.

Enhance care delivery with IoMT

According to my estimates, the use of IoT technology in healthcare will continue to rise during the next decade, driven by the impact of the COVID situation and the growing demand for remote care. If you need help with creating and implementing a fitting IoMT solution, you’re welcome to turn to ScienceSoft’s healthcare IT team.

Originally posted here.

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IoT Sustainability, Data At The Edge.

Recently I've written quite a bit about IOT, and one thing you may have picked up on is that the Internet of Things is made up of a lot of very large numbers.

For starters, the number of connected things is measured in the tens of billions, nearly 100's of billions. Then, behind that very large number is an even bigger number, the amount of data these billions of devices is predicted to generate.

As FutureIoT pointed out, IDC forecasted that the amount of data generated by IoT devices by 2025 is expected to be in excess of 79.4 zettabytes (ZB).

How much is Zettabyte!?

A zettabyte is a very large number indeed, but how big? How can you get your head around it? Does this help...?

A zettabyte is 1,000,000,000,000,000,000,000 bytes. Hmm, that's still not very easy to visualise.

So let's think of it in terms of London busses. Let's image a byte is represented as a human on a bus, a London bus can take 80 people, so you'd need 993 quintillion busses to accommodate 79.4 zettahumans.

I tried to calculate how long 993 quintillion busses would be. Relating it to the distance to the moon, Mars or the Sun wasn't doing it justice, the only comparable scale is the size of the Milky Way. Even with that, our 79.4 zettahumans lined up in London busses, would stretch across the entire Milky Way ... and a fair bit further!

Sustainability Of Cloud Storage For 993 Quintillion Busses Of Data

Everything we do has an impact on the planet. Just by reading this article, you're generating 0.2 grams of Carbon Dioxide (CO2) emissions per second ... so I'll try to keep this short.

Using data from the Stanford Magazine that suggests every 100 gigabytes of data stored in the Cloud could generate 0.2 tons of CO2 per year. Storing 79.4 zettabytes of data in the Cloud could be responsible for the production of 158.8 billion tons of greenhouse gases.

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Putting that number into context, using USA Today numbers, the total emissions for China, USA, India, Russia, Japan and Germany accounted for a little over 21 billion tons in 2019.

So if we just go ahead and let all the IoT devices stream data to the Cloud, those billions of little gadgets would indirectly generate more than seven times the air pollution than the six most industrial countries, combined.

Save The Planet, Store Data At The Edge

As mentioned in a previous article, not all data generated by IoT devices needs to be stored in the Cloud.

Speaking with an expert in data storage, ObjectBox, they say their users on average cut their Cloud data storage by 60%. So how does that work, then? 

First, what does The Edge mean?

The term "Edge" refers to the edge of the network, in other words the last piece of equipment or thing connected to the network closest to the point of usage.

Let me illustrate in rather over-simplified diagram.

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How Can Edge Data Storage Improve Sustainability?

In an article about computer vision and AI on the edge, I talked about how vast amounts of network data could be saved if the cameras themselves could detect what an important event was, and to just send that event over the network, not the entire video stream.

In that example, only the key events and meta data, like the identification marks of a vehicle crossing a stop light, needed to be transmitted across the network. However, it is important to keep the raw content at the edge, so it can be used for post processing, for further learning of the AI or even to be retrieved at a later date, e.g. by law-enforcement.

Another example could be sensors used to detect gas leaks, seismic activity, fires or broken glass. These sensors are capturing volumes of data each second, but they only want to alert someone when something happens - detection of abnormal gas levels, a tremor, fire or smashed window.

Those alerts are the primary purpose of those devices, but the data in between those events can also hold significant value. In this instance, keeping it locally at the edge, but having it as and when needed is an ideal way to reduce network traffic, reduce Cloud storage and save the planet (well, at least a little bit).

Accessible Data At The Edge

Keeping your data at the edge is a great way to save costs and increase performance, but you still want to be able to get access to it, when you need it.

ObjectBox have created not just one of the most efficient ways to store data at the edge, but they've also built a sophisticated and powerful method to synchronise data between edge devices, the Cloud and other edge devices.

Synchronise Data At The Edge - Fog Computing.

Fog Computing (which is computing that happens between the Cloud and the Edge) requires data to be exchanged with devices connected to the edge, but without going all the way to/from the servers in the Cloud. 

In the article on making smarter, safer cities, I talked about how by having AI-equipped cameras share data between themselves they could become smarter, more efficient. 

A solution like that could be using ObjectBox's synchronisation capabilities to efficiently discover and collect relevant video footage from various cameras to help either identify objects or even train the artificial intelligence algorithms running on the AI-equipped cameras at the edge.

Storing Data At The Edge Can Save A Bus Load CO2

Edge computing has a lot of benefits to offer, in this article I've just looked at what could often be overlooked - the cost of transferring data. I've also not really delved into the broader benefits of ObjectBox's technology, for example, from their open source benchmarks, ObjectBox seems to offer a ten times performance benefit compared to other solutions out there, and is being used by more than 300,000 developers.  

The team behind ObjectBox also built technologies currently used by internet heavy-weights like Twitter, Viber and Snapchat, so they seem to be doing something right, and if they can really cut down network traffic by 60%, they could be one of sustainable technology companies to watch.  

Originally posted here.

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The possibilities of what you can do with digital twin technology are only as limited as your imagination

Today, forward-thinking companies across industries are implementing digital twin technology in increasingly fascinating and ground-breaking ways. With Internet of Things (IoT) technology improving every day and more and more compute power readily available to organizations of all sizes, the possibilities of what you can do with digital twin technology are only as limited as your imagination.

What Is a Digital Twin?

A digital twin is a virtual representation of a physical asset that is practically indistinguishable from its physical counterpart. It is made possible thanks to IoT sensors that gather data from the physical world and send it to be virtually reconstructed. This data includes design and engineering details that describe the asset’s geometry, materials, components, and behavior or performance.

When combined with analytics, digital twin data can unlock hidden value for an organization and provide insights about how to improve operations, increase efficiency or discover and resolve problems before the real-world asset is affected.

These 4 Steps Are Critical for Digital Twin Success:

Involve the Entire Product Value Chain

It’s critical to involve stakeholders across the product value chain in your design and implementation. Each department faces diverse business challenges in their day-to-day operations, and a digital twin provides ready solutions to problems such as the inability to coordinate across end-to-end supply chain processes, minimal or no cross-functional collaboration, the inability to make data-driven decisions, or clouded visibility across the supply chain. Decision-makers at each level of the value chain have extensive knowledge on critical and practical challenges. Including their inputs will ensure a better and more efficient design of the digital twin and ensure more valuable and relevant insights.

Establish Well-Documented Practices

Standardized and well-documented design practices help organizations communicate ideas across departments, or across the globe, and make it easier for multiple users of the digital twin to build or alter the model without destroying existing components or repeating work. Best-in-class modelling practices increase transparency while simplifying and streamlining collaborative work.

Include Data From Multiple Sources

Data from multiple sources—both internal and external—is an essential part of creating realistic and helpful simulations. 3D modeling and geometry is sufficient to show how parts fit together and how a product works, but more input is required to model how various faults or errors might occur somewhere in the product’s lifecycle. Because many errors and problems can be nearly impossible to accurately predict by humans alone, a digital twin needs a vast amount of data and a robust analytics program to be able to run algorithms to make accurate forecasts and prevent downtime.

Ensure Long Access Lifecycles 

Digital twins implemented using proprietary design software have a risk of locking owners into a single vendor, which ties the long-term viability of the digital twin to the longevity of the supplier’s product. This risk is especially significant for assets with long lifecycles such as buildings, industrial machinery, airplanes, etc., since the lifecycles of these assets are usually much longer than software lifecycles. This proprietary dependency only becomes riskier and less sustainable over time. To overcome these risks, IT architects and digital twin owners need to carefully set terms with software vendors to ensure data compatibility is maintained and vendor lock-in can be avoided.

Common Pitfalls to Digital Twin Implementation

Digital twin implementation requires an extraordinary investment of time, capital, and engineering might, and as with any project of this scale, there are several common pitfalls to implementation success.

Pitfall 1: Using the Same Platform for Different Applications

Although it’s tempting to try and repurpose a digital twin platform, doing so can lead to incorrect data at best and catastrophic mistakes at worst. Each digital twin is completely unique to a part or machine, therefore assets with unique operating conditions and configurations cannot share digital twin platforms.

Pitfall 2: Going Too Big, Too Fast

In the long run, a digital twin replica of your entire production line or building is possible and could provide incredible insights, but it is a mistake to try and deploy digital twins for all of your pieces of equipment or programs all at once. Not only is doing too much, too fast costly, but it might cause you to rush and miss critical data and configurations along the way. Rather than rushing to do it all at once, perfect a few critical pieces of machinery first and work your way up from there.

Pitfall 3: Inability to Source Quality Data

Data collected in the field is subject to quality errors due to human mistakes or duplicate entries. The insights your digital twin provides you are only as valuable as the data it runs off of. Therefore, it is imperative to standardize data collection practices across your organization and to regularly cleanse your data to remove duplicate and erroneous entries.

Pitfall 4: Lack of Device Communication Standards

If your IoT devices do not speak a common language, miscommunications can muddy your processes and compromise your digital twin initiative. Build an IT framework that allows your IoT devices to communicate with one another seamlessly to ensure success.

Pitfall 5: Failing to Get User Buy-In

As mentioned earlier in this eBook, a successful digital twin strategy includes users from across your product value chain. It is critical that your users understand and appreciate the value your digital twin brings to them individually and to your organization as a whole. Lack of buy-in due to skepticism, lack of confidence, or resistance can lead to a lack of user participation, which can undermine all of your efforts.

The Challenge of Measuring Digital Twin Success

Each digital twin is unique and completely separate in its function and end-goal from others on the market, which can make measuring success challenging. Depending on the level of the twin implemented, businesses need to create KPIs for each individual digital twin as it relates to larger organizational goals.

The configuration of digital twins is determined by the type of input data, number of data sources and the defined metrics. The configuration determines the value an organization can extract from the digital twin. Therefore, a twin with a higher configuration can yield better predictions than can a twin with a lower configuration. The reality is that success can be relative, and it is impossible to compare the effectiveness of two different digital twins side by side.

Conclusion

It’s possible — probable even — that in the future all people, enterprises, and even cities will have a digital twin. With the enormous growth predicted in the digital twin market in the coming years, it’s evident that the technology is here to stay. The possible applications of digital twins are truly limitless, and as IoT technology becomes more advanced and widely accessible, we’re likely to see many more innovative and disruptive use cases.

However, a technology with this much potential must be carefully and thoughtfully implemented in order to ensure its business value and long-term viability. Before embracing a digital twin, an organization must first audit its maturity, standardize processes, and prepare its culture and staff for this radical change in operations. Is your organization ready?

Originally posted here.

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Five IoT retail trends for 2021

In 2020 we saw retailers hard hit by the economic effects of the COVID-19 pandemic with dozens of retailers—Neiman Marcus, J.C. Penney, and Brooks Brothers to name a few— declaring bankruptcy. During the unprecedented chaos of lockdowns and social distancing, consumers accelerated their shift to online shopping. Retailers like Target and Best Buy saw online sales double while Amazon’s e–commerce sales grew 39 percent.1 Retailers navigated supply chain disruptions due to COVID-19, climate change events, trade tensions, and cybersecurity events.  

After the last twelve tumultuous months, what will 2021 bring for the retail industry? I spoke with Microsoft Azure IoT partners to understand how they are planning for 2021 and compiled insights about five retail trends. One theme we’re seeing is a focus on efficiency. Retailers will look to pre-configured digital platforms that leverage cloud-based technologies including the Internet of Things (IoT), artificial intelligence (AI), and edge computing to meet their business goals. 

a group of people standing in front of a mirror posing for the camera

Empowering frontline workers with real-time data

In 2021, retailers will increase efficiency by empowering frontline workers with real-time data. Retail employees will be able to respond more quickly to customers and expand their roles to manage curbside pickups, returns, and frictionless kiosks.  

In H&M Mitte Garten in Berlin, H&M empowered employee ambassadors with fashionable bracelets connected to the Azure cloud. Ambassadors were able to receive real-time requests via their bracelets when customers needed help in fitting rooms or at a cash desk. The ambassadors also received visual merchandising instructions and promotional updates. 

Through the app built on Microsoft partner Turnpike’s wearable SaaS platform leveraging Azure IoT Hub, these frontline workers could also communicate with their peers or their management team during or after store hours. With the real-time data from the connected bracelets, H&M ambassadors were empowered to delivered best-in-class service.   

Carl Norberg, Founder, Turnpike explained, “We realized that by connecting store IoT sensors, POS systems, and AI cameras, store staff can be empowered to interact at the right place at the right time.” 

Leveraging live stream video to innovate omnichannel

Livestreaming has been exploding in China as influencers sell through their social media channels. Forbes recently projected that nearly 40 percent of China’s population will have viewed livestreams during 2020.2 Retailers in the West are starting to leverage live stream technology to create innovative omnichannel solutions.  

For example, Kjell & Company, one of Scandinavia’s leading consumer electronics retailers, is using a solution from Bambuser and Ombori called Omni-queue built on top of the Ombori Grid. Omni-queue enables store employees to handle a seamless combination of physical and online visitors within the same queue using one-to-one live stream video for online visitors.  

Kjell & Company ensures e-commerce customers receive the same level of technical expertise and personalized service they would receive in one of their physical locations. Omni-queue also enables its store employees to be utilized highly efficiently with advanced routing and knowledge matching. 

Maryam Ghahremani, CEO of Bambuser explains, “Live video shopping is the future, and we are so excited to see how Kjell & Company has found a use for our one-to-one solution.” Martin Knutson, CTO of Kjell & Company added “With physical store locations heavily affected due to the pandemic, offering a new and innovative way for customers to ask questions—especially about electronics—will be key to Kjell’s continued success in moving customers online.” 

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Augmenting omnichannel with dark stores and micro-fulfillment centers  

In 2021, retailers will continue experimenting with dark stores—traditional retail stores that have been converted to local fulfillment centers—and micro-fulfillment centers. These supply chain innovations will increase efficiency by bringing products closer to customers. 

Microsoft partner Attabotics, a 3D robotics supply chain company, works with an American luxury department store retailer to reduce costs and delivery time using a micro-fulfillment center. Attabotics’ unique use of both horizontal and vertical space reduces warehouse needs by 85 percent. Attabotics’ structure and robotic shuttles leveraged Microsoft Azure Edge Zones, Azure IoT Central, and Azure Sphere.

The luxury retailer leverages the micro-fulfillment center to package and ship multiple beauty products together. As a result, customers experience faster delivery times. The retailer also reduces costs related to packaging, delivery, and warehouse space.  

Scott Gravelle, Founder, CEO, and CTO of Attabotics explained, “Commerce is at a crossroads, and for retailers and brands to thrive, they need to adapt and take advantage of new technologies to effectively meet consumers’ growing demands. Supply chains have not traditionally been set up for e-commerce. We will see supply chain innovations in automation and modulation take off in 2021 as they bring a wider variety of products closer to the consumer and streamline the picking and shipping to support e-commerce.” 

a group of people wearing costumes

Helping keep warehouse workers safe

What will this look like? Cognizant’s recent work with an athletic apparel retailer offers a blueprint. During the peak holiday season, the retailer needed to protect its expanding warehouse workforce while minimizing absenteeism. To implement physical distancing and other safety measures, the retailer  leveraged Cognizant’s Safe Buildings solution built with Azure IoT Edge and IoT Hub services.   

With this solution, employees maintain physical distancing using smart wristbands. When two smart wristbands were within a pre-defined distance of each other for more than a pre-defined time, the worker’s bands buzzed to reinforce safe behaviors. The results drove nearly 98 percent distancing compliance in the initial pilot. As the retailer plans to scale-up its workforce at other locations, implementing additional safety modules are being considered:   

  • Touchless temperature checks.  
  • Occupancy sensors communicate capacity information to the management team for compliance records.  
  • Air quality sensors provide environmental data so the facility team could help ensure optimal conditions for workers’ health.  

“For organizations to thrive during and post-pandemic, enterprise-grade workplace safety cannot be compromised. Real-time visibility of threats is providing essential businesses an edge in minimizing risks proactively while building employee trust and empowering productivity in a safer workplace,” Rajiv Mukherjee, Cognizant’s IoT Practice Director for Retail and Consumer Goods.  

Optimizing inventory management with real-time edge data

In 2021, retailers will ramp up the adoption of intelligent edge solutions to optimize inventory management with real-time data. Most retailers have complex inventory management systems. However, no matter how good the systems are, there can still be data gaps due to grocery pick-up services, theft, and sweethearting. The key to addressing these gaps is to combine real-time data from applications running on edge cameras and other edge devices in the physical store with backend enterprise resource planning (ERP) data.  

Seattle Goodwill worked with Avanade to implement a new Microsoft-based Dynamics platform across its 24 stores. The new system provided almost real-time visibility into the movement of goods from the warehouses to the stores. 

Rasmus Hyltegård, Director of Advanced Analytics at Avanade explained, “To ensure inventory moves quickly off the shelves, retailers can combine real-time inventory insights from Avanade’s smart inventory accelerator with other solutions across the customer journey to meet customer expectations.” Hyltegård continued, “Customers can check online to find the products they want, find the stores with product in stock, and gain insight into which stores have the shortest queues, which is important during the pandemic and beyond. Once a customer is in the store, digital signage allows for endless aisle support.” 

a person standing in front of a building

Summary

The new year 2021 holds a wealth of opportunities for retailers. We foresee retail leaders reimagining their businesses by investing in platforms that integrate IoT, AI, and edge computing technologies. Retailers will focus on increasing efficiencies to reduce costs. Modular platforms supported by an ecosystem of strong partner solutions will empower frontline workers with data, augment omnichannel fulfillment with dark stores and micro-fulfillment, leverage livestream video to enhance omnichannel, prioritize warehouse worker safety, and optimize inventory management with real-time data. 

Originally posted here.

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Skoltech researchers and their colleagues from Russia and Germany have designed an on-chip printed "electronic nose" that serves as a proof of concept for this kind of low-cost and sensitive devices to be used in portable electronics and healthcare. The paper was published in the journal ACS Applied Materials Interfaces.

The rapidly growing fields of Internet of Things (IoT) and advanced medical diagnostics require small, cost-effective, low-powered yet reasonably sensitive and selective gas-analytical systems like so-called "electronic noses." These systems can be used for noninvasive diagnostics of human breath, such as diagnosing chronic obstructive pulmonary disease (COPD) with a compact sensor system also designed at Skoltech. Some of these sensors work a lot like actual noses—say, yours—by using an array of sensors to better detect the complex signal of a gaseous compound.

One approach to creating these sensors is by additive manufacturing technologies, which have achieved enough power and precision to be able to produce the most intricate devices. Skoltech senior research scientist Fedor Fedorov, Professor Albert Nasibulin, research scientist Dmitry Rupasov and their collaborators created a multisensor "electronic nose" by printing nanocrystalline films of eight different metal oxides onto a multielectrode chip (they were manganese, cerium, zirconium, zinc, chromium, cobalt, tin, and titanium). The Skoltech team came up with the idea for this project.

"For this work, we used microplotter printing and true solution inks. There are a few things that make it valuable. First, the resolution of the printing is close to the distance between electrodes on the chip which is optimized for more convenient measurements. We show these technologies are compatible. Second, we managed to use several different oxides which enables more orthogonal signal from the chip resulting in improved selectivity. We can also speculate that this technology is reproducible and easy to be implemented in industry to obtain chips with similar characteristics, and that is really important for the 'e-nose' industry," Fedorov explained.

In subsequent experiments, the device was able to sniff out the difference between different alcohol vapors (methanol, ethanol, isopropanol, and n-butanol), which are chemically very similar and hard to tell apart, at low concentrations in the air. Since methanol is extremely toxic, detecting it in beverages and differentiating between methanol and ethanol can even save lives. To process the data, the team used linear discriminant analysis (LDA), a pattern recognition algorithm, but other machine learning algorithms could also be used for this task.

So far the device operates at rather high temperatures of 200-400 degrees Celsius, but the researchers believe that new quasi-2-D materials such as MXenes, graphene and so on could be used to increase the sensitivity of the array and ultimately allow it to operate at room temperature. The team will continue working in this direction, optimizing the materials used to lower power consumption.

Originally posted here.

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The benefits of IoT data are widely touted. Enhanced operational visibility, reduced costs, improved efficiencies and increased productivity have driven organizations to take major strides towards digital transformation. With countless promising business opportunities, it’s no surprise that IoT is expanding rapidly and relentlessly. It is estimated that there will be 75.4 billion IoT devices by 2025. As IoT grows, so do the volumes of IoT data that need to be collected, analyzed and stored. Unfortunately, significant barriers exist that can limit or block access to this data altogether.

Successful IoT data acquisition starts and ends with reliable and scalable IoT connectivity. Selecting the right communications technology is paramount to the long-term success of your IoT project and various factors must be considered from the beginning to build a functional wireless infrastructure that can support and manage the influx of IoT data today and in the future.

Here are five IoT architecture must-haves for unlocking IoT data at scale.

1. Network Ownership

For many businesses, IoT data is one of their greatest assets, if not the most valuable. This intensifies the demand to protect the flow of data at all costs. With maximum data authority and architecture control, the adoption of privately managed networks is becoming prevalent across industrial verticals.

Beyond the undeniable benefits of data security and privacy, private networks give users more control over their deployment with the flexibility to tailor their coverage to the specific needs of their campus style network. On a public network, users risk not having the reliable connectivity needed for indoor, underground and remote critical IoT applications. And since this network is privately owned and operated, users also avoid the costly monthly access, data plans and subscription costs imposed by public operators, lowering the overall total-cost-of-ownership. Private networks also provide full control over network availability and uptime to ensure users have reliable access to their data at all times.

2. Minimal Infrastructure Requirements

Since the number of end devices is often fixed to your IoT use cases, choosing a wireless technology that requires minimal supporting infrastructure like base stations and repeaters, as well as configuration and optimization is crucial to cost-effectively scale your IoT network.

Wireless solutions with long range and excellent penetration capability, such as next-gen low-power wide area networks, require fewer base stations to cover a vast, structurally dense industrial or commercial campuses. Likewise, a robust radio link and large network capacity allow an individual base station to effectively support massive amounts of sensors without comprising performance to ensure a continuous flow of IoT data today and in the future.

3. Network and Device Management

As IoT initiatives move beyond proofs-of-concept, businesses need an effective and secure approach to operate, control and expand their IoT network with minimal costs and complexity.

As IoT deployments scale to hundreds or even thousands of geographically dispersed nodes, a manual approach to connecting, configuring and troubleshooting devices is inefficient and expensive. Likewise, by leaving devices completely unattended, users risk losing business-critical IoT data when it’s needed the most. A network and device management platform provides a single-pane, top-down view of all network traffic, registered nodes and their status for streamlined network monitoring and troubleshooting. Likewise, it acts as the bridge between the edge network and users’ downstream data servers and enterprise applications so users can streamline management of their entire IoT project from device to dashboard.

4. Legacy System Integration

Most traditional assets, machines, and facilities were not designed for IoT connectivity, creating huge data silos. This leaves companies with two choices: building entirely new, greenfield plants with native IoT technologies or updating brownfield facilities for IoT connectivity. Highly integrable, plug-and-play IoT connectivity is key to streamlining the costs and complexity of an IoT deployment. Businesses need a solution that can bridge the gap between legacy OT and IT systems to unlock new layers of data that were previously inaccessible. Wireless IoT connectivity must be able to easily retrofit existing assets and equipment without complex hardware modifications and production downtime. Likewise, it must enable straightforward data transfer to the existing IT infrastructure and business applications for data management, visualization and machine learning.

5. Interoperability

Each IoT system is a mashup of diverse components and technologies. This makes interoperability a prerequisite for IoT scalability, to avoid being saddled with an obsolete system that fails to keep pace with new innovation later on. By designing an interoperable architecture from the beginning, you can avoid fragmentation and reduce the integration costs of your IoT project in the long run. 

Today, technology standards exist to foster horizontal interoperability by fueling global cross-vendor support through robust, transparent and consistent technology specifications. For example, a standard-based wireless protocol allows you to benefit from a growing portfolio of off-the-shelf hardware across industry domains. When it comes to vertical interoperability, versatile APIs and open messaging protocols act as the glue to connect the edge network with a multitude of value-deriving backend applications. Leveraging these open interfaces, you can also scale your deployment across locations and seamlessly aggregate IoT data across premises.  

IoT data is the lifeblood of business intelligence and competitive differentiation and IoT connectivity is the crux to ensuring reliable and secure access to this data. When it comes to building a future-proof wireless architecture, it’s important to consider not only existing requirements, but also those that might pop up down the road. A wireless solution that offers data ownership, minimal infrastructure requirements, built-in network management and integration and interoperability will not only ensure access to IoT data today, but provide cost-effective support for the influx of data and devices in the future.

Originally posted here.

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by Ariane Elena Fuchs

Solar power, wind energy, micro cogeneration power plants: energy from renewable sources has become indispensable, but it makes power generation and distribution far more complex. How the Internet of Things is helping make energy management sustainable.

It feels like Ground Hog Day yet again – in 2020 it happened on August 22. That was the point when the demand for raw materials exceeded the Earth’s supply and capacity to reproduce these natural resources. All reserves that are consumed from that date on cannot be regenerated in the current year. In other words, humanity is living above its means, consuming around 50 percent more energy than the Earth provides naturally.

To conserve these precious resources and reduce climate-damaging CO2 emissions, the energy we need must come from renewable sources such as wind, sun and water. This is the only way to reduce both greenhouse gases and our fossil fuel use. Fortunately, a start has now been made: In 2019, renewable energies – predominantly from wind and sun – will already cover almost 43 percent of Germany's energy requirements and the trend is rising.

DECENTRALIZING ENERGY PRODUCTION

This also means, however, that the traditional energy management model – a few power plants supplying a lot of consumers – is outdated. After all, the phasing out of large nuclear and coal-fired power plants doesn’t just have consequences for Germany’s CO2 balance. Shifting electricity production to wind, solar and smaller cogeneration plants reverses the previous pattern of energy generation and distribution from a highly centralized to an increasingly decentralized organizational structure. Instead of just a few large power plants sending electricity to the grid, there are now many smaller energy sources such as solar panels and wind turbines. This has made the management of it all – including the optimal distribution of the electricity – far more complex as a result. It’s up to the energy sector to wrangle this challenging transformation. As the country’s energy is becoming more sustainable, it’s also becoming harder to organize, since the energy generated from wind and sun cannot be planned in advance as easily as coal and nuclear power can. What’s more, there are thousands of wind turbines and solar panels making electricity and feeding it into the grid. This has made the management of the power network extremely difficult. In particular, there’s a lack of real-time information about the amount of electricity being generated.

KEY TECHNOLOGY IOT: FROM ENERGY FLOW TO DATA STREAM

This is where the Internet of Things comes into play: IoT can supply exactly this data from every power generator and send it to a central location. Once there, it can be evaluated before ideally enabling the power grid to be controlled automatically. The result is an IoT ecosystem. In order to operate wind farms more efficiently and reliably, a project team is currently developing an IoT-supported system that bundles and processes all relevant parameters and readings at a wind farm. They can then reconstruct the current operating and maintenance status of individual turbines. This information can be used to detect whether certain components are about to wear out and replace them before a turbine fails.

POTENTIAL FOR NEW BUSINESS MODELS

According to a recent Gartner study, the Internet of Things (IoT) is becoming a key technology for monitoring and orchestrating the complex energy and water ecosystem. In addition, consumers want more control over energy prices and more environmentally friendly power products. With the introduction of smart metering, data from so-called prosumers is becoming increasingly important. These energy producing consumers act like operators of the photovoltaic systems on their roofs. IoT sensors are used to collect the necessary power generation information. Although they are only used locally and for specific purposes, they provide energy companies with a lot of data. In order to be able to use the potential of this information for the expansion of renewable energy, it must be combined and evaluated intelligently. According to Gartner, IoT has the potential to change the energy value chain in four key areas: It enables new business models, optimizes asset management, automates operations and digitalizes the entire value chain from energy source to kWh.

ENERGY TRANSITION REQUIRES TECHNOLOGICAL CHANGE

Installing smaller power-generating systems will soon no longer pose the greatest challenge for operators. In the near future, coherently linking, integrating and controlling them will be the order of the day. The energy transition is therefore spurring technological change on a grand scale. For example, smart grids will only function properly and increase overall capacity when data on generation, consumption and networks is available in real-time. The Internet of Things enables the necessary fast data processing, even from the smallest consumers and prosumers on the grid. With the help of the Internet of Things, more and more household appliances can communicate with the Internet. These devices are then in turn connected to a smart meter gateway, i.e. a hub for the intelligent management of consumers, producers and storage locations at private households and commercial enterprises. To be able to use the true potential of this information, however, all the data must flow together into a common data platform, so that it can be analyzed intelligently.

FROM INDIVIDUAL APPLICATIONS TO AN ECOSYSTEM

For the transmission of data from the Internet of Things, Germany has national fixed-line and mobile networks available. New technology such as the 5G mobile standard allows data to be securely and reliably transferred to the cloud either directly via the 5G network or a 5G campus networks. Software for data analytics and AI tailored to energy firms are now available – including monitoring, analysis, forecasting and optimization tools. Any analyzed data can be accessed via web browsers and in-house data centers. Taken together, it all provides the energy sector with a comprehensive IoT ecosystem for the future.

Originally posted here.

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by Philipp Richert

New digital and IoT use cases are becoming more and more important. When it comes to the adoption of these new technologies, there are several different maturity levels, depending on the domain. Within the retail industry, and specifically food retail, we are currently seeing the emergence of a host of IoT use cases.

Two forces are driving this: a technology push, in which suppliers in the retail domain have technologies available to build retail IoT use cases within a connected store; and a market pull by their customers, who are boosting the demand for such use cases.

Retail-IoT-use-case-technology-push-and-market-pull-1136x139.png

However, we also need to ask the following questions: What are IoT use cases good for? And what are they aiming at? We currently see three different fields of application:

  • Increasing efficiency and optimizing processes
  • Increasing customer satisfaction
  • Increasing revenues with new business models

No matter what is most important for your organization or whatever your focus, it is crucial to set up a process that provides guidance for identifying the right use cases. In the following section, we share some insights on how retailers can best design this process. We collated these insights together with the team from the Food Tech Campus.

How to identify the right retail IoT use cases

When identifying the right use cases for their stores, retailers should make sure to look into all phases within the entire innovation process: from problem description and idea collation to solution concept and implementation. Within this process, it is also essential to consider the so-called innovator’s trilemma and ensure that use cases are:

  • Desirable ones that your customer really needs
  • Technically feasible
  • Profitable for your sustainable business development

Before we can actually start identifying retail IoT use cases, we need to define search fields so that we can work on one topic with greater dedication and focus. We must then open up the problem space in order to extract the most relevant problems and pain points. Starting with prioritized and selected pain points, we then open up the solution space in order to define several solution concepts. Once these have been validated, the result should be a well-defined problem statement that concisely describes one singular pain point.

In the following, we want to take a deep dive into the different phases of the process while giving concrete examples, tips and our top-rated tools. Enjoy!

Search fields

Retailers possess expertise and face challenges at various stages along their complex process chains. It helps here to focus on a specific target group in order to avoid distraction. Target groups are typically users or customers in a defined environment. A good example would be to focus your search on processes that happen inside a store location and are relevant to the customer (e.g., the food shopper).

Understand and observe problems

User research, observation and listening are keys to a well-defined problem statement that allows for further ideation. Embedding yourself in various situations and conducting interviews with all the stakeholders visiting or operating a store should be the first steps. Join employees around the store for a day or two and support them during their everyday tasks. Empathize, look for any friction and ask questions. Take your key findings into workshops and spend some time isolating specific causes. Use personas based on your user research and make use of frameworks and canvas templates in order to structure your findings. Use working titles to name the specific problem statements. One example might be: Long queueing as a major nuisance for customers.

Synthesize findings

Are your findings somehow connected? Single-purpose processes and their owners within a store environment are prone to isolated views. Creating a common problem space increases the chances of adoption of any solution later. So it is worth taking the time to map out all findings and take a look at projects in the past and their outcome. In our example, queueing is linked to staff planning, lack of communication and unpredictable customer behavior.

Prioritize problems and pain points

Ask users or stakeholders to give their view on defined problem statements and let them vote. Challenge their view and make them empathize and broaden their view towards a more holistic benefit. Once the quality of a problem statement has been assessed, evaluate the economic implications. In our example, this could mean that queueing affects most employees in the store, directly or indirectly. This problem might be solved through technology and should be further explored.

The result of a well-structured problem statement list should consist of a few new insights that might result in quick gains; one or two major known pain points, where the solution might be viable and feasible; and a list with additional topics that exist but are not too pressing at the moment.

Define opportunity areas

Map technologies and problems together. Are there any strategic goals that these problem statements might be assigned to? Have things changed in terms of technical feasibility (e.g., has the cost of a technology dropped over the past three years?). Can problems be validated within a larger setup easily or are we talking about singular use cases? All these considerations should lead towards the most attractive problem to solve. Again, in our example, this might be: Queuing is a major problem in most locations, satisfying our customers should be our main goal, existing solutions are too expensive or inflexible.

Retail-IoT-use-case-problem-solution-space-1-1136x580.png

When identifying the right use cases for their stores, retailers should make sure to look into all phases within the entire innovation process: from problem description and idea collation to solution concept and implementation.

Ideate and explore use cases

When conducting an ideation session, it is very helpful to bring in trends that are relevant to the defined problem areas so as to help boost creativity. In our example, for instance, this might be technology trends such as frictionless checkout for retail, hybrid checkout concepts, bring your own device (BYOD) and sensor approaches. It is always important to keep the following in mind: What do these trends mean for the customer journey in-store and how can they be integrated in (legacy) environments?

Define solutions concepts

In the process of further defining the solution concepts, it is essential to evaluate the market potential and to consider customer and user feedback. Depending on the solution, it might be necessary to ask the various stakeholders – from store managers to personnel to customers – in order to get a clearer picture. When talking to customers or users, it is also helpful to bring along scribbles, pictures or prototypes in order to increase immersion. The insights gathered in this way help to validate assumptions and to pilot the concept accordingly.

Set metrics and KPIs to prove success

Defining data-based metrics and KPIs is essential for a successful solution. When setting up metrics and KPIs, you need to consider two aspects:

  • Use existing data – e.g., checkout frequency – in order to demonstrate the impact of the new solution. This offers a very inexpensive way of validating the business potential of the solution early on.
  • Use new data – e.g. measure waiting time – from the solution and evaluate it on a regular basis. This helps to get a better understanding of whether you are collecting the right data and to derive measures that help to improve your solution.

Prototype for quick insights

In terms of technology, practically everything is feasible today. However, the value proposition of a use case (in terms of business and users) can remain unclear and requires testing. Instead of building a technical prototype, it can be helpful to evaluate the value proposition of the solution with humans (empathy prototyping). This could be a person triggering an alarm based on the information at hand instead of an automatic action. Insights and lessons learnt from this phase can be used alongside the technical realization (proof-of-concept) in order to tweak specific features of the solution.

Initiate a PoC for technical feasibility

When it comes to technical feasibility, a clear picture of the objectives and key results (OKRs) for the PoC is essential. This helps to set the boundaries for a lean process with respect to the installation of hardware, an efficient timeline and minimum costs. Furthermore, a well-defined test setup fosters short testing timespans that often yield all needed results.

How IoT platforms can help build retail IoT use cases

The strong trend towards digitization within the retail industry opens up new use cases for the (food) retail industry. In order to make the most of this trend and to build on IoT, it is crucial first of all to determine which use cases to start with. Every retailer has a different focus and needs for their stores.

In the course of our retail projects, we have identified some of the recurring use cases that food retailers are currently implementing. We have also learnt a lot about how they can best leverage IoT in order to build a connected store. We share these insights in our white paper “The connected retail store.”

Originally posted here.

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By Sanjay Tripathi, Lauren Luellwitz, and Kevin Egge

There are petabytes of data generated by intelligent, interconnected and autonomous systems of Industry 4.0. When combined with artificial intelligence tools that provide actionable insight, it has the potential to improve every function within a plant, i.e. operations, engineering, quality, reliability and maintenance.

The maintenance function, while crucial to the smooth functioning of a plant has, until recently not seen much innovation. Many among us have experienced the equipment downtime, process drifts, massive hits to yield, and decline in product reliability because of maintenance performed poorly or late. Yet, Enterprise Asset Management (EAM) systems – ERP systems that help maintain assets – remained as systems of record that typically generated work-orders and recorded maintenance performed. Even as production processes became mind-numbingly complex, EAM systems remained much the same.

IBM Maximo 8.0, or Maximo Application Suite, is one example of a system that combines artificial intelligent (AI), big data and cloud computing technologies with domain expertise from operating technologies (OT) to simplify maintenance and deliver production resilience.

Maximo 8.0 leverages AI to visually inspect gas pipelines, rail tracks, bridges and tunnels; AI guides technicians as they conduct complex repairs; it provides maintenance supervisors real-time visibility into the health and safety of their technicians. Domain expertise is incorporated in the form of data to train AI models. These capabilities improve the ability to avoid unscheduled downtime, improve first-time-fix rate, and reduce safety incidents.

Maintenance records residing in Maximo are combined with real-time operational data from production assets and their associated asset model to better predict when maintenance is required. In this example, asset models embody domain expertise. These models characterize how a production asset such as a power generator or catalytic converter should perform in the context of where it is installed in the process.

The Maximo application itself is encapsulated (containerized) using Red Hat’s OpenShift technology. Containerization allows the application to be easily deployed on-premises, on private clouds or hybrid clouds. This flexibility in deployment benefits IT organizations that need to continually evolve their infrastructure, which is almost every organization.

Maximo 8.0 is available as a suite that includes both core and advanced capabilities. A single software entitlement provides access to all capabilities. The entitlement provides access to the core EAM functionality of work and resource scheduling, asset management, industry-specific customizations, EHS guidelines, and mobile functionality. And it provides access to advanced functionality such as Maximo Monitor, which automatically detects anomalies in how an asset may be performing; Maximo Health, which measures equipment health; Maximo Predict, which, as the name suggests, predicts when maintenance is required; and Maximo Assist which assists technicians conduct repairs.

Originally posted here.

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by Olivier Pauzet

Over the past year, we have seen the Industrial IoT (IIoT) take an important step forward, crossing the chasm that previously separated IIoT early adopters from the majority of companies.

New solutions like Octave, Sierra Wireless’ edge-to-cloud solution for connecting industrial assets, have greatly simplified the IIoT, making it possible now for practically any company to securely extract, transmit, and act on data from bio-waste collectors, liquid fertilizer tanks, water purifiers, hot water heaters and other industrial equipment.

So, what IIoT trends will these 2020 developments lead to in 2021? I expect that they will drive greater adoption of the IIoT next year, as manufacturing, utility, healthcare, and other organizations further realize that they can help their previously silent industrial assets speak using the APIs integrated in new IoT solutions. At the same time, I expect we will start to see the development of some revolutionary IIoT applications that use 5G’s Ultra-Reliable, Low-Latency Communications (URLLC) capabilities to change the way our factories, electric grid, and healthcare systems operate.

In 2021, Industrial Equipment APIs Will Give Quiet Equipment A Voice

Cloud APIs have transformed the tech industry, and with it, our digital economy. By enabling SaaS and other cloud-based applications to easily and securely talk to each other, cloud APIs have vastly expanded the value of these applications to users. These APIs have also spawned billion-dollar companies like Stripe, Tableau, and Twilio, whose API-focused business models have transformed the online payments, data visualization, and customer service markets.

2021 will be the year industrial companies begin seeing their markets transformed by APIs, as more of these companies begin using industrial equipment APIs built into new IIoT solutions to enable their industrial assets to talk to the cloud.

Using new edge-to-cloud solutions - like Octave -with built-in Industrial equipment APIs for Modbus and other industrial communications protocols, these companies will be able to securely connect these assets to the cloud almost as easily as if this equipment was a cloud-based application.

In fact, by simply plugging a low-cost IoT gateway with these IIoT APIs into their industrial equipment, they will be able to deploy IIoT applications that allow them to remotely monitor, maintain, and control this equipment. Then, using these applications, they can lower equipment downtime, reduce maintenance costs, launch new Equipment-as-a-Service business models, and innovate faster.

Industrial companies have been trying to connect their assets to the cloud for years, but have been stymied by the complexity, time, and expense involved in doing so. In 2021, industrial equipment APIs will provide these companies with a way to simply, quickly, and cheaply connect this equipment to the cloud. By giving a voice to billions of pieces of industrial equipment, these Industrial IoT APIs will help bring about the productivity, sustainability, and other benefits Industry 4.0 has long promised.

In 2021 Manufacturing, Utility and Healthcare Will Drive Growth of the Industrial IoT

Until recently, the consumer sector, and especially the smart home market, has led the way in adopting the IoT, as the success of the Google Nest smart thermostat, the Amazon Echo smart speaker and Ring smart doorbell, and the Phillips Hue smart lights demonstrate. However, in 2021 another IIoT trend we can expect to see is the industrial sector starting to catch up to the consumer market regarding the IoT, with the manufacturing, utility, and healthcare markets leading the way.

For example, new IIoT solutions now make it possible for Original Equipment Manufacturers (OEMs) and other manufacturing companies to simply plug their equipment into the IIoT and begin acting on data from this equipment almost immediately. This has lowered the time to value for IIoT applications to the point where companies can begin reaping financial benefits greater than the total cost for their IIoT application in a few short months.

At this point, manufacturers who don’t have a plan to integrate the IIoT into their assets are, to put it bluntly, leaving money on the table – money their competitors will happily snap up with their own new connected industrial equipment offerings if they do not.

Like manufacturing companies, utilities will ramp up their use of the IIoT in 2021, as they seek to improve their operational efficiency, customer engagement, reliability, and sustainability. For example, utilities will increasingly use the IIoT to perform remote diagnostics and predictive maintenance on their grid infrastructure, reducing this equipment’s downtime while also lowering maintenance costs. In addition, a growing number of utilities will use the IIoT to collect and analyze data on their wind, solar and other renewable energy generation portfolios, allowing them to reduce greenhouse gas emissions while still balancing energy supply and demand on the grid.

Along with manufacturing and utilities, healthcare is the third market sector I expect to lead the way in adopting the IIoT in 2021. The COVID-19 pandemic has demonstrated to healthcare providers how connectivity – such as Internet-based telemedicine solutions -- can improve patient outcomes while reducing their costs. In 2021 they will increase their use of the IIoT, as they work to extend this connectivity to patient monitors, scanners and other medical devices. With the Internet of Medical Things (IoMT), healthcare providers will be better able to prepare patient treatments, remotely monitor and respond to changes to their patients’ conditions, and generate health care treatment documents.

Revolutionary Ultra-Reliable, Low-Latency 5G Applications Will Begin to Be Developed

There is a lot of buzz regarding 5G New Radio (NR) in the IIoT market. However, having been designed to co-exist with 4G LTE, most of 5G NR’s impact in this market is still evolutionary, not revolutionary. Companies are beginning to adopt 5G to wring better performance out of their existing IIoT applications, or to future-proof their connectivity strategies. But they are doing this while continuing to use LTE, as well as Low Power Wide Area (LPWA) 5G technologies, like LTE-M and NB-IoT, for now.

In 2021 however I think we will begin to see companies starting to develop revolutionary new IIoT application proof of concepts designed to take advantage of 5G NR’s Ultra-Reliable, Low-Latency Communications (URLLC) capabilities. These URLLC applications – including smart Automated Guided Vehicle (AGVs) for manufacturing, self-healing energy grids for utilities and remote surgery for health care – are simply not possible with existing wireless technologies.

Thanks to its ability to deliver ultra-high reliability and latencies as low as one millisecond, 5G NR enables companies to finally build URLLC applications – especially when 5G NR is used in conjunction with new edge computing technologies.

It will be a long time before any of these URLLC application proof-of-concepts are commercialized. But as far as 5G Wave 5+, next year is when we will first begin seeing this wave forming out at sea. And when it does eventually reach shore, it will have a revolutionary impact on our connected economy.

Originally posted here.

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By Sanjay Tripathi, Kevin Egge, and Shane Kehoe

Each Industrial Revolution has been catalyzed by the convergence of technologies from multiple domains. Industry 4.0 is no different.

Machines were first introduced into a manual manufacturing process between 1760 and 1820.  But, it was the concurrent introduction of means to power machines that led to the First Industrial Revolution. An example is the first commercially viable Textile Power Loom which was introduced by Edmund Cartwright in England. It used water-power at first. But in two short years water-powered looms were replaced with looms powered with the steam-engines created by James Watts. The relatively smaller steam-engines allowed textile looms to be deployed in many sites enabling persons to be employed in factories.

Multiple innovations such as new manufacturing methods, electricity, steel, and machine tools ushered in the era of mass manufacturing and the Second Industrial Revolution. Henry Ford’s River Rouge Complex in Michigan, completed in 1928, deployed these modern inventions and was the largest integrated factory in the world at that time. The era of mass manufacturing subsequently brought about an explosion in the consumption of goods by households.

The Third Industrial Revolution improved Automation and Controls across many industries through the use of Programmable Logic Controllers (PLCs). PLCs were first introduced by Modicon in 1969. PLC-based automation and controls were introduced to a mostly mechanical world, and helped improve yields and decrease manufacturing costs. This revolution helped provide cheaper products.

Fast forward to the Industry 4.0 Revolution made possible by the synergistic combination of expertise from the worlds of Operating Technologies (OT) and Information Technologies (IT). The current revolution is bringing about intelligent, interconnected and autonomous manufacturing equipment and systems. This is by augmenting deep domain expertise within OT companies with IT technologies such as artificial intelligence (AI), big data, cloud computing and ubiquitous connectivity.

The widespread use of open protocols across heterogeneous equipment makes it feasible to optimize horizontally across previously disjointed processes. In addition, owner/operators of assets can more easily link the shop-floor to the top-floor. Connections across multiple layers of the ISA-95/Purdue Model stack provides greater vertical visibility and added ability to optimize processes.

The increased integration brings together both OT data (from sensors, PLCs, DCS, SCADA systems) and IT data (from MES, ERP systems). However, this integration has different impacts on different functions such as operations, engineering, quality, reliability, and maintenance.

To learn more about how the integration positively impacts the organization, read the next installment in this series to see how you can bridge the gap between OT and IT teams to improve production resilience.

Originally posted here.

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Then it seemed that overnight, millions of workers worldwide were told to isolate and work from home as best as they could. Businesses were suddenly forced to enable remote access for hundreds or thousands of users, all at once, from anywhere across the globe. Many companies that already offered VPN services to a small group of remote workers scurried to extend those capabilities to the much larger workforce sequestering at home. It was a decision made in haste out of necessity, but now it’s time to consider, is VPN the best remote access technology for the enterprise, or can other technologies provide a better long-term solution?

Long-term Remote Access Could Be the Norm for Some Time

Some knowledge workers are trickling back to their actual offices, but many more are still at home and will be for some time. Global Workplace Analytics estimates that 25-30% of the workforce will still be working from home multiple days a week by the end of 2021. Others may never return to an official office, opting to remain a work-from-home (WFH) employee for good.

Consequently, enterprises need to find a remote access solution that gives home-based workers a similar experience as they would have in the office, including ease of use, good performance, and a fully secure network access experience. What’s more, the solution must be cost effective and easy to administer without the need to add more technical staff members.

VPNs are certainly one option, but not the only one. Other choices include appliance-based SD-WAN and SASE. Let’s have a look at each approach.

VPNs Weren’t Designed to Support an Entire Workforce

While VPNs are a useful remote access solution for a small portion of the workforce, they are an inefficient technology for giving remote access to a very large number of workers. VPNs are designed for point-to-point connectivity, so each secure connection between two points – presumably a remote worker and a network access server (NAS) in a datacenter – requires its own VPN link. Each NAS has a finite capacity for simultaneous users, so for a large remote user base, some serious infrastructure may be needed in the datacenter.

Performance can be an issue. With a VPN, all communication between the user and the VPN is encrypted. The encryption process takes time, and depending on the type of encryption used, this may add noticeable latency to Internet communications. More important, however, is the latency added when a remote user needs access to IaaS and SaaS applications and services. The traffic path is convoluted because it must travel between the end user and the NAS before then going out to the cloud, and vice versa on the way back.

An important issue with VPNs is that they provide overly broad access to the entire network without the option of controlling granular user access to specific resources. Stolen VPN credentials have been implicated in several high-profile data breaches. By using legitimate credentials and connecting through a VPN, attackers were able to infiltrate and move freely through targeted company networks. What’s more, there is no scrutiny of the security posture of the connecting device, which could allow malware to enter the network via insecure user devices.

SD-WAN Brings Intelligence into Routing Remote Users’ Traffic

Another option for providing remote access for home-based workers is appliance-based SD-WAN. It brings a level of intelligence to the connectivity that VPNs don’t have. Lee Doyle, principal analyst with Doyle Research, outlines the benefits of using SD-WAN to connect home office users to their enterprise network:

  • Prioritization for mission-critical and latency-sensitive applications
  • Accelerated access to cloud-based services
  • Enhanced security via encryption, VPNs, firewalls and integration with cloud-based security
  • Centralized management tools for IT administrators

One thing to consider about appliance-based SD-WAN is that it’s primarily designed for branch office connectivity—though it can accommodate individual users at home as well. However, if a company isn’t already using SD-WAN, this isn’t a technology that is easy to implement and setup for hundreds or thousands of home-based users. What’s more, a significant investment must be made in the various communication and security appliances.

SASE Provides a Simpler, More Secure, Easily Scalable Solution

Cato’s Secure Access Service Edge (or SASE) platform provides a great alternative to VPN for remote access by many simultaneous workers. The platform offers scalable access, optimized connectivity, and integrated threat prevention that are needed to support continuous large-scale remote access.

Companies that enable WFH using Cato’s platform can scale quickly to any number of remote users with ease. There is no need to set up regional hubs or VPN concentrators. The SASE service is built on top of dozens of globally distributed Points of Presence (PoPs) maintained by Cato to deliver a wide range of security and networking services close to all locations and users. The complexity of scaling is all hidden in the Cato-provided PoPs, so there is no infrastructure for the organization to purchase, configure or deploy. Giving end users remote access is as simple as installing a client agent on the user’s device, or by providing clientless access to specific applications via a secure browser.

Cato’s SASE platform employs Zero Trust Network Access in granting users access to the specific resources and applications they need to use. This granular-level security is part of the identity-driven approach to network access that SASE demands. Since all traffic passes through a full network security stack built into the SASE service, multi-factor authentication, full access control, and threat prevention are applied to traffic from remote users. All processing is done within the PoP closest to the users while enforcing all corporate network and security policies. This eliminates the “trombone effect” associated with forcing traffic to specific security choke points on a network. Further, admins have consistent visibility and control of all traffic throughout the enterprise WAN.

SASE Supports WFH in the Short-term and Long-term

While some workers are venturing back to their offices, many more are still working from home—and may work from home permanently. The Cato SASE platform is the ideal way to give them access to their usual network environment without forcing them to go through insecure and inconvenient VPNs.

Originally posted here

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Today the world is obsessed with the IoT, as if this is a new concept. We've been building the IoT for decades, but it was only recently some marketing "genius" came up with the new buzz-acronym.

Before there was an IoT, before there was an Internet, many of us were busy networking. For the Internet itself was a (brilliant) extension of what was already going on in the industry.

My first experience with networking was in 1971 at the University of Maryland. The school had a new computer, a $10 million Univac 1108 mainframe. This was a massive beast that occupied most of the first floor of a building. A dual-processor machine it was transistorized, though the control console did have some ICs. Rows of big tape drives mirrored the layman's idea of computers in those days. Many dishwasher-sized disk drives were placed around the floor and printers, card readers and other equipment were crammed into every corner. Two Fastrand drum memories, each consisting of a pair of six-foot long counterrotating drums, stored a whopping 90 MB each. Through a window you could watch the heads bounce around.

The machine was networked. It had a 300 baud modem with which it could contact computers at other universities. A primitive email system let users create mail which was queued till nightfall. Then, when demands on the machine were small, it would call the appropriate remote computer and forward mail. The system operated somewhat like today's "hot potato" packets, where the message might get delivered to the easiest machine available, which would then attempt further forwarding. It could take a week to get an email, but at least one saved the $0.08 stamp that the USPS charged.

The system was too slow to be useful. After college I lost my email account but didn't miss it at all.

By the late 70s many of us had our own computers. Mine was a home-made CP/M machine with a Z80 processor and a small TV set as a low-res monitor. Around this time Compuserve came along and I, like so many others, got an account with them. Among other features, users had email addresses. Pretty soon it was common to dial into their machines over a 300 baud modem and exchange email and files. Eventually Compuserve became so ubiquitous that millions were connected, and at my tools business during the 1980s it was common to provide support via this email. The CP/M machine gave way to a succession of PCs, Modems ramped up to 57 K baud.

My tools business expanded rapidly and soon we had a number of employees. Sneakernet was getting less efficient so we installed an Arcnet network using Windows 3.11. That morphed into Ethernet connections, though the cursing from networking problems multiplied about as fast as the data transfers. Windows was just terrible at maintaining reliable connectivity.

In 1992 Mike Lee, a friend from my Boys Night Out beer/politics/sailing/great friends group, which still meets weekly (though lately virtually) came by the office with his laptop. "You have GOT to see this" he intoned, and he showed me the world-wide web. There wasn't much to see as there were few sites. But the promise was shockingly clear. I was stunned.

The tools business had been doing well. Within a month we spent $100k on computers, modems and the like and had a new business: Softaid Internet Services. SIS was one of Maryland's first ISPs and grew quickly to several thousand customers. We had a T1 connection to MAE-EAST in the DC area which gave us a 1.5 Mb/s link… for $5000/month. Though a few customers had ISDN connections to us, most were dialup, and our modem shelf grew to over 100 units with many big fans keeping the things cool.

The computers all ran BSD Unix, which was my first intro to that OS.

I was only a few months back from a failed attempt to singlehand my sailboat across the Atlantic and had written a book-length account of that trip. I hastily created a web page of that book to learn about using the web. It is still online and has been read several million times in the intervening years. We put up a site for the tools business which eventually became our prime marketing arm.

The SIS customers were sometimes, well, "interesting." There was the one who claimed to be a computer expert, but who tried to use the mouse by waving it around over the desk. Many had no idea how to connect a modem. Others complained about our service because it dropped out when mom would pick up the phone to make a call over the modem's beeping. A lot of handholding and training was required.

The logs showed a shocking (to me at the time) amount of porn consumption. Over lunch an industry pundit explained how porn drove all media, from the earliest introduction of printing hundreds of years earlier.

The woman who ran the ISP was from India. She was delightful and had a wonderful marriage. She later told me it had been arranged; they met  their wedding day. She came from a remote and poor village and had had no exposure to computers, or electricity, till emigrating to the USA.

Meanwhile many of our tools customers were building networking equipment. We worked closely with many of them and often had big routers, switches and the like onsite that our engineers were working on. We worked on a lot of what we'd now call IoT gear: sensors et al connected to the net via a profusion of interfaces.

I sold both the tools and Internet businesses in 1997, but by then the web and Internet were old stories.

Today, like so many of us, I have a fast (250 Mb/s) and cheap connection into the house with four wireless links and multiple computers chattering to each other. Where in 1992 the web was incredibly novel and truly lacking in useful functionality, now I can't imagine being deprived of it. Remember travel agents? Ordering things over the phone (a phone that had a physical wire connecting it to Ma Bell)? Using 15 volumes of an encyclopedia? Physically mailing stuff to each other?

As one gets older the years spin by like microseconds, but it is amazing to stop and consider just how much this world has changed. My great grandfather lived on a farm in a world that changed slowly; he finally got electricity in his last year of life. His daughter didn't have access to a telephone till later in life, and my dad designed spacecraft on vellum and starched linen using a slide rule. My son once saw a typewriter and asked me what it was; I mumbled that it was a predecessor of Microsoft Word.

That he understood. I didn't have the heart to try and explain carbon paper.

Originally posted HERE.

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When I think about the things that held the planet together in 2020, it was digital experiences delivered over wireless connectivity that made remote things local.

While heroes like doctors, nurses, first responders, teachers, and other essential personnel bore the brunt of the COVID-19 response, billions of people around the world found themselves cut off from society. In order to keep people safe, we were physically isolated from each other. Far beyond the six feet of social distancing, most of humanity weathered the storm from their homes.

And then little by little, old things we took for granted, combined with new things many had never heard of, pulled the world together. Let’s take a look at the technologies and trends that made the biggest impact in 2020 and where they’re headed in 2021:

The Internet

The global Internet infrastructure from which everything else is built is an undeniable hero of the pandemic. This highly-distributed network designed to withstand a nuclear attack performed admirably as usage by people, machines, critical infrastructure, hospitals, and businesses skyrocketed. Like the air we breathe, this primary facilitator of connected, digital experiences is indispensable to our modern society. Unfortunately, the Internet is also home to a growing cyberwar and security will be the biggest concern as we move into 2021 and beyond. It goes without saying that the Internet is one of the world’s most critical utilities along with water, electricity, and the farm-to-table supply chain of food.

Wireless Connectivity

People are mobile and they stay connected through their smartphones, tablets, in cars and airplanes, on laptops, and other devices. Just like the Internet, the cellular infrastructure has remained exceptionally resilient to enable communications and digital experiences delivered via native apps and the web. Indoor wireless connectivity continues to be dominated by WiFi at home and all those empty offices. Moving into 2021, the continued rollout of 5G around the world will give cellular endpoints dramatic increases in data capacity and WiFi-like speeds. Additionally, private 5G networks will challenge WiFi as a formidable indoor option, but WiFi 6E with increased capacity and speed won’t give up without a fight. All of these developments are good for consumers who need to stay connected from anywhere like never before.

Web Conferencing

With many people stuck at home in 2020, web conferencing technology took the place of traveling to other locations to meet people or receive education. This technology isn’t new and includes familiar players like GoToMeeting, Skype, WebEx, Google Hangouts/Meet, BlueJeans, FaceTime, and others. Before COVID, these platforms enjoyed success, but most people preferred to fly on airplanes to meet customers and attend conferences while students hopped on the bus to go to school. In 2020, “necessity is the mother of invention” took hold and the use of Zoom and Teams skyrocketed as airplanes sat on the ground while business offices and schools remained empty. These two platforms further increased their stickiness by increasing the number of visible people and adding features like breakout rooms to meet the demands of businesses, virtual conference organizers, and school teachers. Despite the rollout of the vaccine, COVID won’t be extinguished overnight and these platforms will remain strong through the first half of 2021 as organizations rethink where and when people work and learn. There’s way too many players in this space so look for some consolidation.

E-Commerce

“Stay at home” orders and closed businesses gave e-commerce platforms a dramatic boost in 2020 as they took the place of shopping at stores or going to malls. Amazon soared to even higher heights, Walmart upped their game, Etsy brought the artsy, and thousands of Shopify sites delivered the goods. Speaking of delivery, the empty city streets became home to fleets FedEx, Amazon, UPS, and DHL trucks bringing packages to your front doorstep. Many retail employees traded-in working at customer-facing stores for working in a distribution centers as long as they could outperform robots. Even though people are looking forward to hanging out at malls in 2021, the e-commerce, distribution center, delivery truck trinity is here to stay. This ball was already in motion and got a rocket boost from COVID. This market will stay hot in the first half of 2021 and then cool a bit in the second half.

Ghost Kitchens

The COVID pandemic really took a toll on restaurants in the 2020, with many of them going out of business permanently. Those that survived had to pivot to digital and other ways of doing business. High-end steakhouses started making burgers on grills in the parking lot, while takeout pizzerias discovered they finally had the best business model. Having a drive-thru lane was definitely one of the keys to success in a world without waiters, busboys, and hosts. “Front of house” was shut down, but the “back of house” still had a pulse. Adding mobile web and native apps that allowed customers to easily order from operating “ghost kitchens” and pay with credit cards or Apple/Google/Samsung Pay enabled many restaurants to survive. A combination of curbside pickup and delivery from the likes of DoorDash, Uber Eats, Postmates, Instacart and Grubhub made this business model work. A surge in digital marketing also took place where many restaurants learned the importance of maintaining a relationship with their loyal customers via connected mobile devices. For the most part, 2021 has restauranteurs hoping for 100% in-person dining, but a new business model that looks a lot like catering + digital + physical delivery is something that has legs.

The Internet of Things

At its very essence, IoT is all about remotely knowing the state of a device or environmental system along with being able to remotely control some of those machines. COVID forced people to work, learn, and meet remotely and this same trend applied to the industrial world. The need to remotely operate industrial equipment or an entire “lights out” factory became an urgent imperative in order to keep workers safe. This is yet another case where the pandemic dramatically accelerated digital transformation. Connecting everything via APIs, modeling entities as digital twins, and having software bots bring everything to life with analytics has become an ROI game-changer for companies trying to survive in a free-falling economy. Despite massive employee layoffs and furloughs, jobs and tasks still have to be accomplished, and business leaders will look to IoT-fueled automation to keep their companies running and drive economic gains in 2021.

Streaming Entertainment

Closed movie theaters, football stadiums, bowling alleys, and other sources of entertainment left most people sitting at home watching TV in 2020. This turned into a dream come true for streaming entertainment companies like Netflix, Apple TV+, Disney+, HBO Max, Hulu, Amazon Prime Video, Youtube TV, and others. That said, Quibi and Facebook Watch didn’t make it. The idea of binge-watching shows during the weekend turned into binge-watching every season of every show almost every day. Delivering all these streams over the Internet via apps has made it easy to get hooked. Multiplayer video games fall in this category as well and represent an even larger market than the film industry. Gamers socially distanced as they played each other from their locked-down homes. The rise of cloud gaming combined with the rollout of low-latency 5G and Edge computing will give gamers true mobility in 2021. On the other hand, the video streaming market has too many players and looks ripe for consolidation in 2021 as people escape the living room once the vaccine is broadly deployed.

Healthcare

With doctors and nurses working around the clock as hospitals and clinics were stretched to the limit, it became increasingly difficult for non-COVID patients to receive the healthcare they needed. This unfortunate situation gave tele-medicine the shot in the arm (no pun intended) it needed. The combination of healthcare professionals delivering healthcare digitally over widespread connectivity helped those in need. This was especially important in rural areas that lacked the healthcare capacity of cities. Concurrently, the Internet of Things is making deeper inroads into delivering the health of a person to healthcare professionals via wearable technology. Connected healthcare has a bright future that will accelerate in 2021 as high-bandwidth 5G provides coverage to more of the population to facilitate virtual visits to the doctor from anywhere.

Working and Living

As companies and governments told their employees to work from home, it gave people time to rethink their living and working situation. Lots of people living in previously hip, urban, high-rise buildings found themselves residing in not-so-cool, hollowed-out ghost towns comprised of boarded-up windows and closed bars and cafés. Others began to question why they were living in areas with expensive real estate and high taxes when they not longer had to be close to the office. This led to a 2020 COVID exodus out of pricey apartments/condos downtown to cheaper homes in distant suburbs as well as the move from pricey areas like Silicon Valley to cheaper destinations like Texas. Since you were stuck in your home, having a larger house with a home office, fast broadband, and a back yard became the most important thing. Looking ahead to 2021, a hybrid model of work-from-home plus occasionally going into the office is here to stay as employees will no longer tolerate sitting in traffic two hours a day just to sit in a cubicle in a skyscraper. The digital transformation of how and where we work has truly accelerated.

Data and Advanced Analytics

Data has shown itself to be one of the world’s most important assets during the time of COVID. Petabytes of data has continuously streamed-in from all over the world letting us know the number of cases, the growth or decline of infections, hospitalizations, contact-tracing, free ICU beds, temperature checks, deaths, and hotspots of infection. Some of this data has been reported manually while lots of other sources are fully automated from machines. Capturing, storing, organizing, modeling and analyzing this big data has elevated the importance of cloud and edge computing, global-scale databases, advanced analytics software, and the growing importance of machine learning. This is a trend that was already taking place in business and now has a giant spotlight on it due to its global importance. There’s no stopping the data + advanced analytics juggernaut in 2021 and beyond.

Conclusion

2020 was one of the worst years in human history and the loss of life was just heartbreaking. People, businesses, and our education system had to become resourceful to survive. This resourcefulness amplified the importance of delivering connected, digital experiences to make previously remote things into local ones. Cheers to 2021 and the hope for a brighter day for all of humanity.

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By Michele Pelino

The COVID-19 pandemic drove businesses and employees to became more reliant on technology for both professional and personal purposes. In 2021, demand for new internet-of-things (IoT) applications, technologies, and solutions will be driven by connected healthcare, smart offices, remote asset monitoring, and location services, all powered by a growing diversity of networking technologies.

In 2021, we predict that:

  • Network connectivity chaos will reign. Technology leaders will be inundated by an array of wireless connectivity options. Forrester expects that implementation of 5G and Wi-Fi technologies will decline from 2020 levels as organizations sort through market chaos. For long-distance connectivity, low-earth-orbit satellites now provide a complementary option, with more than 400 Starlink satellites delivering satellite connectivity today. We expect interest in satellite and other lower-power networking technologies to increase by 20% in the coming year.
  • Connected device makers will double down on healthcare use cases. Many people stayed at home in 2020, leaving chronic conditions unmanaged, cancers undetected, and preventable conditions unnoticed. In 2021, proactive engagement using wearables and sensors to detect patients’ health at home will surge. Consumer interest in digital health devices will accelerate as individuals appreciate the convenience of at-home monitoring, insight into their health, and the reduced cost of connected health devices.
  • Smart office initiatives will drive employee-experience transformation. In 2021, some firms will ditch expensive corporate real estate driven by the COVID-19 crisis. However, we expect at least 80% of firms to develop comprehensive on-premises return-to-work office strategies that include IoT applications to enhance employee safety and improve resource efficiency such as smart lighting, energy and environmental monitoring, or sensor-enabled space utilization and activity monitoring in high traffic areas.*
  • The near ubiquity of connected machines will finally disrupt traditional business. Manufacturers, distributors, utilities, and pharma firms switched to remote operations in 2020 and began connecting previously disconnected assets. This connected-asset approach increased reliance on remote experts to address repairs without protracted downtime and expensive travel. In 2021, field service firms and industrial OEMs will rush to keep up with customer demand for more connected assets and machines.
  • Consumer and employee location data will be core to convenience. The COVID-19 pandemic elevated the importance location plays in delivering convenient customer and employee experiences. In 2021, brands must utilize location to generate convenience for consumers or employees with virtual queues, curbside pickup, and checking in for reservations. They will depend on technology partners to help use location data, as well as a third-party source of location trusted and controlled by consumers.

* Proactive firms, including Atea, have extended IoT investments to enhance employee experience and productivity by enabling employees to access a mobile app that uses data collected from light-fixture sensors to locate open desks and conference rooms. Employees can modify light and temperature settings according to personal preferences, and the system adjusts light color and intensity to better align with employees’ circadian rhythms to aid in concentration and energy levels. See the Forrester report “Rethink Your Smart Office Strategy.”

Originally posted HERE.

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By Patty Medberry

After 2020’s twists and turns, here’s hoping that 2021 ushers in a restored sense of “normal.” In thinking about what the upcoming year might bring for industrial IoT, three key trends emerge.

Trend #1: Securing operational technology (OT)

 IT will take a bolder posture to secure OT environments.

Cyber risks in industrial environments will continue to grow causing IT to take bolder steps to secure the OT network in 2021. The CISO and IT teams have accountability for cybersecurity across the enterprise. But often they do not have visibility into the OT network. Many OT networks use traditional measures like air gapping or an industrial demilitarized zone to protect against attacks. But these solutions are rife with backdoors. For example, third-party technicians and other vendors often have remote access to update systems, machines and devices. With increasing pressure from board members and government regulators to manage IoT/OT security risks, and to protect the business itself, the CISO and IT will need to do more.

Success requires OT’s help. IT cybersecurity practices that work in the enterprise are not always appropriate for industrial environments. What’s more, IT doesn’t have the expertise or insight into operational and process control technology. A simple patch could bring down production (and revenues).

Bottom line? Organizations will need solutions that strengthen cybersecurity while meeting IT and OT needs. For IT, that means visibility and control across their own environment to the OT network. For OT, it means security solutions that allow them respond to anomalies while keeping production humming.

Trend #2: Remote and autonomous operations

The need for operational resiliency will accelerate the deployment of remote and autonomous operations – driving a new class of networking.

The impact of changes brought on in 2020 is driving organizations to increasingly use IoT technologies for operational resiliency. After all, IoT helps keep a business up and running when people cannot be on the ground. It also helps improve safety and efficiencies by preventing unnecessary site visits and reducing employee movement throughout facilities.

In 2021, we will see more deployments aimed at sophisticated remote operations. These will go well beyond remote monitoring. They will include autonomous operational controls for select parts of a process and will be remotely enabled for other parts. Also, deployments will increasingly move toward full autonomy, eliminating the need for humans to be present locally or remotely. And more and more, AI will used for dynamic optimization and self-healing, in use cases such as:

  • autonomous guided vehicles for picking and packing, material handling, and autonomous container applications across manufacturing, warehouses and ports
  • increased automation of the distribution grid
  • autonomous haul trucks for mining applications
  • Computer-based train control for rail and mass transit

All these use cases require data instantly and in mass, demanding a network that can support that data plus deliver the speed required for analysis. This new class of industrial networking must provide the ability to handle more network bandwidth, offer zero latency data and support edge compute. It also needs security and scale to adapt quickly, ensuring the business is up and running – no matter what.

Trend #3: Managing multiple access technologies

Organizations will operate multiple-access technologies to achieve operational agility and flexibility.

While Ethernet has always been the foundation for connectivity in industrial IoT spaces, that connectivity is quickly expanding to wireless. Wireless helps reduce the pain of physical cabling and provides the flexibility and agility to upgrade, deploy and reconfigure the network with less operational downtime. Newer wireless technologies like Wi-Fi 6 and 5G also power use cases not possible in the past (or possible only with wired connectivity).

As organizations expand their IoT deployments, the need to manage multiple access technologies will grow. Successful deployments will require the right connectivity for the use case, otherwise, costs, complexity and security risks increase. With wireless choices including Wi-Fi, LoRaWAN, Wi-SUN, public or private cellular, Bluetooth and more, organizations will need to determine the best technology for each use case.  

Cisco’s recommendation: Build an access strategy to optimize costs and resources while ensuring security. Interactions between access technologies should deliver a secured and automated end-to-end IP infrastructure – and must avoid a “mishmash” leading to complexity and failed objectives.

As the end of 2020 fast approaches, I wish everyone a safe and healthy New Year. As you continue building and refining your plans for 2021, please consider how you can unleash these IoT network trends to reduce your cybersecurity risks and increase your operational resiliency. 

Originally posted HERE.

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Figure 1: Solution architecture with AWS IoT core

Critical and high-value assets are always on the move, and this holds across practically every industry vertical relying on supply chain and logistics operations. Naturally, enterprises seek ways to track their assets with the shipment carrier in ways that are most optimal to their requirements. The end goal is often to have greater visibility and control of assets while in transit with the shipment carrier while opening up opportunities to optimize business operations based on insights-driven decisions.

For assets in transit, proactive shipment monitoring results in greater reliability of the shipment's integrity by way of real-time updates about the shipment's location, transit status, and conditions like temperature and humidity (for perishable shipments). All this information helps quick issue identification and remediation by the respective stakeholders. This helps minimize losses and reduced insurance claims, which results in further cost optimization for the enterprise while delivering a delightful purchase experience to their customers.

A solution to address such requirements would need to be an IoT (Internet of Things) solution requiring a combination of tracker devices (hardware), cloud apps (software platform), enterprise systems integrations (with SCM, ERP & similar systems), and professional services & support for field installation & continuous data insights. For most enterprises, this implementation of the Internet of things is complex and non-core. Such an IoT solution requires the investment of capital, time, and expertise to build and deploy such a solution, especially one that's secure and scalable.

In this post, we'll discuss such an IoT solution that is built using AWS IoT Core and can be delivered in an affordable manner such that it's ready to use within a matter of days or weeks. The solution leverages GPS-enabled tracker hardware comprising condition monitoring sensors like temperature, humidity, shock impact, and ambient light. This device can be used to track entire containers or pallets having multiple cartons or even individual item boxes depending on the requirements. The shock impact sensor on the device indicates asset mishandling based on threshold limits, and the light sensor can indicate potentially unauthorized use/asset theft. Such a device requires a cellular connectivity service to communicate sensor data to the cloud per pre-configured rules.

By way of API integrations using AWS SDKs for the Internet of things, the tracker devices are first connected and authenticated. The data they generate is published to a cloud app powered by AWS IoT Core in real-time or at preset time intervals. The data sent to the cloud app is in JSON-format message payloads sent via the MQTT protocol supported by AWS IoT Core; and is presented on the Frontend Dashboard UI in a rich, interactive manner on a map interface with sensor-specific information available within a couple of taps/clicks.

These sensor data messages are further forwarded to other back-end systems like AWS IoT Analytics. The data is usually saved in a time-series data store for analysis and insights later in time. Additionally, API integrations can also be easily built for the cloud app to work with enterprise apps like Transport Management Systems and Warehouse Management Systems to realize autonomous supply chain operations. Business rules define such movement of data- and operations-specific logic and is handled via AWS's Rules Engine service, which also can be used to transform device data before forwarding it to a different application.

However, not every data point a sensor picks up needs to be sent to the cloud app unless such a mandate exists, often due to regulatory compliance requirements in verticals like healthcare and pharmaceuticals. The Dashboard UI on the cloud provides a simple interface to set ranges of minimum and maximum sensor readings acceptable. Any breach of this range is immediately notified as an alert to the team responsible for monitoring the shipment. The team can then contact the shipment carrier to take corrective action. Such ranges can also be separately configured within mere seconds for each shipment per its monitoring requirements.

The secure bidirectional messaging between the tracker device and the cloud app is enabled via AWS IoT Core's Device Gateway, which scales automatically to process millions of messages in either direction while ensuring low latency mission-critical applications.

This makes the purpose-built shipment monitoring solution completely configurable and hence scalable while still being quickly deployable without the hassles of capital expenses and significant resource time spent in custom building such solutions from scratch.

Summary

The intelligent shipment monitoring solution enables enterprises to have greater control over the movement of their assets while having enough data and insights over time to optimize business operations as required.

With AWS IoT Core and AWS IoT Analytics, such a data-driven outcome approach to handle supply chain operations delivers transformational benefits such as reduced losses, greater cost control, and improved customer satisfaction rates that can result in sustainable competitive advantage in the marketplace.

Originally posted HERE.

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In order to form proper networks to share data, the Internet of Things (IoT) needs reliable communications and connectivity. Because of popular demand, there’s a wide range of connectivity technologies that operators, as well as developers, can opt for.

IoT Connectivity Groups

The IoT connectivity technologies are currently divided into two groups. The first one is cellular-based, and the second one is unlicensed LPWAN. The first group is based around a licensed spectrum, something which offers an infrastructure that is consistent and better. This group supports larger data rates, but it comes with a cost of short battery life and expensive hardware. However, you don’t have to worry about this a lot as its hardware is becoming cheaper.

Cellular-Based IoT

Because of all this, cellular-based IoT is only offered by giant operators. The reason behind this is that acquiring licensed spectrum is expensive. But these big operators have access to this licensed spectrum, as well as expensive hardware. The cellular IoT connectivity also has its own two types. The first one being the narrowband IoT (NB-IoT) and category M1 IoT (Cat-M1).

Although both are based on cellular standards, there is one big difference between the two. That NB-IoT has a smaller bandwidth than Cat-M1, and thus offers a lower transmission power. In fact, its bandwidth is 10x smaller than that of Cat-M1. However, both still have a very long range with NB-IoT offering a range of up to 100 Km.

The cellular standard based IoT connectivity ensure more reliability. Their device operational lifetimes are longer as compared to unlicensed LPWAN. But when it comes to choosing, most operators prefer NB-IoT over Cat-M1. This is because Cat-M1 provides higher data rates that are not usually necessary. In addition to this, the higher costs of it prevent operators from choosing it.

Cat-M1 is mostly chosen by large-scale operators because it provides mobility support. This is something suitable for transportation and traffic control-based network. It can also be useful in emergency response situations as it offers voice data transfer.

The hardware (module) used for cellular IoT is relatively more expensive compared to LPWAN. It can cost around $10, compared to $2 LPWAN. However, this cost has been dropping rapidly recently because of its popular demand. 

Unlicensed LPWAN

As for the unlicensed LPWANs, they are used by those who don’t have the budget to afford cellular-based IoT. They are designed for customized IoT networks and offer lower data rates, but with increased battery life and long transmission range. They can also be deployed easily. At the moment, there are two types of unlicensed LPWANs, LoRa (Long Range) and SigFox.

Both types are amazing as they designed for devices that have a lower price, increased battery life, and long range. Their coverage range can be up to 10 Km, and their connectivity cost is as low as $2 per module. Not only this, but the cost is even lower than this sometimes. Therefore, they are ideal for local areas.

Weightless LPWAN

Although there are many variants of the LPWAN, Weightless is considered to be the most popular one. This is because the Weightless Special Interest Group, or the SIG, currently offers three different protocols. These include the Weightless-N, the Weightless-W, and the Weightless-P. All three work in a different way as they have different modalities.

Weightless-W

First off, we have the Weightless-W open standard model. This one is designed to operate in TV white space (TVWS). TV Whitespace (TVWS) is the inactive or unoccupied space found between channels actively used in UHF and VHF spectrum its frequency spans from 470 MHz – 790 MHz. For those who don’t know, this is similar to what Neul was developing before getting acquired by Huawei. Now, while using TVWS can be great as it uses ultra-high frequency spectrum, it has one downside. In theory, it seems perfect. But in practice, it is difficult because the rules and regulations for utilizing TVWS for IoT vary greatly.

In addition to this, the end nodes of this model don’t work like they are supposed to. They are designed to operate in a small part of the spectrum. As is difficult to design an antenna that can cover a such wide band of spectrum. This is why TVWS can be difficult when it comes to installing it. The Weightless-W is considered a good option in:

  • Smart Oil sector.
  • Gas sector.

Weightless-N

Second up we have the ultra-narrowband system, the Weightless-N. This model is similar to SigFox as both have a lot in common. The best thing about it is it is made up of different networks instead of being an end-to-end enclosed system. Weightless-N uses differential binary phase shift keying (DBPSK) digital modulation scheme same as of used in SigFox.

The Weightless-N line is operated by Nwave, a popular IoT hardware and software developer. However, while is model is best for sensor-based networks, temperature readings, tank level monitoring, and more, there are some problems with it. For instance, Nwave has a special requirement for TCXO, that is the temperature compensated crystal oscillator.

 In addition to this, it has an unbalanced link budget. The reason behind why this is bad is that there will be much more sensitivity going up to the base station compared to what will be coming down. 

Weightless-P

Finally, we have the Weightless-P. This model is the latest one in the group as it was launched some time after the above two. What people love the most about this one is that it has two-way features. In addition to this, it has a 12.5 kHz channel that is pretty amazing. The Weightless-P doesn’t require a TXCO, something which makes it different from Weightless-N and -W.

The main company behind Weightless-P is Ubiik. The only downside about this model is that it is not ideal for wide-area networks as it offers a range of around 2 Km. However, the Weightless-P is still ideal for:

  • Private Networks
  • Extra sophisticated use cases.
  • Areas where uplink data and downlink control are important.

Capacity

Because of the fact that the Weightless protocols are based on SDR, its base station for narrowband signals is much more complex. This is something that ends up creating thousands of small binary phase-shift keying channels. Although this will let you get more capacity, it will become a burden on your wallet.

In addition to this, since the Weightless-N end nodes require a TXCO, it will be more expensive. The TXCO is used when there is a threat of the frequency becoming unstable when the temperature gets disturbed at the end node.

Range

Talking about the ranges, the Weightless-N and -W has a range of around 5 Km in Urban environments. As for the Weightless-P, it can go up to 2 Km.

Comparison

Weightless and SigFox

If we take the technology into consideration, then the Weightless-N and SigFox are pretty similar. However, they are different when it comes to go-to-market. Since Weightless is a standard, it will require another company to create an IoT based on it. However, this is not the case with SigFox as it is a different type of solution.

Weightless and LoRa

In terms of technology, the Weightless and LoRa. Lorawan are different. However, the functionally of the Weightless-N and LoRaWAN is similar. This is because both are uplink-based systems. Weightless is also sometimes considered as the very good alternative when LoRa is not feasible to the user.

Weightless and Symphony Link

The Symphony Link and Weightless-P standards are more similar to each other. For instance, both focus on private networks. However, Symphony Link has a much more better range performance because it uses LoRa instead of Minimum-shift keying modulation MSK.

Originaly posted here

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