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Case Studies (220)

We are well aware that IoT offers a range of possibilities across various industries including consumer electronics and cars, healthcare, utilities, transportation, manufacturing, and so on. Also, Industrial IoT offers means to obtain insights into the business operations.

IoT offers a greater promise in the healthcare sector than in other sectors. This is because the IoTprinciples are already being applied to enhance the quality of care, reduce the cost of care, and improve the overall access to care.

The integration of IoT features into medical devices greatly enhances the effectiveness and quality of service, especially bringing greater value to those requiring constant supervision and elderly patients suffering from chronic illnesses. The IoT has the potential to not only keep the patients healthy and safe but also to improve how the doctors provide care as well.

A few estimates have revealed that by 2025 spending on Healthcare IoT solutions will reach around $1 trillion, and hopefully, will make the conditions favourable for highly accessible, on-time, and personalized health services for everyone.

The IoT can also enhance patient satisfaction and engagement by allowing patients to spend more time interacting with their doctors. This article will explore some of the major applications of healthcare IoT and the challenges it poses for healthcare today.

Applications of Healthcare IoT

Starting with managing chronic diseases to preventing a disease, there are a broad range of applications for IoT in the healthcare sector. Now, let’s dig deeper into each of the major applications.

Providing Constant Attention

The patients who are hospitalized and whose health status requires close attention can be monitored constantly using noninvasive, IoT driven monitoring. This kind of solution uses sensors to gather comprehensive physiological data and the cloud and gateways to examine and preserve the data and then send the examined information wirelessly to physicians for further analysis and review.

This eliminates the need for the doctor having to visit at regular intervals to check the vital signs of a patient, instead offering a continuous and automated flow of data. In this way, it enhances the quality of care via constant attention and lowers the cost involved by eliminating the need for a physician to engage actively in data gathering and analysis.

Building Trust

The connectivity of a healthcare system with the IoT places emphasis on the patient needs. This means timely intervention by doctors, enhanced accuracy in case of diagnosis, proactive treatments, and improved treatment outcomes result in a care that is highly accountable and gains trust among the patients.

Remote Patient Monitoring

All over the world, there are many people who face health issues due to lack of access to effective health monitoring. But, with the help of powerful, interrelated IoT solutions, monitoring the patients has become easier than ever.

These solutions can be utilized to capture the health data of a patient in a secure way from different sensors, make use of complex algorithms to examine the data and then share it via wireless connectivity with the physicians who can make proper health recommendations.

Reduced Costs

With the availability of real-time data from the connected healthcare solutions, the doctors can not only take better care of their patients but also lessen their number of visits to the patient as they can monitor their patients remotely. This decreases the overall health care costs as the costs involved in hospital stays and readmissions are cut down to a greater extent.

Configuring Emergency Alerts

Healthcare IoT allows care teams to gather and connect millions of data points regarding the personal fitness of a patient from wearables like activity, temperature, perspiration, sleep, and heart-rate. As a result, the information obtained from sensors can send out real-time alerts to caregivers and patients so they obtain event-triggered messaging such as triggers and alerts for elevated heart-rate and so on. This will hugely enhance workflow optimization and ensure all the care is handled from home.  

Challenges of IoT in Healthcare

The IoT continues to face challenges in spite of the promise of what it can achieve in healthcare. If these challenges are not addressed soon, they could put the IoT at risk of failure.

By intent and design, the IoT devices collect and transmit real-time data. The infrastructure required to receive and process this information should be designed and developed for scale. This means obtaining, processing, and storing data in real-time from millions of IoT devices and applying analytics to gain insights from this data. Unfortunately, most of the providers lack the know-how and infrastructure to access the data.

Also, most of the devices reporting healthcare data suffer from a lack of common security practices or standards. Due to this, many healthcare IT professionals have raised concerns about the risks associated with data breaches and IoT device tampering.

Other major challenges include lack of EHR system integration and lack of adoption of interoperability. Addressing these problems will further revolutionize the health industry as more organizations will start implementing IoT for their healthcare services.

Healthcare IoT is transforming the way the facilities are delivered to patients. In order to derive the true value of healthcare IoT, the interrelated healthcare devices and the processes that are supporting them must work as a joint system that is comprehensive, integrated, and secure. With healthcare IoT facing few challenges, the healthcare providers are hopeful that the IoT will have a positive impact on delivering valuable data and supporting patient care.

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Since its conception, IoT has been impacting numerous businesses in unprecedented ways than expected. IoT infrastructure market, one of contemporary niche verticals of the building construction and infrastructure development sphere, now holds the reputation of being encompassed among the many IoT influenced business spheres. The proliferation of the Internet of things in infrastructure development has led to the procreation of smart homes and cities, touted as a revolutionary phenomenon of the 21st century. With the rising demand for connectivity to enable smart security, social surveillance, smart transportation, energy safety, smart metering, and efficient governance for enhancing consumer lifestyle, IoT infrastructure industry is likely to garner much acclaim in the ensuing years. Estimates compiled in a recent IoT infrastructure market research report forecast this business space to have accumulated a valuation of close to USD 15 billion in 2016.

U.S. IoT infrastructure market, by application, 2016 & 2024 (USD Billion)

A succinct overview of IoT infrastructure market in terms of the application spectrum

IoT infrastructure industry outlook from smart homes

The proliferation of IoT in the home sector has brought about a barrage of changes in consumer standard of living. IoT-enabled homes offer some of the best advantages that can transform a person’s lifestyle across the urban space. Smart devices such as the Nest thermostat, Amazon Echo, smart fridges, Google Home, Wink Relay and Controller, etc., have been popularized across IoT infrastructure market and liberally deployed in smart homes, subject to their incredible benefits such as controlled energy consumption, automated notifications, weather alerts, etc. Fiercely vying with one another to consolidate their positions in IoT infrastructure industry, tech companies have been going the whole hog to introduce highly advanced connected devices for smart homes.

IoT infrastructure market outlook from smart buildings

The deployment of big data and IoT in smart buildings helps deliver actionable insights to improve consumer living comfort, optimize building operations, and reduce energy expenditure. The robust rise in the number of connected devices being installed in smart buildings bears evidence to the fact that IoT infrastructure industry share from smart buildings is likely to plummet in the years ahead. Companies have been planning strategies to brainstorm numerous connected devices for exploiting the potential of IoT in buildings. Recently for instance, Kone signed on a multi-year deal with IBM, with an aim to maneuver the IBM IoT Cloud Platform for connecting, monitoring, and optimizing building components such as doors, elevators, turnstiles, and escalators.

IoT infrastructure market outlook from smart cities

A recently compiled report depicts that close to 60% U.S. citizens prefer living in smart cities, given their incredible advantages. The rising proliferation of smart cities is evident from the incredible proportion of smart city projects that are being undertaken across myriad geographies – which may have a mammoth impact on the revenue graph of IoT infrastructure industry. The numerous advantages provided by smart cities with regards to planning, finance, energy safety, transportation, and other urban aspects have accelerated their demand and popularity across IoT infrastructure market. In consequence, tech behemoths have been signing public-private partnerships, that would lead to the generation of layered framework to address the many challenges of smart city projects by building effective, connected solutions.

The Internet of Things, conceived back in the 1980s at the Carnegie Mellon University, has now metamorphosed into a prodigy that defines efficiency, sustainability, and convenience. The deployment of this concept in infrastructure is likely to open up a plethora of opportunities for construction companies, real estate developers, technology behemoths, and infrastructure development firms, that would strive to brainstorm numerous solutions for connected infrastructure, augmenting IoT infrastructure industry trends. An IoT related report by a research firm claims close to 1.40 billion IoT units to be shipped ahead for smart city projects by 2020, for smart homes, smart buildings, smart transportation, sustainability and climate change. This provides ample evidence to the fact that IoT infrastructure market is here to stay, boasting of a widespread array of technologies, platforms, and applications. A report compiled by Global Market Insights, Inc., claims IoT infrastructure market size to surpass a valuation of more than USD 130 billion by 2024 – which is apparently close to 8.5 times its value in 2016.

Source:https://www.gminsights.com/industry-analysis/iot-infrastructure-market

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Adapting To Digital Transformation

From incorporating a faster and more efficient fleet-tracking technology to application delivery, digital transformation has become a permeating voice in talking about taking businesses to the next level by fast-tracking their time to market, reducing optimization costs, and creating a fluid business model.
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For more than a century, advances in technology, machinery and automation have oftentimes replaced humans as a means to accomplish tasks. In this podcast, Rob Tiffany tackles the unsavory topic of workforce reduction as certain tasks have evolved from manual to mobile to IoT.

Listen to the Podcast 

 

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Security systems installed in a typical facility consists of cameras, access control, intrusion sensors and fire alarms. Typically, these devices are places behind a firewall on a dedicated network. Building control systems are installed on a secondary network can contains lighting, HVAC, fire protection, elevators/lifts, chillers and air/moisture sensors. These systems serve their purpose and will continue to be adapted and make facility systems design more complicated. This complexity can be controlled using common development tools and platforms. Not only will this approach make the process of creating smarter, safer, more energy efficient systems but will also reduce the number accidental deaths and injuries that occur every year.

 

The redundant network design approach is not a very efficient nor cost effective way of operating a facility. This is starting to change as savvy building managers are making the decision to integrate security and building control systems and map them onto a single network. This can entail integrating multiple disparate systems, sensors, NVR devices and video management software. The concept of integrating a camera or access control system to an HVAC system, or a visitor/facility management system or edge recording device to a lighting or fire protection system may seem unusual to some. Yet, this is where many security systems integrators and manufactures are missing out on untapped applications and services opportunities. Modern integrated security and building systems can give facility managers and security directors the tools to improve, simplify operations and reduce the efforts of the operations staff and points of control teams.

 

In the past, the security industry has relied on it’s own approach to integrated systems know as physical security information management (PSIM). PSIM attempts to provide an open architecture to integrate multiple security system products into a single operating platform. This approach has been very hit-or-miss and has left a bad taste in the mouths of systems integrators and end-users. On the flip side of the coin, facility managers have their own integration platform known as a building automation system (BAS). As it relates to physical security, BAS systems are intended to integrate with PSIMs and control individual security systems. However, BAS systems come in many different flavors; many of them are not viewed in a glowing light by building operation end users. Past integrations are not all filled with doom-and-gloom. There are some successful integrations attempted by the collaborative efforts of building controls and physical security organizations. The question is why is this design practice not more common where the benefits and economics make sense?

 

In order to facilitate the adoption and implementation of an integrated system the use of open standard protocols is an absolute must. The building automation industry created BACnet and LONworks which allow for real-time remote connectivity between sensors, actuators, controller devices and software. In the case of LONworks, hardware manufactures have the ability to include a chipset with built-in building control system support. It took some time, but finally the security industry created the protocols ONVIF and PSIA. These open architectures allows the end-user to choose vendors selecting either security or BAS equipment based on features and price. The end-user can also decide to install partial system upgrades without the risk of making costly investments in obsolete legacy systems. With that said, The security industry is curious about implementing the building controls protocols but needs an easier way to integrate them into their hardware and software products in an ad-hoc applications based manner.

 

There are security directors that are not completely sold on the idea of integrating with building control systems. On the other hand, facility managers may question the benefits of sharing a network with security systems especially when functions do not overlap with life-safety systems. However, system integration between building controls, physical and now cybersecurity offers more than just staffing convenience and operational efficiency. Here are a few results from a truly integrated security system.

Faster Response to Incidents – With the use of a robust mobile software solution and integration approaches such camera-to-access control-to-lighting or HVAC staff members can be freed from a console which makes them readily available to respond to incidents or equipment failure.

Provide more accurate compliance reports – Data provided by building controls and security edge devices can be paired with artificial intelligence technologies such as neural networks and genetic algorithms. This helps facilities to comply with government regulations with regards to security.

Reduce accidents and save money – Integrated systems provide better control of building and security systems. For example, if some accidentally stumbles into a restricted area or manages to make it to overly heated or chilled area the access control system, Variable air volume (VAV), or other HVAC system components can send alerts and create historical trend reports. Also a single network architecture can make managing system components easier.

 

Integrated building control and security systems are gaining some traction. However, it is still not a mainstream approach among many manufactures and systems integrators. One proposed solution is to utilize a common platform that is utilizes the industry protocol standards as application and system component building blocks.

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If you are planning to innovate your business and disrupt your niche with the Internet of Things, it may not be as easy as it seems. There are quite a few things that you need to be prepared with, and you should know certain facts about the technology before starting out.

Before anything else, it is important for you to be patient, understand the nuances of the technology and know how best to incorporate it into your business.

It is true that your IoT product will differ from what your competitors are planning to offer and in the technologically driven environment, it is important to differentiate. But, there are underlying patterns that cannot differ, which is why you need to know the basics of IoT before getting started.

So, are you ready to know them?

#1 Start with Design Thinking

When you are surfacing a company with IoT at the core, it is important to think slightly different. All your life as a businessman, you have thought of tactical ways to get your business started, focusing on objectives and goals. However, when you are dealing with IoT, your focus will need to differ. The idea is to think from the user’s perspective and create a framework that will create more practical and usable approaches.

The design strategy should be your first priority. You need to know how and what will work when you are designing for the users. There are a few things you might want to know before planning the design.

What is it that your users need? When we automated home ACs over WiFi, the purpose was to allow remote access, and not keep an eye out for another remote. Once this point is cleared, you may want to think of path defining solutions for the basic idea. The remote needed to go obsolete, which is why the path defining idea was to convert your mobile into a remote. Finally, you will need to build the prototypes and craft a story around it. The idea is to define a product that talks for itself.

#2 Workaround security

When you are working on an IoT-based startup, you might want to think about a security-first solution. You will need to protect the data that can be availed from the connected device so as to offer better security. Remember, the security for IoT based solutions are complex and difficult as compared to a regular security need. If there are more connected devices in the network, the security threat grows and you will find it difficult to control and manage.

So, when you are planning an IoT solution, you will need to think of security before you plan anything else in the device management or define other aspects of the solution.

#3 Managing the costs

Like with any other venture, you will need to think IoT solution development cost. There are costs involved in every stage, and these costs evolve through your development phases.

For instance, let’s start with the development cost of the IoT solution. From planning to actual feature selection to development with connected devices, there are various phases that you need to manage and work around.

Similarly, introducing security into your IoT solution will cost you, which you need to think about before panning it out. Finally, you will need to plan for the operation and maintenance costs of the IoT business, which requires either bootstrapped funds or investment, if you want to survive in the long run. Remember, the IoT business will not get your immediate returns on the investment.

#4 Scaling is different

The scaling of your IoT business works in a different manner from the scaling of other businesses. If a business works at a particular size, it is not necessary it will work for other sizes too. So, before scaling, you will need to figure out will the scaling manage the increased needs and demands of your company. The prototype scaling would differ from the actual business scaling.

Conclusion

IoT businesses are different from the normal businesses, and you will need to understand the nuances before you start building the prototype and acquiring customers. It is more user-oriented and works with a focus on the end goal to be achieved. If you are planning an IoT business, you should ideally consult a professional before starting with the strategies.

 

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The dream of making money with IoT, AI and Blockchain

Have you ever think about how could you make money with the Internet of Things (IoT) or Artificial Intelligence (AI) and of course with Blockchain?  What would happen if you could use the three of them in a new business model?.  Apparently, Success, Success and Success.

In the next sections I provide information of some business models implemented with these three technologies.

IoT Business Models

As IoT moves past its infancy, certain trends and economic realities are becoming clear. Perhaps the most significant of those is the realisation that traditional hardware business models just don’t work in IoT. Take a look at “The top 5 most successful IoT business models” that have emerged as particularly effective applications for IoT.

If any of you is building an IoT product, this article ” IoT Business Models For Monetizing Your IoT Product”  show how to make money with IoT.

Zack Supalla, the founder and CEO of Particle, an Internet of Things (IoT) startup, suggest “6 ways to make money in IoT”.

Finally, in “How IoT is Spawning Better Business Models” we can read three ways companies like Rolls Royce, Peloton, MTailor or STYR Lab  was rethinking their business model and have created revolution in the marketplace. 

Blockchain Business Models 

It sounds repetitive, but yes "Blockchain technology may disrupt the existing business models”. The authors´ s findings concerning the implications of blockchain technology for business models are summarised in the following picture.

 

Do you think that blockchain will likely to cut into big-players’ revenues? Then, this article: “New Blockchain-Based Business Models Set to Disrupt Facebook and Others”, is for you.

If you are ambitious and you are planning to build a viable business on blockchain, then read “Building an International Business Model on Blockchain”.

I am also an advocate of the coming era of decentralization (at least in my most optimistic version) and Blockchain is a step more to create value when the End of All Corporate Business Models will arrive.

AI Business Models 

Companies from all industries, of all shapes and sizes are thus faced with an important set of questions: Which AI business models and applications can I use ? And what technologies and infrastructures are required?.

It seems that we all are convinced that artificial intelligence is now the most important general-purpose technology in the world that can drive changes at existing business models. Not surprised then, that  AI is Revolutionizing Business Models.  The “data trap” strategy, that in venture capitalist Matt Turck’s words consists of offering (often for free) products that can initialize a data network effect. In addition, the user experience and the design are becoming tangibly relevant for AI, and this creates friction in early stage companies with limited resources to be allocated between engineers, business, and design.

This article introduces  some good examples of AI business models :

New Business models with the intersection of IoT, AI and Blockchain

With IoT we are connecting the Digital to the Physical world. Connected objects offers a host of new opportunities for companies, especially in terms of creating new services. The amount of data generated by the billions of connected objects will be the perfect complementary feed to many AI applications. Finally, blockchain technology could be used to secure the ‘internet of things’ and create smart contracts in a decentralized infrastructure that boost the democratization of technology and creation of sustainable communities.

You must remember that new business models that include IoT, AI and blockchain need among other characteristics: Volume and Scalability. Volume of devices, Volume of data, Volume of customers, volume of developers and powerful ecosystems to escalate. 

Good luck in your search and implementation of your new business model.

Thanks for your Likes, Comments and Shares

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Guest post by Romain Wurtz, Chief Technology Officer, NarrativeWave

As companies engage in the implementation of analytics and data science applications, many challenges lie ahead. According to the Harvard Business Review, many data science applications fail due to poor goal definition, a lack of understanding of the key data, or a lack of focus on business value.

We believe the best route to data analytics and particularly analytics for the Industrial Internet of Things, must have several key elements:

Key Elements of Effective Analytics:

Builds upon your Subject Matter Experts’ existing knowledge. Allows engineers to use the platform and be part of the analytics process.

Enables automation of key processes.  Builds a solid foundation for more complex analytics (e.g. predictive).

This article takes a look at each of these elements in further detail and explores why they are important to driving value for your organization.

Having a platform built on your subject matter experts’ knowledge is the best starting point.

Your Subject Matter Experts (SMEs) and engineers have been building and maintaining your equipment for decades. Their expertise and knowledge is the best available expertise on how your equipment should be operated, maintained, and evaluated. Incorporating their knowledge to best evaluate data from the equipment and what that data means, is the ideal starting point for the application of analytics.

Analytics platforms using purely Machine Learning or Artificial Intelligence may lack insight on what the data means and the meaning of events within the data. Without human interaction or interpretation, more advanced analytics, such as predictions, have a difficult time achieving the desired outcome. Without a determined outcome, the process can take months to evaluate, and even then, the analytic effectiveness and accuracy can remain unknown and unproven.

We believe the best starting point for analytics is one that starts by using your own proven analytic methods as a foundation and then allows for a natural, building blocks approach.

Using a platform that allows engineers to be part of the process helps with the adoption of analytics.

Adopting new analytics and data driven business models is fundamentally about changing the way business has been done for many years. In an effort to make this transition, gaining adoption and trust of key players within your organization will significantly impact the success of a new program. Having a platform where SMEs can interact and engage, without having to be a data scientist or a developer, results in higher adoption and more impactful business outcomes for the organization.

Implementing a platform that automates current processes creates short-term and significant value.

In order to gain value from large data sets and sensor data, only a platform that starts to automate part of the process can create scalable value. Meaning, the platform must be able to interpret data, generate insights, and provide recommended outcomes for end users. Otherwise, it becomes just another way to visualize and explore data. This can add value on its own, but doesn’t reach the impact that automation provides. As noted earlier, building a system on your proven analytic methods, and then adding a layer of more advanced analytics, such as machine learning based predictions, is the best route to a highly accurate, automated platform.

Building a platform with a solid foundation of your experts’ knowledge is the best way to approach implementing an entire suite of analytics.

Building a platform configured by your own SMEs creates the optimal foundation for an entire range of analytics. Your experts can provide knowledge about significant areas such as:

The meaning of key data. How sensors are related to each other.

What constitutes an actionable event?  What constitutes a false alarm?

Exceptions to the rule.

Once this knowledge is part of an automated platform, adding a full range of analytics becomes more impactful. For example, knowledge of what constitutes a false alarm can lead to an insight describing what turned a false alarm into a valid alarm and what indicators are worth automatically tracking. By contrast, an approach that solely tries to use machine learning or AI techniques without these key understandings, can struggle with the “right” business outcome, accuracy, dealing with exceptions, and delivering significant value to the business.

Business Cases & Outcomes

These business case examples show how we at NarrativeWave impact customer’s operations, profitability, unplanned downtime, and workforce efficiency.

Improved Accuracy of Event & Alarm Analysis.

Challenge: The traditional workflow of diagnosing events or alarms on large industrial assets is a manual process for engineers. A manufacturer was looking for a solution that would increase accuracy and reduce the risk of costly human errors. 

Solution: NarrativeWave’s platform allowed the customer’s engineers to create detection models and equations through the SaaS platform. Currently, this manufacturer receives accurate and automated root-cause analysis of events in near real-time.

Impact: The software provided a 25% increase in accuracy of diagnosing events, which means a more consistent, predictable solution for this manufacturer’s engineers and clients.

Reduced Time Spent Diagnosing Alerts & Alarms

Challenge: Sensors on large industrial assets generate millions of data points per second. When an alert was triggered, engineers spent hours conducting redundant, manual research to diagnose the problem and produce an actionable report for clients. The diagnostic process can take up to 16 hours and technicians were struggling to keep up with the expanding service requirements. 

Solution: The NarrativeWave platform automated their manual processes, delivering an analysis, actionable insights, recommendations, and a report to their engineers in less than 3 minutes. This allowed their engineers to make near real-time decisions on what happened, why it happened, and what to do next.

Impact: The outcome resulted in a 95% time savings in diagnosing alerts and alarms, which reduced unplanned equipment downtime, improved workforce efficiency, and enhanced service contract profitability. This proved the opportunity for a multi-million dollar savings per year for this OEM, and better supported real-time service contracts.

Optimized Productivity of Skilled Engineering Labor

Challenge: More than 50% of all industry alarms are false positives, which still have to be diagnosed and solved. A customer was looking for a solution that would allow their engineers to optimize their workflow and spend less time servicing invalid alarms. 

Solution: The NarrativeWave platform automated the root cause analysis of events to produce actionable insights based on the manufacturer’s data. The outcome was an explanation of the event that occurred and guidance on what to do next, which was provided to the engineers within a few minutes.

Impact: The platform accurately and quickly invalidated false alarms, allowing engineers to focus more time on resolving valid alarms and serving their clients. For the first time, engineers were being leveraged in the best way to impact this manufacturer’s operations.

Increased Efficiency in Creating Detection Models

Challenge: A large enterprise client had a robust analysis setup with 3 detection models and 150 threshold variants. The client’s process for iterating detection models originally took 3–4 months and required engineers to rely on development from either a software engineer, data scientist, or an outside software vendor. 

Solution: NarrativeWave’s platform provided an intuitive pipeline, enabling their business users to quickly create, manage, and iterate their own detection models. The platform is user-directed, managed and utilized by the customer’s internal engineers, without the ongoing need of developers or data scientists.

Impact: The iteration timeframe has been dramatically reduced since using NarrativeWave. More importantly, this customer’s engineers can setup iterations on their own, allowing for immediate impact on the business operations and for their clients.

Enhanced Next Generation Knowledge Base

Challenge: Engineers have been detecting alarms individually for 30 or more years. While working with a major engine manufacturer, NarrativeWave found the detection process was not recorded, standardized, or made available to other engineers and management within the organization. 

Solution: The platform is setup to record the engineers’ knowledge and feedback, resulting in a platform that gets smarter over time. Engineers can customize the business analysis and recommendations to make them as accurate as possible, therefore creating an evolving knowledge base for SMEs. 

Impact: The outcome resulted in the manufacturer, for the first time, being able to capture their engineers’ knowledge. This increased collaboration between engineers, improved standardization, and allowed valuable knowledge to be visible across the organization.

Improved Fleet Health & Management

Challenge: Manufacturers and equipment operators currently lack visibility into assets across their entire fleet, making it difficult to identify poorly performing assets and best performing assets. 

Solution: With NarrativeWave, asset performance can be evaluated near real-time, enabling organizations to better manage critical assets and plan for future actions, all by the click of a mouse.

Impact: The platform-wide view provides significant time-savings of tracking and managing fleet health for equipment manufacturers and operators. Additionally, the platform reduces unplanned downtime and helps organizations prevent critical equipment failures.

Improved Predictive Analytics & Maintenance

Challenge: Manufacturers and equipment operators are interested in deploying predictive models for better asset maintenance and warranty support. Pure machine learning approaches lack a solid foundational basis and can be difficult to implement successfully.

Solution: With the NarrativeWave Knowledge Base, key information such as the meaning of events, the relationship of sensors, and what constitutes a valid alarm are already known. By applying machine learning techniques to a solid NarrativeWave foundation, predictive analytics is more effectively implemented. 

Impact: This approach provides a strategic method of utilizing predictive analytics and improves the outcome of implementing analytics. The result is a highly accurate, auditable platform rather than a pure “black box” approach.

 

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Internet of Things (IoT) has generated a ton of excitement and furious activity. However, I sense some discomfort and even dread in the IoT ecosystem about the future – typical when a field is not growing at a hockey-stick pace . . .

“History may not repeat itself but it rhymes”, Mark Twain may have said. What history does IoT rhyme with?

 I have often used this diagram to crisply define IoT.

Even 10 years ago, the first two blocks in the diagram were major challenges; in 2017, sensors, connectivity, cloud and Big Data are entirely manageable. But extracting insights and more importantly, applying the insights in, say an industrial environment, is still a challenge. While there are examples of business value generated by IoT, the larger value proposition beyond these islands of successes is still speculative. How do you make it real in the fastest possible manner?

In a slogan form, the value proposition of IoT is ”Do more at higher quality with better user experience”. Let us consider a generic application scenario in industrial IoT.

IoT Data Science prescribes actions (“prescriptive analytics”) which are implemented, outcomes of which are monitored and improved over time. Today, humans are involved in this chain, either as observers or as actors (picking a tool from the shelf and attaching it to the machine).

BTW, when I mentioned “Better UX” in the slogan, I was referring to this human interaction elements improved by “Artificial Intelligence” via natural language or visual processing.

Today and for the foreseeable future, IoT Data Science is achieved through Machine Learning which I think of as “competence without comprehension” (Dennett, 2017). We cannot even agree on what human intelligence or comprehension is and I want to distance myself from such speculative (but entertaining) parlor games!

Given such a description of the state of IoT art in 2017, it appears to me that what is preventing us from hockey-stick growth is the state of IoT Data Science. The output of IoT Data Science has to serve two purposes: (1) insights for the humans in the loop and (2) lead us to closed-loop automation, BOTH with the business objective of “Do More at Higher Quality” (or increased throughput and continuous improvement).

Machine Learning has to evolve and evolve quickly to meet these two purposes. One, IoT Data Science has to be more “democratized” so that it is easy to deploy for the humans in the loop – this work is underway by many startups and some larger incumbents. Two, Machine Learning has to become *continuous* learning for continuous improvement which is also at hand (NEXT Machine Learning Paradigm: “DYNAMICAL" ML).

With IoT defined as above, when it comes to “rhyming with history”, I make the point (in Neural Plasticity & Machine Learning blog) that the current Machine Learning revolution is NOT like the Industrial Revolution (of steam engine and electrical machines) which caused productivity to soar between 1920 and 1970; it is more like the Printing Press revolution of the 1400s!

Printing press and movable type played a key role in the development of Renaissance, Reformation and the Age of Enlightenment. Printing press created a disruptive change in “information spread” via augmentation of “memory”. Oral tradition depended on how much one can hold in one’s memory; on the printed page, memories last forever (well, almost) and travel anywhere.

Similarly, IoT Data Science is in the early stages of creating disruptive change in “competence spread” via Machine Learning (which is *competence without comprehension*) based on Big Data analysis. Humans can process only a very limited portion of Big Data in their heads; Data Science can make sense of Big Data and provide competence for skilled actions.

 

To make the correspondence explicit, "information spread" in the present case is "competence spread"; "memory" analog is "learning" and "printed page" is "machine learning".

 

Just like Information Spread was enhanced by “augmented memory” (via printed page), Competence Spread will be enhanced by Machine Learning. Information Spread and the Printing Press “revolution” resulted in Michelangelo paintings, fractured religions and a new Scientific method. What will Competence Spread and IoT Data Science “revolution” lead to?!

From an abstract point of view, Memory involves more organization in the brain and hence a reduction in entropy. Printed page can hold a lot more “memories” and hence the Printing Press revolution gave us an external way to reduce entropy of “the human system”. Competence is also an exercise in entropy reduction; data get analyzed and organized; insights are drawn. IoT Data Science is very adept at handling tons of Big Data and extracting insights to increase competence; thus, IoT Data Science gives us an external way to reduce entropy.

What does such reduction in entropy mean in practical terms? Recognizing that entropy reduction happens for Human+IoT as a *system*, the immediate opportunity will be in empowering the human element with competence augmentation. What I see emerging quickly is, instead of a “personal” assistant, a Work Assistant which is an individualized “machine learner” enhancing our *work* competence which no doubt, will lead each of us to “do more at higher quality”. Beyond that, there is no telling what amazing things “competence-empowered human comprehension” will create . . .

I am no Industrial IoT futurist; in the Year 1440, Gutenberg could not have foreseen Michelangelo paintings, fractured religions or a new Scientific method! Similarly, standing here in 2017, it is not apparent what new disruptions IoT revolution will spawn that drop entropy precipitously. I for one am excited about the possibilities and surprises in store in the next few decades.

PG Madhavan, Ph.D. - “LEADER . . . of a life in pursuit of excellence . . . in IoT Data Science” 

http://www.linkedin.com/in/pgmad

This post original appeared here.

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IoT Fight

Here's the latest IoT Central Digest. Encourage your friends and colleagues to be a part of our community by forwarding this newsletter to them. They can join IoT Central here. You can contribute your thoughts on IoT here.  

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Surprise! Operations and IT aren't getting along when it comes to IoT.

451 Research announced new survey results that show operational technology (OT) and IT stakeholders are not aligned on IoT projects. Sure will be harder to drive business results if this doesn't get fixed. Here are some key findings:

Research shows that IT and OT personnel are not well aligned on IoT initiatives, and they need to cross that divide for those enterprise IoT projects to prove viable.

  • Only one-third of OT respondents (34%) said they ‘cooperate closely with IT’ on IoT projects from conception to operations.
  • A relatively small group of respondents said they were in ‘active conflict’ with IT over IoT, OT professionals are four times more likely to characterize their relationship with IT that way.  
  • More than half (55%) of the OT survey respondents currently deploy IoT within their organization, and 44% have successfully moved those projects from proof of concept to full-scale deployment.
  • New operational efficiencies and data-analytics capabilities are driving successful projects; however, many IoT projects face roadblocks in the trial stage due to the IT and OT divide and budget, staff, and ROI concerns. 

Additional details in the graphic below. Want the full findings? 451 Research will happily sell it to you.

 

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Advancements in IoT technologies have enabled machine-to-machine (M2M) communication and collection of relevant data. Predictive maintenance solutions leverage such data and IoT technologies, to help companies reduce costs of maintenance by adopting a proactive approach. This approach is proving to be a value-add solution. This is because, IoT enabled Predictive Maintenance solutions help shop-floors, assembly lines and other industrial or enterprise set-ups to avoid sudden machine failures and related operational delays.
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After years of evangelization waiting for the promises of the Internet of Things (IoT) to come true it seems that we are finally close to reaching the trough of disillusionment phase, we begin to forget all the hype generated so far and focus on reality. A harsh reality that involves selling IoT and not continue selling smoke anymore

THE TIME TO SELL IoT IS NOW

The sale of IoT is perhaps more complex than the sale of other disruptive technologies such as Big Data, Cloud or AI and maybe as complex as Blockchain today.  In the article “ Welcome to the first “Selling IoT” Master Class!” I commented how it should be  the evolution of M2M Vendors for sell IoT and how should be the evolution of IT Technology Vendors for sell IoT. However, many of these companies still have difficulty in forming and finding good sellers of IoT

The truth is that nowadays it does not make any sense to sell IoT as a technology. Enterprise buyers only want to buy solutions that provide measurable business outcomes while, in the other side, many IoT Vendors only want to sell their portfolio of products and services that have been categorized under the umbrella of IoT, either as quickly as possible or at the lowest possible cost.

During last 5 years, I have been analysing how IoT companies sell their products and services. Some of my customers (Start-ups, Device vendors, Telco Operators, Platform vendors, Distributors, Industry Applications, System Integrators) requested me to create IoT sales material to train their sales team about how to sell their IoT solutions and services. And sometimes I also helped Head Hunters or customers searching for IoT sales experts

Based on this varied experience I have launched this year a new service: “IoT Sales Workshops” to help companies train their internal teams in how to sell IoT. Here are some of the lessons I learned

  • There is a time for act as an IoT Sales generalist and a time for act as an IoT Specialist.
  • You need to adapt the IoT storytelling based on your audience.
  • Being an IoT expert is not synonymous with being successful in selling IoT.
  • You need to show how companies can get more out of IoT by solving a specific business problem.
  • Make it easy for the customer to see the benefits of your IoT product or IoT service and what is the value you are adding.
  • Given the complexity and specialization of IoT by vertical, explain companies the need to focus more closely at business cases, on their IoT business model as well as the ROI over three to four years before jumping into technology.
  • You need to be patient because IoT selling is not easy and takes time align strategy and business needs with the IoT products and services you are selling.
  • Build a strong ecosystem and make easy the customer the adoption of end to end IoT solution collaborating with your partners.
  • Train your IoT Business and Technical experts to get better at telling stories. Design a new marketing and sales communications playbook. Keep it simple. Build your narrative from the foundation up – one idea at a time.
  • If you want an IoT sales expert you need to pay for it (not expect miracles from external sales agents working on commission base).
  • IoT Sales is a full-time job. You will not have time to other enterprise activities.
  • Selling IoT to large enterprises is a teamwork process.
  • Be Persistent. Do not expect big deals soon.
  • Be Passionate, Be Ambitious, Be Disruptive to sell IoT.

Summary

I do not consider myself an IoT sales expert. And of course, neither a superman of sales. In fact, I have shied away from classifying myself in the role of a pure salesperson even though over time I have given a weight and value to this work that once seemed derogatory to me.

Sell IoT is not easy. In a few years we will have forgotten of the word IoT and we will be selling new hypes, but in the mean time you need to be prepared for disillusionment moments, long sales cycles and a lot of work with sometimes poor results. However, I do not know if will be 2020, suddenly if you persevere you probably will be awarded as the best IoT sales expert and you finally will earn a lot of money.

Be Persistent, Be Passionate, Be Ambitious, Be Disruptive to sell IoT

 

Thanks for your Likes and Shares

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IoT Tech Expo was unique in that provided opportunities to connect with leaders at the intersection of internet-of-things(IoT), artificial intelligence(AI) and blockchain.  Speakers showcased discussed their projects and many vendors shared their expertise.  Presentations and panelists discussed real-world implementations from John Deere, Porsche, Pfizer, Harley Davidson just to name a few.  The conference itself covered a lot of ground: there were entire speaker tracks for IoT Developers, Connected Industry, Connected Transportation, AI Analytics for IoT, AI in the Enterprise, Blockchain for the Enterprise, Blockchain for Enterprise, Cryptofinance & ICO Strategies, Blockchain for Business, and Blockchain development. This article shares some the key take-aways and interesting anecdotes from IoT implementations we collected from the show.
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Counterfeit Menace

Here's the latest IoT Central Digest. Encourage your friends and colleagues to be a part of our community by forwarding this newsletter to them. They can join IoT Central here. You can contribute your thoughts on IoT here.  

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IoT Survival Guide

Here's the latest IoT Central Digest. Encourage your friends and colleagues to be a part of our community by forwarding this newsletter to them. They can join IoT Central here. You can contribute your thoughts on IoT here.  

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The rise of IoT is good because it has enabled humans to gather, process and understand vast sums of data. This understanding helps us observe the nature of Human existence in real time, both collectively and individually.

Supply chain management is an integral business process. It affects people in every industry from farmers in Food Supply Chain to manufacturers in Industrial Supply Chain. We are going to observe the up and coming technologies and how they are revolutionizing this fundamental business process.

How is IoT being used in today’s World?

The Understanding of Mass Human behavior at an individual level has enabled services and technologies to exist that cater to personalized needs.It is introducing a new genre of innovation in Mobile App Development.

Companies use this data to develop applications that can efficiently increase revenue by cutting liability costs because of Big Data Analytics and IoT prompting all investments.

Take for example the efficiency with which you can use GPS trackers and environment sensors to keep track of your inventory and the storing conditions of your goods. Asset Tracking has created transparency in the supply chain, providing manufacturers with scope for business customization.

The kind of granular data that can and is being generated using RFID tags and global SIMs can create efficient staffing practices. Also, addressing the availability of complementary resources at the right place and right time.

There is Beacon technology, which is Low Energy Bluetooth devices (BLE), capable of transmitting information over short distances. Bluetooth SIG (Bluetooth Special Interest Group) is pushing this wireless personal area network as a factory floor network.

BLE is being used to create an Internet of Things solution, for instance, take IoT Development companies that created apps that help in Airport Baggage Management all by using these BLE devices or Beacons.

Another great example can be that of Amazon Go. It uses computer vision, machine learning and AI to create a shopping experience where you can just walk in, pick up what you want and walk out.

You check into the store with your mobile Phone and through a technology they have developed called “Just Walk Out” you can shop and just leave. It is one of the best examples of an Internet of Things Company, using a variety of sensors and computer vision tracking working together over a secured shared network.  

How is IoT affecting the Supply Chain Processes (SCP)?

Gartner the leading research and advisory organization, recently released a study, showing a thirty-fold increase in Internet-connected physical devices by 2020. 

International Data Corporation (IDC) reports: Largest IoT segments in 2017: manufacturing operations: $105B

Just imagine the kind of data that will be generated when we could observe the real-time shopping habits of individuals, their waiting time in each aisle, their preference. And the rate at which products and services are sought will see an unprecedented rise.

We will be able to automate a system that will conduct targeted marketing and efficient manufacturing. Research shows three-quarters of all retail and manufacturing ventures beginning to transform their supply chain processes.

IoT is enabling a more bidirectional flow of communication. Now engineers can run efficient diagnostics using the most recent captured data enabling them to conduct remote repair, increasing machine uptime and better customer service.

Unlike previously available passive sensors, this generation of sensors can keep track of the state of products in shipment, such as external surrounding and execute actions. Also, it can monitor utilization of Machine and update cloud platforms that can, in turn, optimize performance and workflow.

IoT is playing an integral role in increasing the scope of digitizing the Supply Chain in the Agro-Industry. Modern farmers are now incorporating Cloud Platforms to keep track of their farm produce and fine-tuning storage conditions.

A much more inter communicative channel is being formed between the different talking heads of the Supply Chain. And the funny thing is IoT devices are guiding how the products reach the market and talking has nothing to do with it.

Industries are trying to create the process more transparent for the consumers, certifying quality checks and an invasive feedback process.

Fleet Management for industries that comprise of companies like FedEx and DHL. Driver headcount, maintenance, and fuel consumption can all be brought down using IoT cloud Platforms. These platforms take in enormous amounts of data about diverse variables like traffic models, weather reports etc. and chart out efficient routes and delivery itineraries.

Having a connecting channel among all the components of the supply chain enables vendors to form better relations amongst themselves and with the customers. This is done by linking the shipping companies to the on-ground delivery services to the shopkeeper, all in real time.

We generate a truly end to end offering by providing vendors with domain expertise in IP connectivity, cloud service, security, hardware, and positioning.

With the help of IoT, we can accurately forecast inventories; keep track of the expiry dates of products and restocking schedules. It can also be used for cutting on Downtime with smart sensors, which are assessing maintenance requirements around the clock, propagating positive revenue generation.

Fitting the factory floors and machinery with sensors helps the system to tail workflow efficiency and logistics short-comings and respective requirements.

The Industrial Internet of Things revolution is pushing entire businesses towards an approach of local connectivity. Many businesses are adopting tools like AT&T’s Low-Power Wide-Area Technology, which has smaller modules with extended battery life and capable connectivity even in underground environments.

This has also created a demand for developers who excel in creating IoT Applications. And lately, it seems IoT technology and software framework has become essential to the 21st-century consumer market at par with Big Data Analytics and Management.

IoT compatibility is the need of the hour for businesses that want to stay ahead of the curve.One should investigate functional ways to integrate IoT technology and Applications into their Business Back-End and generate new streams of revenue.

Also, existing Businesses need to acknowledge the potential of IoT to redesign existing SCP. Building strong bridges to support the convergence of physical and digital supply chain.

In today’s market, SCP isn’t just for tracking your product. It’s an opportunity to gain an edge over your competitors and even establish your own brand.

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Counterfeiting is a major concern for brands. Companies lose billions of dollars in revenue and consumers also suffer the consequences in situations where they are unable to verify themselves or their ownership over products.

“The Organisation for Economic Co-operation and Development (OECD) estimates the annual value of international trade in all counterfeit goods at $200 billion.”

Imports of counterfeit and pirated goods are worth nearly half a trillion dollars a year or around 2.5% of global imports, with US, Italian and French brands hit the hardest and many of the proceeds going to organised crime, according to a new report by the OECD and the EU’s Intellectual Property Office.

So How Did HP Use The Concept of the Internet of Things to Combat Counterfeiting?

HP’s Tamper Evident Label and Security Label initiatives are a step towards enhancing its brand protection that customers can rely on.

Let’s take a look at how HP introduced a four-step method to easily authenticate products such as ink and toners.

  • To authenticate whether a product is a genuine HP product, customers can use their smartphones and scan the QR code placed on the HP Security Label on the packaging.
  • The QR code redirects to an online verification site checking the authentication number on the label against its online database which maintains records of the product down to the serial level.
  • If the IDs match the user is informed they have purchased a genuine HP registered product or offered a way to report a counterfeit in case the authentication fails.

 By providing its customers with easy to use, online and mobile validation processes, HP can ensure the sale of authentic products. HP is continuously working towards providing secure business solutions to its customers. HP anti-counterfeit is a great example of how brands are employing technical innovations based on the concept of ‘Internet of Products’.

“Counterfeit HP cartridges are predominantly refilled or remanufactured print cartridges packed in unauthorized or fake reproductions of HP packaging, that can’t compare to genuine HP cartridges. At HP, we are constantly striving to protect you from counterfeiters with new security measures.”

Being able to maintain a digital record of a product on an individual serial level enables HP customers to scan the physical counterpart of the product, pick the authentication code off the label and use the internet to run a check against the digital record.

This creates an authentication method which is tougher for counterfeiters to replicate.  Easing the product verification process and enabling customers to authenticate products via mobile devices, HP has successfully managed to deter fake products in the market and further strengthen its brand security/image.  

These technology-led initiatives which are capable of connecting the digital counterparts of physical products with their real-time values and status are redefining retail and product surveillance. HP has successfully built an anti-counterfeiting process based the concept of “internet of things” and as a result, other brands are also eagerly moving towards implementing internet of products led initiatives.

Such Internet of products enabled solutions are helping brands explore the possibilities that lie beyond the status-quo of usual product management.

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