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To paraphrase Geoffrey Moore, smart “thing makers” are investing in IoT solutions for their customers today in order to generate more revenue for themselves tomorrow. Traditional hardware vendors are being commoditized and replaced whenever a cheaper “good enough” option comes along. To thrive in the long run, your value must be “sticky”, embedded in your customer’s business, providing benefit to their customers as well. The “things” you sell now simply enable your customers to run their basic operations. Whenever a part breaks, customers make a decision to order a new one either from you or a competitor. How differentiated is your equipment from the rest of the market? Your business is constantly at risk.

What we’re seeing as a result are “thing makers” creating smart systems that empower their customers to not just operate, but to *optimize* their operations. These devices still perform their physical functions as before, but also collect and share a stream of data about their status and conditions in the world around them. It’s the data they produce, and the insights your system derives from this data, that enable your organization to offer far more valuable products and services to your customers that are not so easily replaced.

If you know the state of your machines at all times, you can build predictive maintenance and service models enabling guaranteed uptime and automatic replenishment. If your equipment never breaks or runs empty, your customer is unlikely to replace it with a competitor’s version.

If your products provide not just lighting and temperature control but also insights correlating usage patterns with time, weather, and utility data that reduce your customer’s costs, you can sell them this information for a percentage of these savings.

It’s the future. Your connected product system is part of your customer’s operating procedures, continuously generating insights for maximizing productivity. Improved asset utilization, faster turnarounds, synchronized workflows, and more. Smoother operations and reliable performance deliver better experiences for their customers, further expanding your customer’s business, because of your IoT solution. You don’t just sell “things.” You sell outcomes, which is what your customers really wanted in the first place.

That’s pretty smart.

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The manufacturing industry is undergoing many changes. Those specializing in traditional manufacturing are finding it difficult to keep up with the changes. Perhaps the biggest change has been how traditional manufacturing has come under pressure to manage vast amounts of data captured from different sources. Here are some of the reasons the Internet of Things (IoT) can help.

1. KEEPING AN EYE ON SUPPLIERS

Quality control has become easier because IoT helps keep an eye on suppliers. This makes for easier manufacturing processes. Keeping an eye on suppliers is all about looking at all the constituents that the supplier offers. Capturing data about these constituents through IoT helps make for faster data processing and better quality control.

2. MORE PRODUCTIVITY

Thanks to IoT, many manufacturers are now building self-correcting systems. Missing parts are replaced and parts are replenished, giving rise to greater productivity. Since manufacturing industries are looking in particular for ways to boost productivity, there is no way for them to overlook what IoT can do for them. In addition to greater productivity, there is also more convenience since the need for human labor reduces.

3. MAINTAINING SUPPLY LINES

The Internet of Things is expected to help manufacturers stick to lean manufacturing while at the same time helping maintain supply lines. Since lean manufacturing often requires smart management of the supply lines – to ensure that components are never in short supply but there is no overstock – IoT is expected to help resolve many problems. It will help ensure that suppliers located in different regions can be kept in the loop and supply lines can be managed smoothly so that there is no shortage. It will also help reduce waste and optimize the use of resources.

4. UNINTERRUPTED MANUFACTURING PROCESS

Usually, manufacturing is divided into many processes, from sourcing of raw materials to production, transportation and reaching the customer. However, with the Internet of Things, experts envision something extra. The entire process will be smooth and effective. The raw materials will be already marked for production, intended to reach a particular buyer. This is how experts see things play out as IoT advances to new levels.

5. REDUCED COST

As IoT gains more efficiency, manufacturers can expect to see lowered costs. This is one of the primary reasons manufacturing experts are enthusiastic about the role of IoT. It will become easier to track information about products and processes and more automation would help bring about greater efficiency, thus eventually reducing costs. Lowered costs are expected to boost profit margins. If your manufacturing plant has not invested in IoT yet, this might be the right time to start.

6. LAUNCH NEW PRODUCTS

With IoT, studying needs and launching new products becomes easier. There is less jostle and inefficiency than traditional systems. Manufacturing is thus one of the key areas where you can expect a lot of improvement, thanks to the Internet of Things.

7. INTEGRATING OFFLINE AND ONLINE PROCESSES

Traditionally data and manufacturing have been treated as separate entities. However, in manufacturing industries where IoT advances, this is expected to change. As products begin to carry information about them, it becomes easier to assign a processing and logistics path to them. This is why it becomes critical to involve IoT in your manufacturing plant.

8. CONNECTED TO THE CONSUMER

Products are, in the end, manufactured to suit the consumer. Thanks to IoT, it becomes easier to stay connected to the consumer and create products that match their requirements. This offers two-way benefits, as the consumer gets the best products and the manufacturing plant is able to manufacture products per exact specification. There are a lot of benefits that manufacturers can expect in the long term, thanks to the Internet of Things.As manufacturing processes undergo change, it becomes imperative for manufacturers to make the most of the coming revolution. Supply chains and logistics will become smoother thanks to the industrial Internet of Things. According to many experts, we are at the cusp of another major revolution that will change not only how things are manufactured but also the market economy. It is a good idea to be prepared for these changes by investing in the right IoT system.

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Digital disruption is omnipresent, get on board or get thrown off the track.

Digital is no longer a purview of only BankingInsuranceHealthcare or Retail. The Restaurant industry is having pressure from multiple directions. 

Today’s consumer expects fresh food, whether it is in season or not, with an exotic dining experience.

Successful restaurants recognize that the easy path to their customers' stomachs begins in their minds. They need to grab customer's attention and entice them with a memorable experience in order to trigger repeat visits.

Here are some of the applications of Digital disruption in the restaurants & food service industry:



  • Digital Signage to deliver eye-catching graphics to engage customers the moment they walk through the door
  • Online reservations using mobile app & flexibility of customization of menu as per customer taste
  • Chatbots: Restaurants are using virtual assistants to respond to customer inquiries and to process and customize customer orders. Taco Bell, Pizza hut have adopted chatbots to automate ordering process from a social media platform.
  • Robots – Restaurants are using AI-driven robots to increase capacity and speed of food preparation and delivery.
  • Recommendation engines – Developers are designing applications which use AI to help consumers choose meals & suggest foods based on their eating preferences.
  • Wi-Fi enabled dining spaces for truly engaging customer experience
  • Kiosks – Restaurants are integrating AI-driven self-service Kiosks to reduce customer waiting time and enhance the customer ordering experience.
  • Pay by phone and flexible paying options
  • Loyalty programs based on frequent visit
  • Digital supply chains to accurate demand forecasting, inventory optimization, and cost reduction.

Restaurants generate vast quantities of data through software that controls everything from scheduling food delivery and shift staffing to taking reservations to managing vendors and inventory to paying bills.

Today almost every consumer is making dining decision on their smartphone. They have tried new menu item based on the mobile ad.  Mobile payments have become the norm now in this industry. Customers would like to order quick meals via mobile and want to use mobile payments.

McDonald’s was the first store to accept Apple Pay.

Starbucks is a leader in digital transformation. Using more than 50mm Facebook fans & over 15mm Instagram followers at their disposal they mastered the social media engagement. First, they created an app to pay for coffee and food in their restaurants. Then they added the loyalty program, starting to craft hyper-personalized offers and experiences for their 24-hour connected customers. The company also developed new digital services to be enjoyed in their physical stores, achieving a highly praised omnichannel approach.

Pizza Hut has started an order and payment-enabled pepper robot. Customers can now have a personalized ordering, reduce wait time for carryout, and have a fun with the frictionless user experience.

TGI Fridays, Wendy’s and other big names have all adopted digital technology to lure their customers.

OpenTable, GrubHub, and Zomato are some of the latest apps showcasing nearby restaurants with high-quality pics, presenting a menu with exotic pictures, price, ratings etc. you can also get offers, deals instantly.

The digital technology available to restaurants has streamlined the lives of restaurant owners much like smartphones have bettered our daily lives.

Digital has entered the restaurants and food industry through the front door and brings many exciting trends.

As consumers expect Apple to come up with a new iPhone every year that makes the earlier model obsolete, similarly they want fresh ways of serving food with fantastic dining experience which is made possible by Digital disruption.

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IoT Business Models, Edge and Transportation

Here is the latest edition of the IoT Central Digest. Encourage your friends and colleagues to be a part of our community. Forward this to them. They can join IoT Central here. You can contribute your thoughts on IoT here.  

5 IoT-based Business Models to Leverage

Posted by Mehul Nayak 

The deployment of the Internet of Things (IoT) has disrupted niche organizations across multiple industries like financial services, technology, agricultural equipment etc. The organizations are shifting from traditional products to smart offerings and outcome-based deliverables. This article eplores 5-IoT based business models. 

Why Edge Computing Is an IIoT Requirement

Posted by Steven Martin

To jump-start the productivity engine of IIoT, real-time response is needed at the machine-level at scale and that requires an edge-plus-cloud architecture designed specifically for the Industrial Internet. From Google maps to weather apps, we’ve been experiencing the benefits of cloud and edge computing working together in our daily lives for quite some time. But, what is edge?

Internet of Things (IoT) and Urban Transportation

Posted by Rajashree Rao

According to United Nations, the World population is projected to reach 9.7 billion by 2050, while the share of urban population in the total population will grow from 50% to 70% and this development will increase the demand for global and individual mobility. Many countries in the world are witnessing a unique period of rapid growth in the demographics, economic, and urbanization. Today, more than 60% of the world's population lives in the urban areas, which is continuing to grow significantly. This article is a look at IoT’s role in transportation.

Connected Cars: From the Edge to the Cloud

Posted by David Oro 

Many of us have yet to see an autonomous vehicle driving down the road, but it will be here faster than we can image. The car of tomorrow is connected, data-rich and autonomous. As 5G networks come online, sensors improve and compute and memory become faster and cheaper, the amount of data a vehicle will generate is expected to be 40 terabytes of data every day. This will make the autonomous vehicle the ultimate edge computing device.

Discover The Best Selection Criteria To Choose Your IoT Platform

Posted by Ashish Trikha

Your IoT platform is the heart of your entire IoT solution. Building a reliable and scalable IoT platform is not a piece of cake, which is why these days the market is booming with hundreds of thousands of IoT PaaS (Platform as a Service) vendors. Choosing the right IoT platform for your solution has become more complex than it was ever before. That’s why, in this blog post we have covered some of the best selection criteria to pick the right IoT cloud platform for your needs.

 


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5 IoT-based Business Models to Leverage

The deployment of the Internet of Things (IoT) has disrupted niche organizations across multiple industries like financial services, technology, agricultural equipment etc. The organizations are shifting from traditional products to smart offerings and outcome-based deliverables.

Evolution of technology

We have progressed from reading a physical copy (paperback and hardcover) of the book to reading it on your device or on Kindle. We furthermore explored the traditional way of reading a book with the audio version of the book. We now can not only download the book and read it anywhere on our smartphones but can also just plug in the earphones and listen to it. This is defined by the progressive model by Amazon:

Amazon →Kindle →Echo →Audible

We need to evolve in a similar manner in the industrial world by thinking of the offer from the consumer’s perspective. Efficiently creating and monetizing value shared by IoT solutions will lead us to profitable outcomes.

Impact of IoT on businesses

Machina Research expands the scope of its IoT forecasts and highlights a USD 4 trillion revenue opportunity in 2025.

Business models require thinking through the consumption side of the offer (demand side). This explores the demand of the product and its usage. Your customers don’t merely purchase your product. They furthermore look for more opportunities – what they want is what your product can do for them. And hence, it is important to understand the consumer aspects of your offerings. Moreover, the business models also require thinking on the production side of the offer (supply side). This helps you better understand how the IoT product is created and delivered for a symbiotic growth.

Let’s further explore various IoT-based business models.

Product Business Model

This model enables to provide your customers with a physical IoT product and the software. You gradually can upgrade the software by notifying the customers of its cost and it will mirror the results at the consumer-end directly.

Example:

Let’s take an example of the self-driving cars. The company doesn’t have to additionally provide any product to the users; instead it can continuously improve the car by updating its onboard model and application. The firm can introduce a new feature and update its users by sending a notification. The users will just have to update the system to leverage that feature.

You can also use this model to collect data to create information service products to eventually sell with the product-service model.

Product-Service Business Model

This is a hybrid version of the traditional product business model and the newer service business models. This model enables organizations to offer a physical IoT product along with an informative model. Implementing information service to a product based on its collected data will ensure incremental revenue and provide a competitive advantage. Providing continual information to monetize the availability of the analyzed data that enhance the consumer’s process is the key of this business model.

Example:

Let’s take an example of ‘connected vehicles’. With the attached Onboard Diagnostic II chip, users will be able to know the temperature, RPM count, pressure, engine load, location of the vehicle, and fuel level. This information-based model revolves around vehicle safety, saving fuel and ultimately, reducing the maintenance cost. This information or data is the key for predictive maintenance that allows the customers to know the health of their vehicles to further avoid any mishap.

Service Business Model

This is a XAAS – Anything As A Service business model. The company rents a physical product with IoT solution and pays for it only for a period while it is running or working. The service business model is not exclusively related to software or physical products; it can also include the information products. This model allows the organizations to have a predictable and recurring revenue stream by providing their IoT services to the customers for a certain time period. However, your IoT solution must not only have value as a service, but, it must be aligned with how the customer expects to receive, consume and pay for the offering.

Example:

Let’s take an example of jet engines. The customers that don’t want to own and maintain the engines by themselves lease the IoT-based jet engines from the seller. The seller also provides maintenance by implementing predictive analytics. The customer pays for only the times where the engines were running and producing outcomes for them.

Service-Outcome Business Model

In the service-outcome business model, the seller becomes a business partner. There are two aspects of the service-outcome model. The first aspect is similar to the service model but instead of focusing on offering a single solution, there are product lines that are monetized. The other model comprises of monetizing based on the outcome or the performance of the offered solution.

The service-outcome business model has an add-on payment based on saving that incentivizes the vendor to improve its customer’s business. The add-on payment in this situation would be related to the reduction in human operating expenses.

Example:

Let’s take an example of the mining industry. Instead of providing the mining equipment, the company provides IoT solution for the equipment to their customers. And based on the data collected with the use of that IoT solution, the company can further adjust the equipment in accordance with the parameters of the better-performing ones. By adopting the service-outcome business model, both, the buyer and the seller receives an incremental value. This enables them to establish a baseline and generate a percentage of the incremental revenue or incremental savings based on phases or milestones.

Outcome Business Model

The final business model comprises of an entire IoT ecosystem. It brings together the producers (vendors) and the consumers (customers) of the IoT technology in order to monetize the solution. Instead of partnering with multiple vendors, the customer becomes part of an ecosystem that delivers the desired outcome.

This goes beyond the service-outcome business model where payment now is completely based on performance. This allows the alignment of the business models of the vendors with that of the customers.

Example:

Let’s take an example of smart farming. The outcome business model focuses on providing a bundled solution for an effective agricultural solution. Instead of providing separate solution for monitoring the moisture level of the soil, the sunlight, and the CO2 emissions, this model offers a set of solution that combines all these in a package. Separately, each of these separate product categories provides value, but when allied, dependencies are organized, creating greater value than the sum of the parts. This enhances the monetization aspect of the solution for the customers as well as the vendors as the payment will take place according to the outcome that each solution provides.

Analyzing business needs through IoT

The greatest challenge in implementing IoT isn’t technical. The key challenge lies in the business aspect. The challenges are further followed by lack of standardization and strong security. However, these are not the kind of challenges that can’t be addressed and solved by any organization. The key focus should be on using IoT technology to deliver and monetize outcomes.

Business issues may be more challenging than technology. Inculcating IoT solutions into your business practice does not mean you must change your business model too. It is equally important to align your sales and distribution goals along with implementing IoT initiatives. You can then continue on the IoT business model continuum as the time progresses.

Outcomes effectively revamp industries. They impact the business in a way that enables you to identify your competitors and partners. This reduces competitive risk and prepares you to decide when to spend the time and the resources needed to develop your IoT business and product line.

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Internet of Things (IoT) and Urban Transportation, to create a world-class Intelligent Transportation System (ITS) which is Safe, Secure, and Sustainable the industry has first to determine the right technologies which they should invest in, as it will be integral in shaping the future of Transportation and Digitize the human existence.
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Why Edge Computing Is an IIoT Requirement

How edge computing is poised to jump-start the next industrial revolution.

From travel to fitness to entertainment, we now have killer apps for many things we never knew we needed. Over the past decade, we’ve witnessed tremendous improvements in terms of democratizing data and productivity across the consumer world.

Building on that, we’re entering a new era of software-defined machines that will transform productivity, products and services in the industrial world. This is the critical link which will drive new scenarios at even faster rates of innovation. By 2020, the Industrial Internet of Things (IIoT) is expected to be a $225 billion market.

To jump-start the productivity engine of IIoT, real-time response is needed at the machine-level at scale and that requires an edge-plus-cloud architecture designed specifically for the Industrial Internet. From Google maps to weather apps, we’ve been experiencing the benefits of cloud and edge computing working together in our daily lives for quite some time.

But, what is edge? Edge is the physical location that allows computing closer to the source of data. Edge computing enables data analytics to occur and resulting insights to be gleaned closer to the machines. While edge computing isn’t new, it’s beginning to take hold in the industrial sector – and the opportunity is far greater than anything we’ve seen in the consumer sector, and here’s why:

Real-time data in a real-time world: The edge is not merely a way to collect data for transmission to the cloud. We are now able to process, analyze and act upon the collected data at the edge within milliseconds. It is the gateway for optimizing industrial data. And when millions of dollars and human lives are on the line, edge computing is essential for optimizing industrial data at every aspect of an operation.

Take windfarms for example. If wind direction changes, the edge software onsite would collect and analyze this data in real-time and then communicate to the wind turbine to adjust appropriately using an edge device, such as a field agent and connected control system, and successfully capture more kinetic energy. Because the data is not sent to the cloud, the processing time is significantly faster. This increases wind turbines’ production, and ultimately distributes more clean energy to our cities, increasing the value of the renewable energy space.

Big data, big trade-offs: The harsh and remote conditions of many industrial sites make it challenging to connect and cost-effectively transmit large quantities of data in real-time. We are now able to add intelligence to machines at the edge of the network, in the plant or field. Through edge computing on the device, we’re bringing analytics capabilities closer to the machine and providing a less expensive option for optimizing asset performance.

Consider the thousands of terabytes of data from a gas turbine. Sending this data to the cloud to run advanced analytics maybe technologically possible, but certainly too cost prohibitive to do a daily basis. Through edge computing, we can capture streaming data from a turbine and use this data in real-time to prevent unplanned downtime and optimize production to extend the life of the machine.

What’s Next

Today, only 3% of data from industrial assets is useable. Connecting machines from the cloud to the edge will dramatically increase useable data by providing greater access to high powered, cost effective computing and analytics tools at the machine and plant level.

Consider the fact that for years traditional control systems were designed to keep a machine running the same way day in and day out for the lifecycle of the machine. At GE Energy Connections, we recently debuted the Industrial Internet Control System (IICS), which successfully allows machines to see, think and do and will enable machine learning at scale. To take IICS to the next level, we’re creating an ecosystem of edge offerings to accelerate widespread adoption across the industrial sector. We’re advancing this ecosystem and empowering app developers who want to play a role in driving the new industrial era. 

Currently, to add value to a software system, a developer writes the code, ports it into the legacy software stack, shuts down the devices and finally, updates it. That’s all going to change. We are working on creating an opportunity for any developer to create value-added edge applications. Customers will be able port the necessary apps to their machine without having to shut it down, just like we do on our phones today. Companies will be able to download apps for their needs and update frequently to ensure their business is running smoothly. While no one likes to run out of battery on their smart phone, an outage for a powerplant is far more costly, so the ability to port apps without shutting down devices and being able to detect issues before it occurs will be a game changer.

From wind turbines to autonomous cars, edge computing is poised to completely revolutionize our world. It’s forcing change in the way information is sent, stored and analyzed.  And there’s no sign of slowing down.

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Your IoT platform is the heart of your entire IoT solution. Building a reliable and scalable IoT platform is not a piece of cake, which is why these days the market is booming with hundreds of thousands of IoT PaaS (Platform as a Service) vendors. Choosing the right IoT platform for your solution has become more complex than it was ever before. That’s why, in this blog post we have covered some of the best selection criteria to pick the right IoT cloud platform for your needs. Before we delve into this, you first need to know what an IoT platform is. 

What is an IoT Platform?

In simple terms, a platform is a comprehensive set of tools and services which allow developers to build and run an application. However, an IoT platform could have diverse meanings depending on whom you are talking to in the internet of things, IoT ecosystem. For instance, an IoT platform for cloud service providers is their infrastructure, where a developer creates an application. For hardware vendors, an IoT platform is the embedded board where you could write your IoT applications. For the sake of clarity, we are considering an IoT platform as the middleware layer responsible for consuming data from the devices and sensors and providing meaningful and actionable results based on that insight. Generally, an IoT platform offers a device software development kit a.k.a SDK or well defined APIs through which developers and programmers could easily connect to any hardware platform and avail of their cloud-based services.

If you have attended any IoT expo recently, most probably you would have noticed that almost every IoT platform provider claims to be better, faster, safer and smarter than others. Now, how do you make a wise decision in such a competitive landscape and pick the right platform that will reduce your solution risk? Don’t fret, we’ve mentioned below some key selection criteria to choose the right IoT platform. Let us take a quick look. 

Considerations In Choosing The Right IoT Platform

Alas! Today, a cloud IoT platform is opted for based on the effectiveness of the vendor sales pitch. This is mainly because the companies that are trying to get a handle on digital transformation do not possess the requisite knowledge or training in IoT specific areas, and IoT vendors usually woo their customers based on their impressive customer references.  There are some important technical evaluation criteria which are often overlooked.  These need to be kept in mind for choosing the right IoT platform. Let's take a look at them:

#1 Bandwidth

#2 Scalability

#3 Protocol

#4 Security

#5 System Performance

#6 Redundancy and Disaster Recovery

#7 Interoperability

#8 Edge Intelligence 

#9 Budget, developmental skills, and capacity of your in-house team

#10 Your business model and its specific requirements that must be met  

Hope you find this post helpful! If you did, share it with your colleagues and friends as well. For any query related to this post and IoT training in India, you can comment down below. Thanks for your time! 

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Connected Cars: From the Edge to the Cloud

Many of us have yet to see an autonomous vehicle driving down the road, but it will be here faster than we can image. The car of tomorrow is connected, data-rich and autonomous. As 5G networks come online, sensors improve and compute and memory become faster and cheaper, the amount of data a vehicle will generate is expected to be 40 terabytes of data every day. This will make the autonomous vehicle the ultimate edge computing device.

Last week at Mobile World Congress Americas in San Francisco, Micron Technology hosted a panel discussion with automotive industry experts where they discussed the future of the connected car and the role of both the cloud and the edge in delivering the full promise of autonomous driving (FYI – Cars are now big at wireless trade shows. See Connected Vehicle Summit at MWC).

Experts from Micron, NVIDIA, Microsoft and Qualcomm discussed what 5G, cloud, IoT and edge analytics will mean for next-generation compute models and the automobile.

Micron claims to be the #1 memory supplier to the automotive industry and notes that its technology will be required to access the massive streams of data from vehicles. This data must be processed and analyzed, both in the car and in the cloud. Think about going down the road at 70 MPH in an autonomous vehicle. You need to have safe, secure and highly-responsive solutions, relying on split second decisions powered by enormous amounts of data. To quickly analyze the data necessary for future autonomous vehicles, higher bandwidth memory and storage solutions are required.

Smart, connected vehicles are the poster child for edge computing and IoT.

Some intriguing quotes from the discussion:

  • “In last seven years 5839 patents have been granted for autonomous vehicle technology.” – Steve Brown, Moderator and Futurist
  • “There is a proactive side of autonomous driving that can’t be fulfilled at the edge.” Doug Seven, Head of Connected Vehicle Platform, Microsoft
  • “The thin client model won’t work for automobiles. You won’t have connectivity all the time.” Steve Pawlowski, Vice President Advanced Computing Solutions, Micron
  • “Once you have enough autonomous vehicles, the humans are the danger.” Tim Wong, Director of Technical Program Management for Autonomous Vehicles, NVIDIA

The entire panel discussion can be found in the video below.

Disclaimer: The author of this post has a paid consulting relationship with Micron Technology. 

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While media has extensively reported in recent years on the estimated 30 billion devices or “things” that are expected to be connected to the Internet by 2020, there has been little discussion regarding the development and education of the next generation of engineers who will need to be trained to meet the market demands and challenges these devices will create.
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Interview: 5G, IoT and Hurricanes

Last week more than 21,000 visitors from 110 countries and territories attended the 2017 Mobile World Congress Americas in San Francisco. It was the first for MWC in the United States, having recently gone into a partnership with CTIA to up the appeal of the long-time wireless tradeshow. We were introduced to Advanced RF Technologies (ADRF) and discussed the the transition to 5G, IoT and hurricanes with ADRF Chief Operating Officer Arnold Kim. 

For our readers who are not familiar with your company, tell us about ADRF?

Advanced RF Technologies (ADRF) is a Top 5 Distributed Antenna System (DAS) provider. We've been operating for more than 18 years and provide in-building wireless connectivity solutions to improve cellular signal and data speeds when there is either a lot of people in one area, or the building infrastructure doesn't allow frequencies to enter unobstructed from the macro network. Our products include DAS, small cells, antennas and passive components.

What industries are adopting your technology?

Every industry needs better connectivity inside of their buildings, so we have clients from many different verticals. We work with all four major carriers (Sprint, Verizon, AT&T, T-Mobile) and our products are currently in most of the Fortune 100 company buildings, many high profile sports stadiums, commercial real estate, healthcare, and more. We also do plenty of Public Safety installations. 

Device types continue to proliferate - no longer is it a type of mobile phone. How do you advise customers on what types of frequencies and standards to implement?

Most companies have an understanding of what their connectivity needs are. However our approach is to offer flexible and future-proof solutions that will grow with our clients. We try to ensure that our clients will never need to do a full refresh on their investment.

From a connectivity perspective, what are some of the near term challenges for IoT?

The biggest challenges we see regarding the IoT has to do with the sheer volume of devices taking a bandwidth on a network. If you think about a sports stadium and trying to connect 50,000 people, network density quickly becomes a challenge. For large enterprises the number of devices connected and the challenges can be just as large. There's a wide range of devices that will be connected that don't necessarily need a 5G connection. For instance, a connected oil pipe simply needs to send signal that things are working correctly or not. This can be accomplished using a 3G signal, on a low frequency band (which travels more effectively that a 5G signal on a high band might). In areas where the is limited connectivity, this is an important thing to consider.

It’s still early days, but how are you tackling the transition from 4G to 5G?

While the definition of 5G has yet to be settled, we are prepared for it, and those who have our systems in place will be too. Our new ADX V series DAS is modular and works with every type of frequency. When 5G becomes standard, whatever frequency may be adopted by each carrier to run the signal will be compatible with our equipment. At MWC America, we are announcing new Head End and Remote Modules for ADX V to support 600 MHz, the frequency that T-mobile plans to use exclusively for 5G. Not many DAS solutions today support it.

Let’s turn our attention to current events. Hurricane Harvey and the floods it caused in Houston. What role does ADRF play in public safety and how do you support response teams when critical infrastructure comes down?

ADRF performs a lot of public safety installations and we were one of the first companies to be FirstNet compliant. As an example, we recently installed two public safety DAS in the new Atlanta Braves stadium. Dense areas and public venues are mostly required by law to have complete, uninterrupted connection at all times. We provide the systems that allow for that. We have also introduced a series of mobile repeaters that can be implemented in crisis situations as well as outdoor venues where concerts are taking place.

Another example is Hurricane Sandy, a Category 3 major hurricane which affected coastal Mid-Atlantic states in 2012.Verizon deployed CROW (Cellular Repeater on Wheels) help provide interim emergency communications. CROWs are low cost, portable, over the air (which doesn’t requires backhaul) and can be used to provide expanded cellular network coverage or capacity. 

What's the most interesting implementation you've done? Why?

We were selected to make the happiest place on earth one of the best connected. Around Disney World parks, we put in a series of repeaters to provide better coverage and let families share their adventures. One of the important parts of the installation, especially in crowded venues where aesthetic is of the utmost importance, is to make sure equipment is concealed and hidden. Locating those areas when thousands of people are walking the entirety of the park every single day was a challenge.

Anything else you’d like to add?

We announced a new high power outdoor modular repeater at Mobile World Congress Americas, and while it’s intended purpose is to improve cellular connection in outdoor areas, it will be beneficial for IoT connectivity as more people become reliant on having these connections everywhere. Our products support every frequency including those that will be used for 5G, and the 3G and 4G that powers IoT connections. The importance of having blanket coverage for IoT cannot be understated, especially as more important devices become connected in the future.

 

 

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Internet of Things (IoT) and Women's Healthcare

Industry to realize that even though healthcare is one of the Industry's to focus, know that the biggest vertical or the significant market opportunity to focus is 'WOMEN.' There is a dire need to come up with IoT solutions that will help a woman manage and do things efficiently and with ease by ensuring preventive mechanisms and enabling her to be Safe, Secure, Empowered - 'Smart Women 2.0'.
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Digital Twins, Intranet of Things and AI

Here is the latest edition of the IoT Central Digest. Encourage your friends and colleagues to be a part of our community. Forward this to them. They can join IoT Central here. You can contribute your thoughts on IoT here.  

The Digital Twin: Key Component of IoT

Posted by Finbar Gallagher 

What is a Digital Twin and why do I care? A Digital Twin uses data from sensors installed on physical systems to represent their near real-time status, working condition or position. This modelling technology allows us to see what is happening inside the system without having to be able to get inside the system. It forms a critical step in the information value chain without which it is often impossible to get from raw data to insight, and therefore to value. As the Internet of Things grows, Digital Twins will become a standard tool for Data Scientists and Engineers wishing to use all this new data to automatically understand and respond to what is going on in the real world.

Best Platforms for IoT Development

Posted by Blake Davies

The fact is, two years ago we were surrounded by more than 15 billion connected devices; in three years from now, we are bound to see this number reach 30 billion, and 75 billion by 2025. Actually, if we were to believe Ericsson, next year there will be more IoT gadgets than mobile devices.

The truth is, we are finding it difficult to define what is an IoT device. With more and more people driving their connected cars and parking them in front of their smart homes, it is evident this market is only going to progress; and it is all happening at a rapid pace. And what are the platforms that are contributing to this extreme development?

Intranet of Things

Posted by Rajashree Rao 

Intranet of Things is a term coined by Airbus' Carlo Nizam, which refers to connecting the organization's assets. Intranet of things is an alternative model to Internet of Things, and both use the same kind of technologies and systems limiting the accessibility of connected things only to the virtual private network (VPN) or to the corporate network.

Security Issues To Expect In Mobile App Development

Posted by Melissa Crooks

Every week, thousands of new apps are seen hitting the mobile market. Unfortunately, the number of hackers working assiduously to tap into these apps to implant malware or phish for user information has also been on the increase. By implication, there is every need to take the security of mobile users very seriously particularly when it comes to app development.

How machine learning APIs are impacting businesses?

Posted by Sandeep raut 

In this Digital age, every organization is trying to apply machine learning and artificial intelligence to their internal and external data to get actionable insights which will help them to be closer to today’s customer. Today many of the organizations are using APIs to access the ready-made algorithms available in the market as they make it easy to develop predictive applications. In fact, you don’t even need to have an in-depth knowledge of coding or computer science to introduce them into your apps.


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The Digital Twin: Key Component of IoT

A Digital Twin uses data from sensors installed on physical systems to represent their near real-time status, working condition or position. This modelling technology allows us to see what is happening inside the system without having to be able to get inside the system. It forms a critical step in the information value chain without which it is often impossible to get from raw data to insight, and therefore to value. As the Internet of Things grows, Digital Twins will become a standard tool for Data Scientists and Engineers wishing to use all this new data to automatically understand and respond to what is going on in the real world.
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Digital Transformation in the Fashion Industry

Gone are the days when brand communication was mostly made up of ads that appeared on billboards, in magazines and/or on television. Today, all of this is augmented with Digital revolution.
The fashion industry is engaging with digital technology in new and different ways, in order to stay competitive and to engage with the ways that consumers are searching for jewelry, clothes, and accessories.
Technology is turning the fashion industry inside out. Today, consumers are most active as digital shoppers in the Fashion industry and are demanding a heartening digital experience across channels. People love the brick-and-mortar stores but also exploit online channels through social media, while on the go and online. These Omni-channel experiences should provide customers with a “wow” factor and Digital Transformation is the way to achieve this objective.
In today’s fashion world, competition is fiercer than ever, giving consumers’ far greater power & they demand only the very best customer service. Most of the fashion brands now have a social media presence on Pinterest, Instagram presence, tapping into our heightened engagement with imagery.
It can take many years to build a successful brand, but only a short time to destroy it. Fashion brands have always needed to be ready and able to respond to issues of uncertainty, risk, and reputation, all at varying times.
Burberry is the poster child in digital for fashion that started with live streaming runshows. Then came iPads and mobile apps for consumers to try out different outfits.
In Paris, a window front invites passers-by to download the Louis Vuitton Pass app in order to interact with the window and explore.
L’Oréal has put up a 'social wall' on its main website so consumers can share posts while shopping.
Harrods is the latest luxury retailer to transform its in-store experience with digital technology. They have many new super-high resolution stairwell displays at the flagship Knightsbridge, London store
Adidas has a store wall which shows shoe collections in 3D to see shoe designs from all angles.
With this availability of streaming big data and resultant analytics, fashion brands use the insights for hyper-personalization, align consumer experience and to track customer trends. The customer’s data is the core component of digital transformation in the fashion industry. So, hyper-personalization of mobile retail experiences will be huge in the near future.
Today, dressing rooms enhanced with augmented reality and social media features have transformed the shopping experience altogether. L’Oreal, Maybelline have already started testing special kiosks that enable shoppers to virtually try on makeup by simply taking a picture.
Even the most successful digital retail experiences are built from desktop experiences but the future is in mobile with a predicted 80% of sales traffic coming via this medium.

With digital at a side, fashion weeks across London, Paris, Milan & New York witness runway shows streamed online, Instagram & snapchat stories in real time, creating a close connection between consumers and brands. 
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Every week, thousands of new apps are seen hitting the mobile market. Unfortunately, the number of hackers working assiduously to tap into these apps to implant malware or phish for user information has also been on the increase. By implication, there is every need to take the security of mobile users very seriously particularly when it comes to app development.


Apart from being highly vigilant about security, app developers need to be able to identify these security issues and know how to avoid them, so as to be able to provide users with the security they need to keep their information and other data safe. Security issues can be experienced in various forms during any mobile application development process; some of which are explained below.

Failure to implement secure communications to servers

Most apps are designed to connect back to a server particularly those applications that control sensitive user information. Therefore, as a critical area of concern, mobile app developers must ensure safe transit between the app and the server. Nothing has to be interrupted on an insecure WiFi connection. Basically, this type of security is achievable through SSL certificates and encryption. User information can be compromised particularly if developers fail to employ the right SSL libraries.

Inability to plan for physical security breaches

Nothing much can be done to prevent theft or loss of mobile devices. In fact, mobile app developers have a very little role to play in this. However, they can greatly help to minimize the problem by executing a local session timeout code. Usually, users are obligated to enter a password from time to time to access an app. Rather than making this a daily occurrence, password requirement from devices can be observed once a week or at the fifth time the app is used. Local session timeout can also prevent the use of software that helps users remember passwords.

The use of weak encryption or an entire lack of encryption

Obviously, improves constantly which helps to make algorithms become obsolete and very easy to crack. Failing to use encryption or using weak encryption in an app can put sensitive user information at risk of getting exposed. In the course of using certain apps, users are obligated to input sensitive data like personal identification information or credit card numbers. It is sad to know that this information can be hacked particularly with the absence of good encryption. An app is more likely to be hacked when it becomes more popular. So, if you are looking to push your app to the top, there is every need to invest in good encryption.

Bypassing systematic security testing

Most importantly, Indian app developers need to consider themselves as the last line of defense. You stand to put your app users at risk when you fail to ensure a secure app. In every development process, testing is very important and as such, there is no need to rush in releasing an app. Ensure to test every common inlet for security issues, such as sensors, GPS, camera, and even the development platform. Viruses and malware are no respecters of apps – every app is vulnerable to an attack from them.

Developers should try as much as possible to avoid the eruption of a crash and debug logs during testing. These are often common places hackers often take advantage of for app vulnerabilities. Apart from increasing the speed of an app, NSLog statements on iOS can be effectively disabled during iPhone app development to avoid vulnerabilities. Also, an Android app remains vulnerable until the Android debug log is typically cleared.

Lack of proper planning for data caching vulnerabilities

Unlike standard laptops and desktops, mobile devices are well-known for their ability to store short-term information for longer periods. This caching method generally helps to increase speed. However, since hackers can easily access cached information, there is every possible for mobile devices to be susceptible to security breaches. A major way of avoiding the problem is by demanding for a password to use an app. However, this can affect the popularity of your app, as most app users often find the use of passwords to be quite inconvenient. Alternatively, you can program the cache to be automatically erased every time users reboot their mobile device. This is another meaningful solution to data caching vulnerabilities.

Adopting other developers’ code

Developing an app from the start can be very time-consuming but with the availability of numerous free codes, this process has been extremely simplified. Interestingly, some hackers create codes for unsuspecting developers. In the hopes that application developers would pick up their codes, some hackers have ventured into creating anonymous codes. Through this, they tend to gain easy and free access to any information of their choice after the app has been designed and released.

Although it is never a bad thing to build upon people’s ideas, however, it is highly essential to carry out relevant research before doing so. In order to avoid experiencing security issues, it is well advisable that you make use of code from reliable sources. So, if you’re looking to build upon the ideas of a third-party, ensure to use sources you can trust. As a matter of fact, always use verified and trusted sources for code and ensure to be on the lookout for phishing scams by reading the code line by line.

Slow patching of app

Just because your app has been launched does not mean that you are done with the development process. Hackers are always on the move, they do not relent in their efforts to break through an app and so, they always work very fast. Most times, they search for apps with irregular security updates. Then they exploit these security breaches to bring down the app. Just to let you know, it is good to perform regular security updates by revisiting the app often.

However, users on their own part may be unable to get these patches on time. This is because they have to accept and download them. Additionally, the approval process of a patch on an iOS platform can typically take up to a week. Obviously, patches can take a while to reach users. To this end, you can put user information at risk if you fail to stay right on top of new security updates.

When it comes to creating apps that deal with confidential matters such as personal information and customer credit cards, there is always no room for error. To any app developer, the repercussions of the smallest security breach can be highly catastrophic. As a matter of fact, it is your duty to protect both your app and its users. So, ensure to take all necessary precautions so as not to get caught unawares.

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In this Digital age, every organization is trying to apply machine learning and artificial intelligence to their internal and external data to get actionable insights which will help them to be closer to today’s customer.

A few years back it was the field only for data scientists and statisticians, who used to analyze the data, apply several techniques and provide results.

Today many of the organizations are using APIs to access the ready-made algorithms available in the market as they make it easy to develop predictive applications. In fact, you don’t even need to have an in-depth knowledge of coding or computer science to introduce them into your apps.

APIs provide the abstraction layers for developers to integrate machine learning into real world applications without worrying about which technique to use or how to scale the algorithm to their infrastructure.

These APIs can be categorized broadly into 5 groups:

  • Image and Face Recognition: It understands the content of the image, classifies the image into various categories, detects individual objects and faces, detects labels and logos from the images.
  • Language Translation: Translate text between thousands of languages, allows you to identify in which language any text that you need to analyze was written. Some APIs allows organizations to communicate with the customer in their language.
  • Speech Recognition and Conversion: Today most of the customer service is handled by Chatbots with underlying APIs helping simple question and answer. Speech to text APIs are used to convert call center voice calls into text for further analysis.
  • Text /Sentiment Analytics using NLP: With the rise of Social Media, consumers easily express and share their opinions about companies, products, services, events etc. Companies are interested in monitoring what people say about their brands in order to get feedback or enhance their marketing efforts. These APIs can identify, analyze, and extract the main content and sections from any web page. They further help in to analyze unstructured text for sentiment analysis, key phrase extraction, language detection and topic detection. There are some tools also helps in spam detection.
  • Prediction: These APIs, as the name suggests helps to predict and find out patterns in the data. Typical examples are Fraud detection, customer churn, predictive maintenance, recommender systems and forecasting etc.

Google Cloud, Microsoft Cognitive Services, Amazon Machine Learning APIs & IBM Watson APIs are the leaders in the market.

With growing number of free/reasonably priced APIs and tsunami of data generated every day, the race is on as to which is the best Machine Learning API.
These machine learning APIs are not yet perfect or matured and they will take some time to learn and act accurately. But they allow faster time to market-based on ready availability, rather than asking data scientist to code the algorithms.

In future, machine learning will lead to revolutions that will intensify human capabilities, assist people in making good choices and help navigate through the world in powerful ways, like Iron Man's Jarvis.
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