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Over the last couple of years, the Internet of Things grew into a huge gate between the reality and the digital world, and CES 2018 was the event that nailed it. IoT dominated the event with a vengeance, and it could be roughly divided into two major areas: smart home (with a nod to smart city) and industrial Internet of Things (with a nod to the much-hyped Industry 4.0).

The event showed the inevitable changes in the industrial sector that are likely to reward early adopters with shares on the market. Meanwhile those who avoid innovation get left behind in the long run. Such companies as Bosch reinvent the way manufacturers run their facilities, with a focus on increased performance and care for safety of human workers.

Smart home was represented not only by a huge variety of standalone products, but also by closed ecosystems created by such consumer tech giants as LG.

Automotive industry always has been leading in innovation with self-driving and connected cars being part of the IoT market. This year all major car manufacturers hosted a kind of car show inside CES, introducing new automotive IoT products.

Besides these spheres, there were two more major followers of IoT trends: healthcare and retail. Both aim for automation of operations, provision of personalized experience to customers, and overall transformation of the ways they operate.

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While IoT has become more of a reality than just an industrial buzzword, what made it impactful among the masses is its ability to build “Smart” solutions.

The IoT based home automation or smart homes endow us with more security, better control of our assets, and cost savings through judicious and efficient use of energy resources such as water & electricity, and real time monitoring.

The IoT enabled smart home solutions are of great help in preventing property damage through theft, water leakage or flood, events of fire break out  – to name a few.

The Basics/Fundamentals of an IoT smart home solution

IoT Smart Home

While a smart home application consists of a set of sensors, gateways, networking channels, cloud framework and web-dashboard and/or a mobile app ; it is the sensor that adds life to an IoT system by sensing the all important data (in the form of temperature, proximity & more).

IoT Sensors: The Cool Guys in the Town

IoT sensors are one of the coolest inventions in the modern times after internet.
Why?

Not only because IoTsensors are:

  1. Easy to set up/install
  2. Easy fault detection
  3. No messy ‘wired’ connections and hence offer advantages of better mobility and management.

But, because the sensors are the ones that render your smart home solution ‘smart’. IoT sensors are IP bases and hence can be connected to the internet.

IoT Sensor nodes sense and capture the real time data from your home appliances and the surroundings with the help of sensory nodes and send it to the cloud backend via the IoT Gateway Device.

Accuracy of the information communicated by the sensors is very important for a robust smart home solution.

Any delay or inaccuracy (due to IoT Sensor Nodes) in sensing the ambient information can be at time catastrophic; for example if a fire breaks out and the sensors fail to detect it, it is needless to say how costly it can prove to be.

Types of IoT Sensors for Smart Home Solutions

Today, various versions of Smart Home Solutions are available in the market with high end sensor technologies and advanced features for added comfort and security.

But at the core, every smart home solution application comprises of basic sensors that are capable of detecting changes in the ambient data based on various stimuli such as temperature, smoke, motion etc.

Most sensors come in two varieties:

  • those that are in direct contact with the physical objects to sense any fluctuation, and
  • those that are remotely connected to the objects

Let us look at some of the most commonly used smart home sensors:

  • Temperature Sensors: Temperature sensors are capable of detecting any fluctuations of temperature in their surroundings

    The information from these temperature sensors are used by the  a home automation solution regulation of the temperature within the rooms to a desired level, to perform certain actions such as turning on the fans and air conditioners, rolling down the curtains etc. based on the user’s request.

    Some of the commonly used temperature sensors in smart home solutions are MSP430 series from Texas Instruments (TI), LM35 from TI, Maxim Integrated DS18B20and more.

  • Humidity Sensors: Humidity sensors are a great way to keep in check the humidity levels. The ideal humid level within homes should range between30 percent and50 percent.

    If the moisture level goes below or above this range, it leads to allergy, dryness of the skin or at higher levels a feeling of heaviness and air becomes suffocating.

    Many of the smart thermostats now come integrated with humidity sensors to detect any change in the moisture level.

    These humidity sensors help in maintaining the air quality and alert you about presence of allergens, mold growth etc.  HTU21D from TE Connectivity, Honeywell Humidicon™HIH6100 series and NPA-700 Amphenol Advanced Sensors are the most commonly used humidity sensors in modern smart home solutions.

  • Optic/ Light Sensors: Optic sensors are great way to detect the ambient light levels. These sensors are useful in measuring the external light levels and accordingly switching on/off of the lights to conserve energy.

    These IoT sensors can also be used for controlling all the lighting installations within your homes – turn them on/off or change their brightness as and when required. Some of the commonly used optical sensors are Adafruit TSL2591 and Addicore BH1750.

  • Fire/Smoke sensors: When it comes to ensuring safety of people and property when a fire breaks out, the timing of alert is very crucial.

    It is here that importance of fire/ smoke sensors comes into light. Usually, smart homes come with CO (carbon monoxide) detector that alert you whenever there is unusually high level of CO inside the building. The Maxim Integrated MAX30105 is a widely used sensor for fire detection.

  • Proximity/Motion Sensors: The motion sensors are crucial for ensuring safety of your home and property especially when you are not present at your homes.

    These IoT sensors can alert you of any suspicious activity inside or around your home. These sensors sense any motion or vibration and can respond to 2D or 3D gesture, UV Index, or heart rate. Some commonly used motion sensors are Si114x and Si1102 from the Silicon Labs.

    There are even more variations of IoT sensors such as pressure/gas sensors, sound detectors, sensors to detect water levels – that are installed in smart homes these days for added security and safety of your dear ones as well as you valuable properties.

Conclusion:
Thus, the power of IoT technology to make sense out of ‘sensor ‘data and to etch out smarter and comprehensive solutions is already transforming the world. The design and development of an IoT sensor node based on standard protocols is a critical factor in deciding the success and efficiency of the IoT implementations. Unless the data sent by the sensors is not accurate or timely, there is no point in having a high-end and extensive IoT setup.

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Here's Wishing you a Very Happy, Smart, and Innovative New Year! 

Internet of Things (IoT) has been revolutionizing the world with its millions of innovations. In 2017 IoT reached its milestone by creating several break-throughs with significant technological advancements. All of these technologies, products, and solutions saw the limelight at the world's largest and the most powerful technology event, Consumer Electronics Show (CES) 2018 at Las Vegas, a Catalyst for Innovations.  

The vision of the Internet of Things (IoT) is to transform the way individual lives, work and communicates with one another. These innovations are meant to simplify by offering products and solutions that are simple, affordable, easy to use, efficient and productive for building a Smart, Safe and Connected world. 

With these above IoT goals in mind, I am personally impressed to highlight some of these mind-boggling innovative products and solutions that was unveiled last week at the CES 2018. 

1. Forever Batteries: The battery maker Ossia launched its AA-sized batteries that suck power out of the air using its IP technology called Cota. Ossia has developed a means of wireless power transmission which Ossia claims can keep the AA battery charged up or provide power to a smartphone that either incorporates Cota's technology natively or uses specific charging case. However, Ossia hasn't revealed much about the working of their Cota technology. This irreplaceable battery will eliminate the spending expenditure 'Forever'. 

2. Byton's $45,000 Gadgeted Electric Smart Car: Chinese Start-up unveiled its first and futuristic real smart electric car. The name refers to 'Bytes on Wheels.' Former BMW and Apple Engineers created it. It has the hardware on board to enable full self-driving mode. The vision behind Byton is to be the company to bring to the market the first real 'Smart' car. Inside the car, the drivers and passengers can interact with the huge display panel. Byton aims to merge an individual's life outside the car with the experience inside the vehicle. Everything will be controlled via the touch, and certain aspects will be controlled via voice (voice recognition by Amazon's Alexa) and gesture control. The key is customisation. When the car is in drive mode, specific features will be disabled. It will not allow watching videos for instance. Byton aims to build a platform where, when there is autonomous driving all occupants of the car including the driver can interact. Some of the features of Byton will be fully-disabled until we live in a world of fully autonomous driving. Fierce competition to Tesla and from my perspective it is redefining life. But the one challenge that might stump Byton is the lack of fast-charging stations. Another major competitor to watch for will be Fisker's EMotion a luxury smart autonomous sports sedan. Although Fisker is not a competition concerning the price factor; however, is a competitor to watch for its technology and new solid-state battery which they filed for a patent. The battery is expected to provide the Electric Vehicles with a range of over 500 miles on a single charge and will take only one minute for recharging. 

3. Razer's SmartPhone Laptop - Project Linda: Razer brings you a disruption in the world of gaming with its Project Linda which is a concept of ultraportable laptop design powered by the Android-based Razer Phone. The docked phone serves as an intelligent touchpad, bridging the gap between handheld entertainment and laptop convenience. The Razer Phone's display, performance, and dual front-firing speakers combine seamlessly with Linda's keyboard, larger screen, and battery to provide ultimate mobile hybrid setup for creativity, gaming, and productivity. Although the Project Linda feels like a product from a Sci-fi world or a future that might not see the daylights after the CES 2018. However, the prototypes like a concept car for gadgets is both sensational and aspirational. Razer hasn't confirmed if it plans to make the smartphone project Linda for a go-to-market next year. 

4. Google Voice Assistant: Google creates a whirlwind at the CES 2018 with its Voice Assistants and predicts to dominate the future homes. Lilian Rincon, Google director of product management, reckons customers making their home “smart” by using the Assistant to turn on lights, boil the kettle and do other tasks could save 15 minutes from their morning routine. Google's Voice Assistant is eroding the well established Amazon's Alexa, a fierce competitor for its voice assistant. Google has already discussed partnerships with various Industry verticals for integrating their Voice Assistant in realizing the goal of "Smart and Connected World." In my opinion, I see this as the most significant breakthrough as Google is not charging the end-user but is working with all its third-party vendors to integrate the voice assistant into their products and solutions. Google showed off a plethora of new Voice Assistant-enabled devices from companies like Lenovo, Sony and LG, featuring “smart displays” that displays information like the schedules, things-to-do, cooking recipes, and other bits of visual accoutrement whenever we ask the Assistant for something. Also, you'll find Assistant integration inside more televisions, headphones — even in new cars, thanks to Android Auto, which is already available in more than 400 car models. The Assistant integration eliminates the need for having an independent device and allows you to manage everything from your one device - 'The SmartPhone.'

5. Smart Hearing-Aids EARGO Max: Technology for healthcare and especially the elderly is something I am very much interested though tech for elderly-care is still a growing area. The ageing population is a growing business opportunity, and EARGO Max might be the airpods of hearing aids. The hearing-aids have a collection of useful features, the most stand-out of which is a complete lack of need for expensive replaceable batteries. The set of hearing aids includes Dynamic Noise Reduction, with Eargo tech which allows the devices to vary noise reduction based on environment. When the environment gets louder, noise reduction ramps up. These devices also change based on user preference. The "Flexi Fibers" hold the hearing aids in place, while the domes “increase the amount of ambient bass sounds and eliminate feedback. I understand very well how useful and life-changing these features are since my mother suffers from major hearing loss and will benefit her tremendously. However, the one road-block I see is the cost factor. Currently, Eargo Max is priced at $2,500 which I believe is quite too high and defeats the purpose of providing cost-effective and affordable products. Hoping to see the Industry ramping up to address this gap. 

To summarize, CES 2018 was a curtain raiser for millions of products, solutions, and technologies which created hope for a future that is beyond imagination. In my opinion, there is still a long way for the Industry stakeholders to meet the primary objectives of IoT which will redefine this entire universe. The one vertical which has gone mainstream is the Autonomous Vehicles or the Self-driving cars. The major tech giants such as Cisco, Nvidia, Intel, Amazon, Google, Tesla, Apple, GM, Toyota, and many others made announcements focusing their investments in this sector.

 

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By Mark Benson, CTO, Exosite 

So you’re the designated IoT champion, leading the connected-product charge for your organization. You may even have “IoT” in your job title. The burden is on you, and you’re constantly absorbing everything you can about how to successfully execute the digital transformation of your business. Beware, this journey will be rife with roadblocks, both externally and internally.

Many IoT challenges exist due to a lack of industry-wide standards around proven success. Everyone starts from ground zero, and few have crossed the finish line. Based on experience working on IoT-innovation programs across a variety of industries, here are five key considerations regarding where to focus your efforts early on and how to move your company forward as you build, deploy, and launch the next generation of your product.

Understand What the Market (Really) Wants

Any corporate IoT endeavor should start by answering the question, “Why build and market a connected product in the first place?” Too many companies have implemented IoT programs centered on the “how” of their smart-product strategy. It’s no wonder over seventy percent of these initiatives are estimated to fail if they weren’t even certain they were building something of value in the first place.

Understanding your market—and what your customers will pay for—through analysis, research, and testing is a smart way to launch an IoT project. Be open and responsive to feedback and contrarian lines of questioning. Successful enterprises will run quick proof-of-concept tests early on that integrate a variety of technologies to validate feasibility, business-model mechanics, user experience, and data integration. This enables them to learn fast, pivot as needed, and plan a well-executed, long-term strategy before investing too heavily.

Garner Leadership Investment and Approval

Another important question is “Who in your company is necessary to making IoT happen?” The answer, more often than not, is everyone. Your business’s IoT success depends on organization-wide alignment from the start, and executive, top-down sponsorship is crucial to making that happen.

As the IoT torchbearer, a major hurdle will be your ability to gain the needed support and buy-in from your leadership team and decision-making stakeholders. Be prepared to present clear objectives and a comprehensive go-to-market strategy. Work with key executives to create a compelling and actionable vision statement that explains core differentiators for the future of your company.

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Device Twins In Industrial IoT Solutions

Guest post by Rick Blaisdell

Device twins are becoming a hot topic as the IoT network gathers greater popularity. Device twins are important in the development and deployment of industrial IoT solutions. They act like virtual devices representing the data and metadata of the physical device connected to the IoT network.

The rise of device twins has been noticed by one Gartner report, which placed this as a top five trend for 2016. The twin devices are typically called twins, shadows or device virtualization.

Each device activated and registered with an IoT platform contain two categories of data. The first one is the metadata which doesn’t change often. Here we include the details that describe precisely the device such as serial number, firmware version, model or year of manufacturing. The second category of data contains real-time and unique data from the device.

Why is the digital twin so valuable?

The concept of the digital twin is a powerful one that can bring real benefits such as:

  • Visibility: the virtual version of the device allows visibility in the operations of the machines and also enables larger interconnected systems.
  • Predictability: by using various modeling techniques, mathematics-based or physics-based, the digital replica can be utilized to predict a future state of the device.
  • Analysis: through well-designed interfaces, the interaction with the model is simplified, and people could address “what if” questions to simulate various conditions that are impractical to create in real life.
  • Documentation and communication mechanism: the digital twin can be used as a communication mechanism, which can provide understanding and explications for different behaviors.
  • Connecting backend business applications: the digital twin can be used successfully to create a connection with the backend business app to achieve useful outcomes in the context of supply chain including procurement, transportation, and logistics.

Industrial twins

These implementations are adopted in general by the Industrial IoT providers, and these constitute information from the Product Lifecycle Management tools on the design of a machine, but it could also be designed as a model of one device. The industrial vendors look at the physical properties, the design of information and then present them in an asset model.

These industrial twins could be implemented as:

  • Virtual twin (device virtualization);
  • Predictive twin (using analytics models);
  • Twin Projections (insights projection);

Within the next few years, billions of things will be represented by their twins, creating a dynamic software model of the physical item. The digital shadows combined with the representations of environments and facilities, as well as businesses, people or processes will enable a sophisticated digital image of the real world, suitable for analysis, simulation, and control.

If you have questions about the topic do not hold back on them.

This post originally appeared here.

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Once a shepherd had two horses. One was strong and fast, another one was slow and weak. The shepherd instead of looking after the weak one and trying to make him fit, he preferred riding the healthy one and taking him almost everywhere. He also fed him better which in long-term led the healthy horse to become heavy and feel lethargic all the time. Later the healthy one became sick and the shepherd then instead of having healthy horse has to deal with two sick and weak horses.

What does this story have to do with digitalization? Well, this is our approach to the whole idea of digitalization and its implementation worldwide. Instead of investing time and resources and bringing the idea of digitalization to the underdeveloped nation or the “weak horse”, we are feeding the already “healthy horse” or the developed nation with fascinating ideas and projects which might result into sickness in the long term. The early symptoms of this sickness can already be witnessed. A World Economic Forum (ref:weforum.org) report says that labour markets will witness a net loss of over 5 million jobs in 15 major developed and emerging economies. Is this in line with the idea of digitalization? 

The World witnessed more than 4.000 ransomware attacks per day in 2016 (ref:Justice.gov) which approx. 300% more than that in 2015. This since we made the whole IT infrastructure more vulnerable to such attacks by simply connecting every electronic device to the internet. Are we just simply neglecting the side effects of digitalization? 

Being not able to read your power meter values on your smartphone is not a problem as compared to not having access to water and electricity due to scarcity. Being not able to sit in a self-driven car is not a problem as compared to be stuck in traffic jam in peak summer for hours and breathing exhaust gases all the time. These are some of the typical problems of the underdeveloped or developing nations. The question which the Gurus of digitalization should address is that if the idea of digitalization/IoT for industry/IT giants are about to create business and thus pushing up the turn over, then why not boosting digitalization across such nations by diverting the resources there. This is far better than making own factories intelligent and then laying down hundreds or thousands of hardworking and loyal employees.  

Here are some of the typical problems of the under-developed or emerging nations, the answer to which could be well-implemented digitalization. 

Corruption: According to an IMF report more than $ 1 trillion dollars is paid in bribes each year around the world with underdeveloped and developing countries topping the list of being the most corrupt nations. People in these nations pay up to 13 percent of their income to bribes which later discourages them from services made available by the government. Corruption is the root cause of crime in many countries and acts like a fuel to poverty and social inequality. Institutes worldwide are trying their best to strictly monitor and thus eliminate corruption worldwide, unfortunately without much success until now. This, however, might change in future. Experts nowadays are betting on the invention of blockchain to fight corruption. The blockchain is a centralized technology which offers full transaction transparency, thus providing no room for fraud or capital manipulation. Blockchain implementation, however, demands a solid digital infrastructure which in my opinion is an area where IT communication network provider should look into.

Image courtesy: Wikicommons

 

Commodity wastage or theft: Water and electricity to two important needs of every society. Their scarcity or theft leads to a major human rights problem. The figures about water scarcity worldwide are very alarming with some 780 million (ref: Water.org) people having no access to clean and safe water. One of the major reason for water scarcity is wastage or theft in emerging/underdeveloped nations. The electricity theft worldwide touched $89 billion (ref: Northeast Group LLC) annually in 2015 with India, Brazil and Russia being the top 3 nations with highest losses. With an introduction of smart water and electric meters along with in-built sensors, certain startups are trying to monitor the overall water and electricity supply and consumption. Based on which a customer profile can be generated so that any irregularities can be immediately reputed to the consumer as well as the respective authorities. This again needs support from government and the industry without which it will take ages to tackle the mentioned problem.

Image courtesy: Wikicommons

 

Landfills: Seems like the never-ending problem of nations with poor or insufficient infrastructure People in some of these nations spend their lives in an area surrounded by a heap of waste or landfills. This is there exist no proper waste management plan due to lack of manpower or resources. This bottleneck can, however, be eliminated by daily tracking and monitoring of location (webcams) with landfills and adjusting the waste management plan accordingly. Here, for instance, the resources can be diverted to a location with a frequent buildup of waste. This, however, demands a strong digital infrastructure which can only be established if government and industry work together.

 Image courtesy: Wikicommons

Street crimes are on the rise in nations with higher social inequality. Authorities in these nations feel helpless due to the degree and frequency of crime happening every day versus the available manpower. Interestingly, the biggest problem is that many of these crimes go unreported since people in these nations have lost their faith in government/authorities/police. The legal structure in these countries needs a face-lift which can be achieved by digitalization the complete process of monitoring, documenting of crime and its prosecution. The street light camera or public surveillance camera project in the US is a good example of crime monitoring here. The public surveillance camera installed in Baltimore and Chicago (ref: Urban.org) region not only resulted in reduced crime but also proven to be cost-effective than the conventional way. A cloud-based complain lodging system can be established allowing the verified victim to lodge complain straight via smartphone. A digital platform managing all these complains based on degree or severity of the crime as well as the date of occurrence can be created.

Healthcare: Proper healthcare is still considered as a luxury in many of underdeveloped/developing nations. Approximately 80 percent (ref: facts and details.com) of people in these nations rely on public hospitals for treatment. These hospitals are often running over-capacity and are ill-equipped.  A healthcare digital platform which integrates the existing database of all the hospitals in the region along with a list of their respective treatment capabilities, services could ensure the even distribution of patient load in these hospitals. Thus allowing treatment to each and very needy individual without any delay. Access to a healthcare App coupled with the platform can allow the patient to see which hospital nearby has an available bed and a doctor and can provide him/her with an option of online booking. 

Uncontrolled traffic: Interestingly an ongoing problem of developing countries. With four-wheeler getting cheaper and infrastructure narrower day by day, the traffic condition in these countries is on the verge of a breakdown. Traffic jams and road accidents are on increase with pollution level due to an increased number of vehicles on road, reaching new peaks. Equipping traffic lights with infrared sensors or webcams can help the authorities to divert the traffic in case of traffic congestion. Moreover, long-term monitoring (analytics) can be beneficial in planning infrastructural change, road buildups in regions where traffic jams are frequent. Car sharing/renting/hiring apps should be promoted. By combing the complete transportation system along with consumer profile, one can monitor the user segment preferring public transportation over own. This segment can then be rewarded in form of discounted bus/train/metro tickets or by means of an annual grant.

Image courtesy: Wikicommons

The list of problems of these nations is long but properly implemented digitalization along with the synergy between government and industry could be the answer to all of these problems. We should not repeat the mistake of the shepherd and should help the weak horse to be as fit as the healthy horse. Only this way we can achieve social and economic balance across the world. 

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IoT Gateway- Enabling Edge and Fog Computing

Connected devices are becoming essential components for enterprises as they can drive significant connectivity and integration between systems and data. The increasing number of devices getting connected to each other generates a huge amount of data.

However, when it comes to leveraging the full potential of these connected devices and data, it is necessary to have a scalable and robust environment which allows faster processing of data between systems.

The fundamental concern is on how to efficiently manage this data, as any data loss or delay in processing of data from a connected ecosystem can cause critical damage to an enterprise’s workflow.

Role of IoT gateway edge analytics in data processing & management

IoT Gateway is the key to any IoT deployment. It is a bridge between IoT devices and cloud that enables remote control of the devices and machines. The increasing number of devices propels the requirement for IoT gateways to solve the data management issues with Edge Analytics.

Edge analytics with IoT Gateway allows data processing before it is transmitted to the cloud. The gateway collects all the data from the connected devices and executes necessary algorithms or rule engine on it and sends actionable commands to connected devices. The actions allow for response to be taken in real-time and also helps in self-healing mechanism during faults/errors.

In large enterprises, having multiple geographical spread, there are a huge number of connected devices and generated data. This heterogeneous data, distributed at different levels (Devices and machines ) have high latency in cloud transferring due to the uncontrolled data flow. Here, distributed edge analytics is the solution as it allows faster data transfer and processing, resulting in the reduction of latency.

AWS Greengrass is the best example for the edge analytics setup. It allows enterprises to run local compute, messaging, data caching, sync, and ML inference capabilities for connected devices in a secure way. Greengrass ensures quick response of IoT devices at the time of local events, that reduces the cost of transmitting IoT data to the cloud.

How distributed edge analytics works in larger geographical areas

Let’s take an example of smart grids to understand the concept in-detail.

Smart grids are the combinations of smart meters, smart appliances, renewable energy resources, energy efficient resources, and substations. In a particular city area, the number of smart meters is equivalent to the number of households in that area. These AMI (Advanced Metering Infrastructure) continuously collects the energy consumption data and route it to the IoT gateways. The gateway enables edge analytics and then the processed data is rerouted to the cloud by the gateway.

As the number of AMI is high in a particular area, the number of gateways will be proportionately higher.

Merits of distributed edge analytics:

  • Reduced data transfer latency
  • Fast access to the faulty areas
  • Quick functional recovery and self healing capabilities that brings resilience in the system

Distributed edge analytics also enables fast response to the cloud in case of faults and failures with Fog Computing so that the recovery time can be minimal. Let us understand how.

How fog computing works with smart grids for faster data processing

Fog computing is the combination of two key components of data processing, Edge and Cloud both. The idea of combining edge computing with more complex computing (cloud computing) results into more reliable and faster data processing.

As smart grid tech is increasing rapidly, fog computing is the best tool for the data and information processing between consumers, grid operators, and energy providers.

In the edge analytics concept, the gateways form a mesh network. The individual mesh network of a designated area creates Fog Nodes. Each fog node is connected to each other, resulting in a fog network of smart meters and IoT gateways in the larger setups. The combination of these fog nodes then allows distributed fog computing, which gives the benefit of fast and real-time data analysis in any large geographical area. This further enables faster fault response time.

Use case of smart grids in distributed edge analytics

eInfochips developed a solution in which gateways are being connected into a mesh network with peer-to-peer communication. Mesh and cluster of gateways enable high availability and reliabilityof the IoT deployment in smart grids. Clustering enables distributed edge analytics. These distributed edge nodes allow processing of data at the edge before transferring it to the cloud.

According to the market research data, fog computing market is growing with the attractive amount of cost annual growth rate (CAGR), 55.6% between 2017 and 2022 (MarketsandMarkets).

With our edge and fog computing expertise, we help the IoT solution providers to optimise their computing infrastructure by distributing load between the cloud and edge devices in an intelligent way through our ready-to-use dynamic rule engine or custom solutions.

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IoT Minute Episode 62: The Collaborative Edge

When retail machines talk to each other directly or collaborate through edge gateways, customers are more likely to find what they're looking for. Why lose a sale due to a lack of inventory when a customer can be redirected to a nearby location where their product preferences can be met.

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The phrase, “the future is here,” is overused and has evolved into a catchphrase for companies struggling to position themselves in times of technological or digital transformations. Still, the sentiment is understood, especially in times like today, where the Internet of Things is quite literally changing the way we think about hardware and software. We’d like to offer an addendum to the phrase: “The future is here more quickly than we thought it would be.”

Digital transformation, increased computing ability, smart hardware and the growth of connectivity capabilities created a perfect storm of accelerated industry, and many were left scrambling to sift through the large amounts of information and solutions available. With that in mind, we wanted to provide some advice for companies across the industrial sector for the best ways to optimize operations for the Industrial IoT.

1) Upgrade your network and throughput capabilities.

Nothing can kill the ROI of automated processes more quickly than the literal inability to function. It’s important to understand that as you upgrade machinery and invest in the software to run it all, those systems demand greater bandwidth in order to effectively utilize the big data and analytics capabilities. Several options exist, but for most companies some combination of industrial-strength broadband (WiFi), narrow-band, cellular and RF communications will create the most effective network for the needs.

2) Invest in smart hardware.

This may seem like a no-brainer, and really, in the not-too-distant future, you may not even have a choice, but the shift toward Fog Computing is gaining momentum and being able to run decentralized computing between hardware and the Cloud can not only create greater operational efficiency, but it can also allow your data transmission to run more smoothly as well. The beauty of a Fog Computing system is that it allows a greater number of devices to transmit smaller data packets, which frees up bandwidth and speeds real-time data analytics. The core of this lies in the smart hardware.

3) Be proactive about application development.

Smart hardware means that it has the ability to host applications designed specifically for your needs. Previously, many companies shied away from app development because it required highly skilled developers and devices capable of hosting those apps – a combination that wasn’t readily available. Today, the scene has changed. With the rise of Node-RED, it is much easier today to create proprietary applications without a computer engineering degree, and any company serious about leveraging IIoT technology needs to be able to to use the full scope of its data.

4) Secure your communications.

There isn’t much more to be said about the importance of cybersecurity. If the last few years of massive data breaches haven’t rung alarm bells, then you aren’t paying attention. Cybersecurity today is a multi-layered need. Most companies building smart hardware are beginning to build encryption directly into the devices. But, since many companies use Cloud applications for computing and analytics, it is important to invest in strong security measures at that level as well. Unfortunately, the sophistication of cyber-attacks are only going to increase, along with the increase in importance of the data needing to be protected. It pays to be paranoid and act accordingly.

Further Reading:

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Going beyond connected buildings

Connecting smart buildings to smart grid, smart transportation, & other smart services is the need of the hour to truly manifest the potential of IoT . However, communicating with numerous systems made up of different protocols is a major challenge faced by integrators. Protocol converters are widely used to convert protocol A to B, but such devices do not offer ease of configuration and flexibility demanded by IoT. The solution to this is a universal gateway – a device that transacts data between two or more data sources using communication protocols specific to each of them. The Universal gateway is also termed as a universal protocol gateway. Such products include a combination of hardware & software, and used to connect data from one automation system like building automation to another like a smart grid.

Role of universal gateway in building automation

 

A typical building automation system comprises of five key components:

  1. I/O modules with multi-protocol implementation including open source, proprietary and wireless
  2. Controllers with multi-control loop implementation such as PID, Adaptive, Rule-Based and software based on multiple platforms like TIFreescaleQualcommNVidia
  3. Data storage & analytics with diverse DBMS like SQL, Mongo DB, Oracle along with varied Data Analytics through Sensor Data, Statistical modelling, Predictive analytics, and Real-time Analytics
  4. Dashboards & Apps with web-based or mobile-based Intuitive dashboards for data monitoring and apps for various OS and devices
  5. Gateways that enable communication of data between the above four data sources using communication protocols specific to each other

In building automation, connectivity technologies have propelled the adoption of connected smart devices for remote sensing, actuating and intelligent monitoring. Industry bodies and standards like BACnet International, Echelon Corporation, are extending or adopting different communication protocols to devices used in building automation, smart grid, etc. to make disparate solutions work seamlessly together. BACnet, Lonworks & other similar protocols have enabled standardization in Building automation. Different systems like HVAC, surveillance camera, access control, BMS, fire protection, audio-visual, lighting are integrated, monitored & controlled on a single system.

The Universal Gateway or Universal Protocol Gateway is an external, high-performance, multiprotocol gateway for integrating HVAC, surveillance camera, access control, fire protection controls into building management systems (BMS) & in turn integrating BMS into Internet of Things (IoT). These gateways also offer bidirectional data flow between devices on selected points.
Universal gateways support various standard protocols like Profibus FMS, DP-Master, DP-Slave, LonTalk, BACnet Ethernet, IP and PTP (RS232), Modbus serial, MODBUS/IP, M-Bus, EIB (European Installation bus), OPC, and many other proprietary protocols.

Benefits of custom-built universal gateways

Universal gateways are generally designed & developed to cater to the needs of mass market. Typically it caters to a limited set of protocol combinations, including a serial bus, a Fieldbus or real-time Ethernet protocols. Custom-built universal gateways provide a flexible platform for a transparent conversion of building automation / industrial automation protocols, thereby enabling connection of networks of different I/O, Controllers and OEM brands. Such gateways are quite flexible, with hundreds of protocol combinations possible through them.

In addition, custom-built universal gateways are software-focused and offer ease of configuration for protocols like CAN, DeviceNet, PROFIBUS, BACnet, LonTalk, Ethernet/IP, Modbus TCP, POWERLINK, CC-Link, EtherCAT, SERCOS III, MB/RTU, RS422, RS485, MB ASCII RS232, Controller Area Network, DeviceNet, FOUNDATION fieldbus, HART, C-Bus, Z-Wave, Zigbee and the like. In summary, use of universal gateways help in developing M2M communication and can aid in enabling IoT efficiently.

Originally Published on eInfochips Blogs

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IIoT protocols for the beginners

We all know HTTP (hypertext transfer protocol). These are the first 4 alphabets which see on any URL of a website you open in your browser. In simple terms, it is a list of rules that define do’s and don’ts of communication between web browser and web server. It is like you (web browser) going to ATM (webserver) to get some cash (request). Here the HTTP will describe the complete procedure – enter pin, amount, etc. You get your cash (result) once you follow the mentioned steps. Quite simple.

The World Wide Web (WWW) works on HTTP as it is the only protocol used there for the data transfer. However, this is not the case in the Industrial (I) IoT world. Here we have a bunch of protocols to choose depending on the type of application or so-called “use case”. The most common among them are MQTT, CoAP and of course HTTP. Before we discuss them, let us first have a look at certain networking terminologies and definitions.

Source: Pixabay

Transport layer protocols (TCP, UDP)

Transport layer protocol, as the name implies, is responsible for transportation of message or information from one computer to another. The transport of the information can be done in two ways:

  1. Connectionless protocol (UDP): This kind of protocol is preferred in cases where speed and efficiency are more important than the reliability. In this case the data is sent without establishing or waiting for a connection. This means that a bit or segment of data can get lost during transportation. A typical example of such protocol is live video streaming where sometimes bad connection results in the fragmented video. For example, imagine yourself bringing a bunch of letters to the postbox and dropping them inside. You are just dropping the letters inside the box without knowing whether they will be delivered to their recipients. This is the case with connectionless protocols. On the other hand, bringing all these letters to the post office and ordering a return receipt for them, thus ensuring their delivery, can be compared to a connection-oriented protocol.
  1. Connection-oriented protocol (TCP): Here the protocol ensures the receipt of a message at the other end without any data loss on the way, thus ensuring a reliable transport. The connection-oriented protocol needs extra overhead (discussed later) as compared to the connectionless protocol. Just like, it takes extra resources (time, money) to order a registered letter with return receipt.

Packet and Packet size 

packet contains data (payload) along with information (header) like source, destination, size etc. Just like a DHL packet that contains stuff to be shipped along with information like address, weight, dimension etc. packet size in networking, is the amount of data (in bytes) carried over the transport layer protocols.

Overhead

It is the extra information (in bytes) or features associated with the packet which ensures the reliable delivery of the data. In other terms, it is that bubble wrap foil around your shipment that is not necessarily needed but provides an extra layer of safety and reliability for a safe shipment of your parcel.

The amount of overhead associated with the packet depends on the type of transport protocol used. UDP in comparison to TCP has smaller overhead.

Bandwidth

Bandwidth is the rate (bits/MB/GB per seconds) at which the data transfer takes place. The larger the bandwidth, the more data can be transferred at a given time.

So that was a crash course on networking. Now let us try to understand the mentioned IIoT protocols using these terminologies.

Message Queue Telemetry Transport or simply MQTT is a lightweight messaging protocol for industrial and mobile applications. It is best suited for application where network bandwidth and power usage are limited, for example, small sensor, remote location applications, machine to machine communication. MQTT communicates with a server over TCP and unlike HTTP works on publish subscriber model (see figure below).

 

Fig. Example of a publish subscriber model used in MQTT

In order to understand the concept behind the MQTT, one should try to understand the underlying architecture “The publish-subscriber model”. Here a client publishes a message or a topic (temperature, humidity) to a broker that in turn sends these topics out to clients interested in subscribing to that message.

 

The publish subscriber model used in MQTT offers a couple of advantages as compared to the standard client-server model used in HTTP. Multicast, scalability and low power consumption are among the top three. These advantages are due to the fact that the publish-subscriber model overcomes some of the structural (one to one communication, tight coupling, fault sensitive) drawbacks of the traditional client-server model.

Let’s have a look at an analogy in order to understand the difference. Let us assume that MQTT and HTTP are two publishing companies: MQTT publishes magazines on various topics (sports, politics, cars, etc.) and provides them to a broker who in turn distributes them to subscribers interested in one or more topics. This way MQTT can cater many (multicast) subscribers at a given time, thus it is scalable. Since he only has to deal with a broker whom he contacts once a day, his investment (power consumption) in maintaining the business is not high.

 

HTTP, another publisher, likes to deal with one customer at a time. He highly relies on his customer and on his value chain (server to server). This, however, comes at a cost of relatively high business investment (power consumption) since he has to visit his customer each time for a handshake.

 

MQTT in contrast to HTTP is best suited for an application where bandwidth, packet size and power are at a premium. An industry generator with battery-powered temperature and humidity sensor cannot afford to maintain a connection with server each time it has to push the measured values (event or message) into the cloud. MQTT is just designed to overcome such constraints where the connection is maintained by using a very little power and the commands and events can be received with as little as 2 bytes of overhead (extra resources needed for operation).

 

Constrained Application Protocol or simply CoAP, is a UDP based protocol, which is mostly interpreted as a light version of HTTP (except the fact that HTTP works over TCP). It is specially designed to work in a constrained environment with limited bandwidth and power constraints, where communication has to be fast and ongoing. Unlike HTTP, CoAP can support one to many (multicast) requirements and is faster than other TCP based protocols which makes it a good choice for M2M.

 

It is quite common to see the device to device (D2D) or device to gateway (D2G) communication done over CoAP and the communication between gateway and cloud is HTTP job. This is due to the fact that there is a well-defined mapping between these two protocols.

So, if both MQTT and CoAP are good for the constrained environment, then what makes one better than another? The answer lies in the underlying transport layer their use. MQTT is better suited for event-based communication in a constrained environment where data needs to be sent in batches (for instance temperature and humidity values) and at regular intervals over a reliable channel.

CoAP is a better choice for continuous conditioning monitoring scenario in a constrained environment. Since it runs over UDP, CoAP offers faster communication among the devices which makes it a better option for M2M/D2D/D2G communication. CoAP is also best suited for web-based IIoT application where it has to work along with HTTP. In such a setup, you have CoAP at sensor side and HTTP running between proxy/gateway and cloud.

What about HTTP? It is on demand whenever you want to push a big chunk of data from gateway/industry modem/computer into the cloud or a web-based application without compromising on security. Here regardless of how data is collected and sent to a gateway (CoAP vs MQTT) if it comes to reliable big package delivery, then HTTP takes the front seat. Moreover, HTTP is still used as a standard protocol for devices who do not support any other protocols.

MQTT or CoAP or HTTP, it is a matter of speed vs reliability vs security, whichever suits your use case the best.

I hope you enjoyed reading the article and that it helped you to get at least a basic understanding of the major IIoT protocols. Your feedback, comments or suggestions are always welcome.

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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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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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The Information Value Chain

Why do IoT Architects need to think about value, not just data?

Several years ago I was pitching what would now be called an Industrial Internet of Things (IIoT) solution to the Production Manager of a large manufacturing plant. After describing all the data we could collect, and the metrics we could turn it into, I thought I had done pretty well. What Production Manager wouldn't want our system to get his finger on the pulse of his operation?

Instead, his next question floored me:

"If I don't do anything with the data your system collects, then it doesn't create any value for me, does it?"

I had never imagined that someone presented with real-time, detailed information wouldn't immediately grab it and use it to improve their business. I was so taken aback I could not think of an intelligent response, and needless to say, we didn't win that deal.

I'm not going to suggest that he was right, since "doing something with the data" was implicit in his job description, but there is a germ of wisdom for the IoT community in what he said:

Merely delivering data does not deliver value.

Even lots of accurate data, even in real time. Many IoT systems -- still -- have clearly been designed under the assumption that their responsibility ends at collecting, storing and presenting data: systems where data is collected and put in a data repository or historian; systems where data is collected an put on on-line graphs.

A real-world ACTION that benefits a group of stakeholders is still the only way that any IT system delivers value. For an IoT system to deliver that value, it must construct a chain from data to action. I suggest we call this chain:

The Information Value Chain.

The Information Value Chain is only just starting when you collect the data. Turning that data into information and ultimately into ACTION is harder, and if anything your "data only" Internet of Things (IoT) system has made the problem worse, not better: understanding a small amount of data to turn it into action is extremely taxing, and takes many different skills. Doing that with a torrent of data is overwhelming.

What is the Information Value Chain?

Very simply, the Information Value Chain is the insight that data only creates value if it goes through a series of steps, steps which eventually result in action back in the real world.

Like so:

If we focus primarily on collecting data, then we will create Data Lakes, which are impressive Information Technology constructs, but on their own are passive entities that deliver no inherent value to the organisation.

If we focus primarily on action, then we will make decisions based on inaccurate information and misleading data, resulting in the wrong action, wasted money and lost opportunity. A great example is this Case Study.

How to solve this conundrum? Before we get into the mechanics of building a robust Information Value Chain, the starting point is human, not technological.

To succeed you must start with the right goal

The starting point is this: What is the motivation for your project?

If it is to build an "IoT System," then I suggest that you are heading down the road to failure. An IoT System is a means, not an end, and has as many different embodiments as the word vehicle - Ferrari; Ford Focus; Mack truck; oil tanker.

Here is what you should be setting as your goal:

"To build a system that creates value in [this] way; by enabling [these] actions; using the best methods; with the minimal required human intervention; based on the best possible information; in as close to real time as possible."

There is a lot in this statement. Let's unpack it.

The central message of the Information Value Chain is to see our information systems as part of a sequence who's end result is action that delivers value.

  1. When I approach systems analysis for a Customer, the first thing I write on the right hand side of the whiteboard is a "$" sign.
  2. To the left I have the Customer help me develop an ROI model:
    • Before: X1 action by X2 participant creates X3 value at X4 cost;
    • After: Y1 action by Y2 participant creates Y3 value at Y4 cost.
  3. Then we step left again to describe the decisions that lead to those actions. Now we can write:
    • Who (or what!) will make those decisions; on
    • What timescale;
    • Based on what algorithm.
  4. Now we can ask what information they will need to make these decision and
    • How to extract this information from the data available.
  5. Then, and only then, do we know what data to collect; how to process it, how -- or whether -- to present it; and how much of it and how to store it.

We have found this approach moves IoT from a vague concept of something the Client thinks "maybe" they should do, but are not clear on how it will impact their business, to a compelling business tool with clear purpose and value. That what this is all about!

What do the links in The Information Value Chain mean?

The terms data, information and decision, as well as knowledge and intelligence get thrown around a lot, often interchangeably, yet these are distinct concepts. It is important to understand what we are talking about so that we can define and deliver each link in the chain successfully. Let's start from right to left, as we have just described in our systems analysis process so that we always keep our end goal in mind:

  • Action: something that results in a change in the real-world which has a $ measurable value to a key stakeholder;
  • Decision: a choice between possible Actions made according to a set of rules that maximize the value of the action taken;
  • Information: Data interpreted in a specific context to best support the Decisions the User needs to be able to make;
  • Data: individual facts collected from the Real World environment, as accurately and as timely as possible, not all of which will be relevant to the Decisions to be made;
  • Real World: The totality of systems, machines, people and environmental factors that can affect the right Action to take in any given circumstance.

How do we turn The Information Value Chain into practice?

The Information Value Chain is a great conceptual framework to think about how to get from Data to Value, but as IoT system architects, we are concerned with the practical question of how to deliver Value from Data. This is the purpose of the 5D IoT Architecture, which maps the links in The Information Value Chain to 4 specific architectural components, suggests core requirements for each of those components, and adds a 5th component to continuously improve the solution itself.

This paper is the development of a series on concepts in Big Data, IoT and systems architecture originally published on Fraysen Systems.

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