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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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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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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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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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Believe it or not, but the possibilities that the Internet of Things, IoT brings to the table are countless. The internet of things, IoT continues to be the next big thing in technology, and now the new phase of the internet of things is pushing everyone hard to ask questions about the data collected by sensors and devices of IoT.  

Undoubtedly, the internet of things, IoT will generate a tsunami of data, with the swift expansion of sensors and devices connected to the IoT. The sheer volume of data being produced by the internet of things will rise exponentially in the upcoming years. This generated data can provide extremely valuable insight to figure out what’s working well and what’s not. Moreover, the internet of things, IoT, will point out the issues that often arise and provide meaningful and actionable insight into new business opportunities and potential risks as correlations and associations are made. 

Examples of IoT Data:  

  • Data that improves productivity of industries through predictive maintenance of equipment and machinery 
  • Data that assists smart cities in predicting crime rates and accidents   
  • Data that creates truly smart living homes with connected devices    
  • Data that provides doctors real-time insight into information from biochips to pacemakers 
  • Data that gives critical communication between self-driven automobiles          

That’s great news, but it’s not possible for humans to monitor, analyze and understand all of this data using traditional methods. Even if they reduce the sample size, it will simply consume too much of their time.  Undoubtedly, finding actionable insights in terabytes of machine data is not a cakewalk, just ask a data scientist. The biggest challenge is to find ways to analyze the deluge of performance data and information that the internet of things, IoT devices creates. The only possible way to keep up with the terabytes of data generated by IoT devices and sensors and gain the hidden insights that it holds is using Artificial Intelligence, commonly known as AI.  

Artificial Intelligence (AI) and IoT    

Artificial intelligence, also known as machine intelligence (MI) is the intelligence that is exhibited by machines or software. John McCarthy, the person who coined this terminology back in 1955, describes it as "the science and engineering of making intelligent machines". In a nutshell, AI is a branch of computer science that emphasizes the creation of an intelligent machine that thinks intelligently, the way intelligent humans think and works and reacts like humans.   

In an IoT environment, Artificial Intelligence (AI) can aid business enterprises take the billions of data points they have and prune them down to what’s really helpful and actionable. The general principle is akin to that in retail applications i.e. review and analyze the data you have collected from different sources to find out similarities or patterns, so that better business decisions can be made.  

To be able to figure out the potential risks or problems, the collected data has to be analyzed in terms of what’s normal and what’s not. Abnormalities, correlations, and similarities need to be identified based on the real-time streams of data generated. The collected data combined with Artificial Intelligence makes life easier with predictive analytics, intelligent automation, and proactive intervention. 

Artificial Intelligence in IoT Applications  

  • New sensors will enable computers and smart devices to “hear,” gather sonic information about the user’s ambience   
  • Visual big data will allow computers and smart devices to gain a deeper insight of images on the screen, with the new AI app that understands the context of images

These are some of the promising applications of Artificial Intelligence in the internet of things, IoT ecosystem. The potential for highly personalized services are countless and will dramatically change the way people live. For example, Amazon.com can suggest what other books and movies you may like, helping Saavn and Gaana to determine what other songs you may love listening, and your family doctor would receive notification if you’re not feeling comfortable.  

Here Are Some Challenges Facing AI in IoT

  • Artificial Stupidity
  • Complexity
  • Safety
  • Ethical and legal Issues
  • Compatibility
  • Privacy/Security 

What’s Next? 

Gartner has predicted that by the end of next year, 6 billion connected devices will be requesting support, which means that processes, technologies, and strategies will have to be in place to respond to them. It is important to think of connected devices less as ‘things’, but more as customers or consumers of services in themselves. The need for Artificial intelligence, AI will become more prominent at the stage when the number of connected devices and sensors increase manifold.

Hope you find this post helpful. If you did, share it with your friends and colleagues. For AI and IoT Courses Online, you can do some research on Google to find the best institute that suits your needs and budget.

For any query related to this post, you can comment down below. Thanks for your time. 

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The other day we were discussing and debating on a solution to be designed to meet the sensing needs for access, temperature and humidity for some devices with form part of a networking infrastructure ecosystem. The idea was to build a IoT based system for monitoring and control.

The design discussions veered around the ability to collect data from the sensors and the types of short range communication protocols which could be deployed .Questions and clarification were raised if we were compliant to use short range communication protocols in sensitive areas as customer Data Centres which are like owned and  that they may be custodians of data of their end customers .

The hidden perils of data acquisition and data ownership reared its head which needed to be addressed as we moved forward .

The data which is acquired by sensors is essentially Machine Generated Data (MGD) .This post will  dwell on the subject of data ownership of MGD as follows :

  1. Sensors ( Data Acquisition and Communication )
  2. Machine Generated Data
  3. The Lifecycle of the MGD and the Ownership Paradigm
  4. Who should be the owner of the MGD?
  5. Sensors (Data Acquisition and Communication):

In the IoT ecosystem, the physical computing frontier is managed by the Sensors .Sensors essentially include three fundamental functions:

  • The act of sensing and acquiring the data
  • Communication of the data through appropriate protocols to communicate their readings to internet cloud services for further aggregation and trend analysis
  • The activity is energised by power supply,

The additional functions would include processing/system management and user interface

The Digital Computing part comprises the IoT application. This   is determined by the types of sensors, cloud connectivity, power sources, and (optionally) user interface used in an IoT sensor device. The following diagram showcases the primacy of sensors in a typical IoT Ecosystem.

When making physical measurements such as temperature, strain, or pressure, we need a sensor to convert the physical properties into an electrical signal, usually voltage. Then, the signal must be converted to the proper amplitude and filtered for noise before being digitized, displayed, stored, or used to make a decision. Data-acquisition systems use ADCs (analog-to-digital converters) to digitize the signals with adequate signal conditioning.

Sensor data communication to the cloud can be done in multiple ways from wireline to wireless communication of various complexities. While wire line communication has some important benefits (such as reliability, privacy, and power delivery over the same wires), wireless communication is the technology that is the key catalyst in the majority of IoT applications that were not previously practical with wired systems. Reliability, channel security, long range, low power consumption, ease of use, and low cost are now reaching new levels, previously thought infeasible

Some examples of recently popular IoT wireless communication types: Wi-Fi, Bluetooth Low Energy (aka Smart), Zigbee (and other mesh 802.15.4 variants), cellular, LPWA (Low-Power, Wide-Area network variants: Ingenu, LoRaWAN, Sigfox, NB-LTE, Weightless), and Iridium satellite.

  1. Machine Generated Data (MGD)  :

Sensor data is the integral component of the increasing reality of the Internet of Things (IoT) environment. With IpV6 , anything can be outfitted with a unique ip address with  the capacity to transfer data over a network. Sensor data  is essentially Machine Generated Data . MGD is that is produced entirely by devices / machines though an event or observation.

Here we would define human-generated data, what is recorded is the direct result of human choices. Examples are buying on the web, making an inquiry, filling in a form , making payments with corresponding updates on database. We would not consider the ownership of this data in the post and would be limiting our post to MGD.

  1. The journey of the MCD and the Ownership Paradigm:

The different phases exist in the typical  journey of Machine Generated Data .

Capture and Acquisition of Data– This is a machine or a device based function through signal reception.

Processing and Synthesis of the Data – This is a function which ensures enrichment and integration of Data

Publication of the Data – This is done by expert systems and analysts who work on exception management , triggers and trends .

Usage of Data – The action which need to be taken on the processed and reported information is used by the end user .

Archival and Purging of Data – This function is essentially done by the data maintenance team with supervision.

Now let us dwell on the Ownership Paradigms .They range from the origination of data , adding value to the data through make over , monetising of data through insights generated. Interestingly, let us explore if there is any conclusive method for determining how ownership should be assigned. A number of players may be involved in the journey of the data (e.g. the user, hardware manufacturer, application developer, provider of database architecture and the purchaser of data, each having an equal lay of the claim in different stages of this journey )

  1. Who should be the owner of MGD :

Let me share the multiple and conflicting views  :

  1. The owner of the device which records Data .In essence, the owner of machine-generated data(MGD), is the entity who holds title to the device that recordw the data. In other words, the entity that owns the IoT device also owns the data produced by that device.

But there could be a  lack of clarity if the device is leased rather than owned.. When real-world constructs such as lease holdings of (say servers) come into play, it indeed gets complex and even murky.

  1. Who should be the owner of MGD :

Let me share the multiple and conflicting views  :

The owner of the device which records Data .In essence, the owner of machine-generated data(MGD), is the entity who holds title to the device that recordw the data. In other words, the entity that owns the IoT device also owns the data produced by that device.

But there could be a  lack of clarity if the device is leased rather than owned.. When real-world constructs such as lease holdings of (say servers) come into play, it indeed gets complex and even murky.

The owner is the user of the Data :The other dimension is data may be owned by one party and controlled by another. Possession of data does not necessarily equate to title. Through possession there is control. Title is ownership. Referred to as usage rights, each time data sets are copied, recopied and transmitted, control of the data follows it. There could be cases where the owner of the device could be the user of the data.

 The maker of the Database who essentially invests in aggregating, processing and making the data usable is the owner of the Data :This has a number of buyers of this paradigm . The owner of a smart thermostat does not, for example, own the data about how he uses it. The only thing that is ‘ownable’ is an aggregation or collection of such data provided there has been a relevant investment in carrying out that aggregation or collection (the individual user is very unlikely to have made that investment). The owner here could be the Home automation company . The value which could be generated though this investment could be producing market intelligence , exploiting the insights form data to build market presence and differentiation ,

The purchaser of Data could be the owner of the Data: An auto insurance company could buy the  vehicle generated data ( from the makers of automobiles )  and could design a product for  targeted offerings to specific market segments based on say driving behaviour patterns  and  demographics  .This may not be as easy as this seems – refer the url  :  http://joebarkai.com/who-owns-car-data/ which states that the owner of the vehicle and not the maker of the car owns the data collected from the electronic data recorder .

The value chain of who owns the data can be a complex one with multiple claimants . As one aggregates more sources it just gets more complicated. A good example is in the making of smart cities. The sources of data can be from multiple layers and operational areas . City authorities would be making the effort to make use of the data in areas of waste management , traffic congestion , air pollution etc . So does the city authority own the data?

My personal take is , if someone in the MGD value chain  is making the data usable for  a larger good , and  in the process may monetize the data to cover the investments , that entity deserves to  be the owner of the data  as that is where value is generated .


Posted on August 14, 2017

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In the United States, precision agriculture is one of the largest industries by both operational scale and economic impact. The technology utilized is typically on the cutting edge, especially for automation and control. Things like sensors, programmable IoT radios and generally more complex software applications have allowed that industry to evolve, domestically, to a point where land and other resources are used optimally. Internationally, although there have been ‘smart’ or ‘precision’ practices in certain sectors of agriculture, many countries are just now starting to adopt the technology to its fullest extent, including the ability to innovate via start-ups and new practices.

India & the Digital Agriculture Revolution

According to an article in India Times (image credit), the country is aiming to secure a 20 percent stake in the IoT market share in the next five years through its ‘Digital India’ initiative. While many might look at India and think of the sprawling and diverse urban environments that could offer some potential complications for IoT, it is rural areas seeing the most interesting developments. There has been a noticeable growth in tele-medicine operations, which can allow patients in remote areas to interact with doctors for consultation, eliminating the need to get to a city, or vice versa. Perhaps an even greater area of growth lies in the agricultural realm. According to the article, agriculture employs 50 percent of the country’s population, so the potential for a digital revolution is high. Farmers are just starting to implement sensor technology, automation hardware, and even leading-edge tools like voluntary milking systems the allow cows to be milked on an automated machine according to biological needs.

Israel’s Precision Ag Start-Up Community

In Israel, where IoT technology is starting to mature, the name of the game is data collection and analytics. Mobile applications, sensor data collection hardware, and advanced analytics software are three areas that Israel is seeing significant market growth, according to Israel21c:

Israel stands out in precision-ag subsectors of water management, data science, drones and sensors, says Stephane Itzigsohn, investment associate at OurCrowd. … “Multiple startups are aiming toward the same goal — providing good agricultural data — but approaching it from slightly different angles,” Itzigsohn tells ISRAEL21c. “One might use satellite images or aerial photography; another might use autonomous tractors. Not all will get to that peak in the long journey of farming becoming more efficient.”

For example, CropX, an investor-backed advanced adaptive irrigation software solution, can be placed throughout a farming area and synced with a smart phone, allowing the operators to receive real-time data updates on things like soil and weather conditions. CropX is based in both Tel Aviv and San Francisco, indicating that the technology may be poised for wide international adoption in the future.

Analytics Drive Italy’s Drought Recovery

Italy is perhaps best known for a single agricultural export: wine. However, many would be surprised to find out that it is one of the top corn producers in the European Union, producing more than 7 million tons of corn in 2015, according to an RCR Wireless report. In 2016, the EU’s total corn output dropped noticeably due to year-long droughts affecting production. In Italy, start-up companies collaborated with industrial ag operations develop and deploy widespread soil sensor and water automation technology to help streamline farming practices and create a more efficient system for resource use. The technology allowed farmers to get a comprehensive look at their operations and identify high and low yield areas in order to better utilize the available space.

Precision Agriculture and the Industrial IoT

The continued maturation of IIoT technology is enabling countries around the globe to better utilize resources like water, energy, and land area to create better agricultural operations. As populations continue to expand, and food production becomes even more important, being able to connect these technologies across the globe could become a key factor in optimizing crop output in critical areas. Imagine the above farm in Italy being able to send its data to data scientists in Germany or the Eastern Europe who could in turn analyze it and provide actionable feedback. Or an industrial farm in Israel managing its yields sending that information in real-time around the country. These possibilities are not far off, and as the networks, hardware and software continue to be adapted, the future of precision ag internationally, will become the present.

For additional reading:

India Times: http://www.indiatimes.com/news/india/how-the-internet-of-things-is-digitizing-agriculture-speeding-up-rural-development-in-india-326546.html

Israel 21c: https://www.israel21c.org/5-israeli-precision-ag-technologies-making-farms-smarter/

RCRWireless: http://www.rcrwireless.com/20161005/big-data-analytics/precision-agriculture-omica-tag31-tag99

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Building a system to get value from the Internet of Things (IoT) or Industrial Internet of Things (IIoT) is a complex process involving a number of very distinct components. We need an Architecture for IoT to define the components which are necessary and sufficient for the system to deliver value. An information system only delivers value if it completes the Information Value Chain, causing real-world action to take place in response to the data it collects. This is what the 5D Architecture does. Luckily, every IoT or IIoT system needs to perform the same 5 core functions in order to deliver value, and therefore the architecture of all these systems is — pleasingly — the same!
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Save IoT, Save The World

When looking for a title for this article, I remembered the famous phrase from TV serie Heroes, "Save the cheerleader,  Save the world". Sorry if one more time I abuse of shocking headlines to attract more readers. 

Is the Internet of Thing (IoT) in danger? In light of the latest events I have attended in Berlin and London and news like this "Intel To Amputate Three Modules For Internet Of Things, Including Joule", I really believe  IoT is falling into the Gartner´s Trough of Disillusionment phase  and we need IoT heroes to push it faster towards the Plateau of Productivity phase.

The other part of the article's title, "Save the World," may sound pretentious, but the world need to be save. This year hot spring and summer is confirming even the most disbelieving that Global Warming is very real (Read more at " Global Warming, Christmas and the Internet of Things" and in spite I do not consider that only IoT can save our blue planet, per recent events like "Portugal forest fire", IoT can help and much.

If we cannot control runaway pollution of our air and water, the world will end

Source: Ron Lake, Technology Evangelist at Galdos Systems Inc.

Let's go by parts.

Has the Interest in IoT Slowed Down?  Some Symptoms

The IoT no longer fills single events. Now events like Internet of Things World Europe 2017 or IoT Tech Expo Europe in Berlin need help from other technologies like AR/VR AI, Blockchain, or 5G to attract exhibitors and visitors.

The heroes of IoT have lost their past evangelizing enthusiasm. What IoT heroes need to do?

  • The IoT Industry heroes need to focus on Customer Value. It is important that IoT heroes address real pain points rather than creating something gimmicky.
  • IoT Heroes can not do it alone, partnership with other heroes are absolutely essential for success in the Internet of Things.
  • IoT heroes need to be more creative with new Use Cases. As sensors continue to decrease in cost and IoT-specific networks get rolled out, everybody expect the number of use cases to increase exponentially.
  • Raise awareness about the major concern, IoT Security
  • IoT heroes should follow the trends by pairing connectivity with AI/Blockchain/AR/VR heroes

How can IoT save us from world challenges?

Gary Atkinson, Director of Emerging Technologies at ARM, identifies five main challenges that the planet is heading towards:

1.       We’re running out of agricultural land

2.       Water is our rarest commodity

3.       Energy needs to be cheaper to be efficient. 

4.       Healthcare is a growing problem

5.       Transport - Everyone will be able to afford cars, but won’t be able to afford to pay for fuel.

Save IoT, Save Agricultural land

If we all expect that IoT Agricultural solutions will be cheap, will have a long-lasting battery (+10 years), and will emit signals at least 5 miles, the smart farming will be a reality and we will not have excuses to save agricultural land.

Additional info:

Save IoT, Save the Water

Water is currently the most precious natural resource on planet Earth.

On the occasion of World Water Day, tech giant IBM entered into a pact with Ireland’s Dublin City University for a collaborative R&D pilot to leverage the internet of things (IoT) technology to help protect water.

The IoT could for instance make desalinisation coming to a cost-effectiveness point. India uses mostly a pivot irrigation system, which means 30% of land is lost and 50 to 60% of water is lost by evaporation. The switch to tape based irrigation could save 2/3 of the water used.

Back in 2014, HydroPoint Data Systems utilised the Internet of Things (IoT) to help with water conservation efforts. According to the company and its partners, this system saved local people some $137m in expenses and 15 billion gallons of water in the first year alone.

Additional info:

Save IoT, Make Energy renewable and cheaper

Smarter, more efficient energy consumption it’s been the dream of environmentalists for decades. Now, it’s possible through the power of Internet of Things devices. Because of their connection capabilities, energy consumption such as the power in a commercial building or even smart home can be constantly monitored and adjusted.

Energy consumption could be reduced thanks to a smarter consumption and the implementation of micro generation storage. Knowing that lightning is the second biggest consumer of energy (after motors), and that there are about 1 billion streetlights in the world, upgrading streetlights infrastructure would strongly impact the world consumption.

Experts said that thanks to the Internet of Things, we can move from about 13 percent aggregate energy efficiency to 40 percent in the next 25 to 30 years.

Creating a new connected economy powered by renewable energy will cause a temporary surge in productivity worldwide as grids are modernized and infrastructure is rolled out. Installing wind and solar is labor intensive, for example, so for two generations, people will have plenty of work to do.

Additional info:

IoT company SkyGrid which is based in Melbourne and Sydney, is developing a smart hot-water system in partnership with hot-water company Quantum Energy. The aim is to intelligently control when a building’s hot-water systems are switched on, so that energy isn’t wasted heating water when no one is around to use it – something that currently wastes as much as 50% of a system’s power.

  • EnLight works on streetlight efficiency
  • Freestyle has partnered with engineering firm PowerTec, on an intelligent energy grid for Kangaroo Island in South Australia. Sensors and controllers in the grid intelligently manage energy sources to sway energy consumption towards renewables without sacrificing the reliability of the supply.
  • Top 10 Internet of Things Companies Disrupting the Energy Industry -
    • PingThings is combining big data and machine learning to change the way that state utility grids operate.
    • Actility employs IoT and machine-to-machine (M2M) communication to reinvent the way the energy sector operates.
    • Tibber is a personal assistant that can regulate a house’s energy consumption and buy more energy if the need arises.
    • Wattz is implementing solar power solutions that rely not on the sun’s light, but capturing ambient light from LED and compact fluorescent bulbs to recharge the batteries in IoT devices.
    • Positive Energy uses IoT devices and software to optimize the functional efficiency of industrial buildings and smart homes alike. 
    • Smappee allows users to turn devices on and off remotely. It also has the capability to monitor solar panel output values and gas and water usage in real-time.
    • GasZen allows customers to convert their traditional “dumb,” or non-networked, propane tanks into smart tanks that can be monitored by both the gas provider and the user remotely. 
    • 75Farenheit, beyond their ability to predict and adapt to changing climates, they offer analytics and suggestions on how to make the operation of a building more efficient.
    • Inspire Energy is giving citizens the power to become a part of the growing clean energy movement.
    • Verdigris Technologies primary target is energy consumption and waste.

Save IoT, Save Healthcare

Despite incredible improvements in health since 1950, there are still a number of challenges, which should have been easy to solve.

In a 2016 report by Deloitte we can read “Change is the new normal for the global health care sector. As providers, payers, governments, and other stakeholders strive to deliver effective, efficient, and equitable care, they do so in an ecosystem that is undergoing a dramatic and fundamental shift in business, clinical, and operating models. This shift is being fueled by aging and growing populations; the proliferation of chronic diseases; heightened focus on care quality and value; evolving financial and quality regulations; informed and empowered consumers; and innovative treatments and technologies — all of which are leading to rising costs and an increase in spending levels for care provision, infrastructure improvements, and technology innovations.”

The IoT has brought many exciting advances to healthcare, improving patient experiences, increasing the quality of care provided, as well as updating and streamlining healthcare operations. From digital assistants to ‘smart’ medicine bottles, a new wave of connected devices could help people live independently for longer.

According with Goldman Sachs, IoT functions would produce an estimated $32.4 billion in annual revenue (45% from remote patient monitoring, 37% from telehealth, and 18% from behavior modification). But Healthcare IoT not only increases revenue, IoT reduces this cost by offering a more cost-effective method of managing chronic illness. The $305 billion estimated savings is accounted for by a combination of chronic disease management and telehealth.

Additional info:

Save IoT, Save Transportation 

I leave this topic for a special post in the coming months.

Key Takeaway: Save IoT and IoT will enable Save the World

As I have commented many times the IoT is a Journey. Those who have been more time in the race know that there are easier and other more difficult stages, but not for that reason we abandon the hardness of climbing one of them.

 If we have not yet achieved that the IoT has a unique definition, it is not surprising that the term could disappear for reasons of business marketing. Nor does it matter that technologies such as AI, VR / AR, Robots, Blockchain, join to IoT to solve world problems. We could call it "Unified Information Technology".

The World of 2017 has some immense problems but It is scary to think about the challenges it for the next 10, 20 50 years. As we have seen IoT must play an important Enabler to Save the World. 

IoT heroes, save the IoT, Save the World.

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For all the value and disruptive potential that Internet of Things (IoT) solutions provide, corporate buyers face a dilemma. Today’s IoT technologies are still immature point solutions that address emerging use cases with evolving technology standards. Buyers are concerned that what they buy today may become functionally or technologically obsolete tomorrow. Faced with this dilemma, many defer buying even if the IoT solutions they buy today offer tremendous value to their organizations.

This post describes a planning strategy called “future-proofing” that helps managers, buyers, and planners deal with obsolescence.

What causes IoT solution obsolescence?

An IoT solution, whether you buy it now or in the future, can become functionally obsolete for several reasons, as described in Figure One.  Unlike more established technologies, today’s immature and fast evolving nature of IoT solutions, amplifies the risk of early obsolescence.

For example, today there are multiple Low Power Wide Area Network (LPWAN) connectivity options – SigFox, LoRa, RPMA (by Ingenu), Symphony Link (by Link Labs), NB-IoT and LTE-M. While each option has advantages and disadvantages, a subset of these will eventually “win” out as technology standards, business models and use cases emerge.

Similarly, there are 350+ IoT platforms in the marketplace today (source: “Current state of the 360+ platforms”, IoT Analytics, June 9, 2016). While many of these platforms target specific applications and industry segments, consolidation is inevitable as there are more vendors than the market can eventually support. The major IoT platform vendors (Amazon, Microsoft, Google, IBM, GE, et al), currently on a market share land grab, will drive consolidation when they begin to acquire select vertical platforms to gain rapid access to those markets.

What is Future-Proofing?

According to Collins English Dictionary (10th edition), “future-proof” is defined as:

“protected from consequences in the future, esp. pertaining to a technology that protect it from early obsolescence”

Because of the high cost of enterprise technologies, many buyers perceive obsolescence as bad. To them, future-proofing means keeping the technology as long as possible in order to minimize costs and maximize return on investment (ROI). Their companies have standardized their business processes, policies and even their technical support on the technologies that they have bought. When a solution goes End of Life (EOL) and transitions to a newer version, it means that managers will have to recertify and retrain everyone on the “new” solution all over again. In general, transitions happen over a period of months (and sometimes years) in large global companies. During this time, multiple generations of the solution will co-exist, with each requiring different processes and policies.

In today’s fast moving IoT market, planned and unplanned obsolescence will be the norm for the foreseeable future. The traditional concept of “future-proofing” doesn’t apply, and can lead to significant, adverse business disruption.

In the era of cloud based solutions and IoT, future-proofing is not about outguessing the future, and choosing the “right” solution so as to never have to “buy” again. Nor is it overbuying technology now to avoid buying in the future. Finally, future-proofing is not about avoiding change. Future-proofing is a solution lifecycle management strategy. It is a continuous process to maximize solution flexibility and options, while making deliberate choices and managing risk.

What does a future-proof IoT infrastructure look like?

In planning the future-proofed IoT infrastructure, managers must first understand its key characteristics, and then define specific requirements for each of those characteristics. At a high level, these characteristics include:

  • Usable– the infrastructure and solutions achieve all functional needs with no loss in performance, security, service level agreements (SLA) over the desired time period.

  • Scalable – supports future needs, applications, devices

  • Supportable – resolves technical, performance, reliability, SLA issues

  • Changeable – addresses “lock-in” and facilitates migration to updated solutions on your schedule based on your needs

  • Economical – the total cost of ownership of the solution stays within forecasted ranges

A framework for future-proofing your IoT infrastructure

Change is constant and cannot be avoided. The driving principle behind future-proofing is managing change, not avoiding or preventing it. This principle recognizes that every solution has a useful functional life, and that what is functionally useful today may be obsolete and discarded tomorrow.

A properly designed future-proof plan provides the organization with options and flexibility, rather than lock-in and risk. It prevents suboptimal decision-making by managing the infrastructure on a system level, rather than at the individual component level.

Future-proofing your IoT infrastructure is a three step process (Figure Two). It is not a “once and done” exercise but must be done annually to remain relevant.

Plan and Design

The first step of the future-proofing process is to identify and place the various IoT infrastructure, systems and solutions into one of nine actionable categories. These categories are shown in Figure Three. The horizontal rows represent the “change” category, while the vertical columns represent the timeframe decision timeframe.

The actual classification of the IoT infrastructure solutions into one of the categories is determined in conjunction with IT, operations and the business units. Key considerations for determining the “future-proof category” include:

  • Usability/functionality – functional utility, compliance with standards, performance against needs, SLAs, and performance

  • Scalability – ability to meet current and future needs, anticipated change in standards

  • Support – resources, expertise, reliability

  • Ease of transition –contractual agreements, technology interdependence/dependence, specialized skills

  • Economics – maintenance costs, licensing/content/subscription fees, utilities, new replacement costs, transition costs

Source and Build

Once the proper categorization is completed, the second step is to procure the necessary solutions, whether they are hardware or software. This requires that a sourcing strategy be put into place over the desired time period. The terms sourcing and buying are sometimes used interchangeably, but they are not the same. Sourcing is about ensuring strategic access to supply while buying is more transactional. In executing the future-proofing plan, procurement managers must understand the supplier product lifecycle, and develop specific tactics.

As an example, a large global company decides to standardize around a specific IoT edge device (and specific generation) and technology for the next five years. In order to maintain access to this supply during this time period, it employs a number of tactics, including:

  • Stocking of spare units to be deployed in the future

  • Placing large “Last time” orders before that version of the solution is discontinued

  • Sourcing refurbished versions of the technology

  • Incorporating leasing as sourcing strategy

  • Negotiating contractual arrangements with the vendor to continue the solution line

Support and Monitor

The third step in the future-proofing strategy is to keep the IoT infrastructure and solutions operational over the desired time period. This is relatively easy when the solutions and technologies are being serviced and supported by the vendors. However, as vendors transition to newer technology and solution versions, buyers may find limited support and expertise. This problem is amplified the further you are from the original end-of-life date.

To keep the infrastructure and solutions fully operational during this time, companies must employ various reactive and proactive tactics. Some of these include:

  • Incorporating and installing vendor firmware updates to maximize functionality, apply bug fixes and extend useful life. Vendors may issue firmware updates on both End of Life and current generation solutions.

  • Purchase warranty and extended warranty and maintenance service contracts to assure access to support

  • Develop in-house maintenance and repair capability

  • Negotiate special one-off engineering support services with the vendor or their designated contractors

About:

Benson Chan is an innovation catalyst at Strategy of Things, helping companies transform the Internet of Things into the Innovation of Things through its innovation laboratory, research analyst, consulting and acceleration (execution) services. He has over 25 years of scaling innovative businesses and bringing innovations to market for Fortune 500 and start-up companies. Benson shares his deep experiences in strategy, business development, marketing, product management, engineering and operations management to help IoTCentral readers address strategic and practical IoT issues.

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An accurate and well-structured security analysis is the key for a holistic security concept and therefore for a secure product. But planing and performing a security analysis can be a hard nut to crack. After collecting experience in more than 6 big IoT projects over the last 2 years I decided to share some key facts that can make your life easier if you have to go the same way.
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Most IoT projects today are unsuccessful

A recent Cisco survey of 1845 business and IT decision-makers in mid market and enterprise companies, conducted in April 2017, found that nearly three quarters of Internet of Things (IoT) projects were not successful.

The top five reasons include:

  • Long completion times,
  • Poor quality of the data collected,
  • Lack of internal expertise,
  • IoT integration,
  • Budget overruns.

These results are not surprising given the immaturity of the IoT solutions, evolving technology standards, and limited expertise among the IoT community.

In light of these survey results, how do you ensure that your first IoT project implementation will be successful? In this post, I’ll share ten best practices for managers planning their first IoT project.

Best Practices for IoT Projects

Best Practice #1 – Solve a problem that someone cares about. Whether it’s a pilot project, or a mini IoT project added to a larger non-IoT project, make the project relevant by addressing a real need. This ensures visibility and support from the organization, whether it is something as simple as time to answer your questions, commitment from management, or contribute resources. Equally important, it gives you a foundation from which to build follow-on projects.

Best Practice #2 – Plan conservatively. As an early IoT adopter, your organization’s capabilities will be limited and the learning curve will be steep. Managers must plan for this in several ways. Don’t try to “change the world”, but instead focus on doing one or two things well. Define the requirements well and resist scope creep. Build in a larger than usual contingency for schedule, resources and cost.

Best Practice #3 – Fix outdated processes and policies. IoT solutions can disrupt existing organizational processes and policies. If you fix the technology but not the processes and policies, you will just get “bad news faster”. Implementing the technology side of IoT is only half the solution. Realize its full potential by updating affected, or in some cases, creating new processes and policies.

Best Practice #4 – Partner for success. IoT solutions affect multiple teams within the organization. Partner with these affected teams early in the planning process to get their requirements, gain their support (knowledge, resources, and budget), and leverage their influence to remove barriers during the execution stages. Partner with your organization’s digital transformation or innovation office, if one exists.

Equally important, partner with IoT solution vendors throughout the process. At this stage of the market, their solutions are still evolving. Work with your IoT vendor at a deeper level than you would with other vendors. Stay in close contact and leverage their product management and technical support teams throughout the project.  Co-design the solution and project with them – tell them what features you like to see, report bugs, and test updated versions of the product.

Best Practice #5 – Augment your capabilities with outside resources. Address gaps in your internal capabilities by leveraging outside resources. Build your IoT knowledge through information shared on industry blogs, publications and analyst reports. Augment your project planning and execution capabilities by contracting with subject matter experts, IoT consultants, and innovation labs.

Best Practice #6 – Address resistance to change. The more disruptive the IoT solution is, the more likely you will face adoption resistance both internally and externally. Whether the changes are small or large, ensure IoT project success with a change adoption plan early on in the project. Identify who is affected and how they are affected, then understand their objections. Craft a plan to address these objections, be transparent and communicate regularly, and implement well before the solution goes live. Be responsive and act with a sense of urgency to any concerns raised during the project.

Best Practice #7 – Define extended project success and goals. During the project planning stage, identify the key success outcomes of the project. Beyond the goals directly enabled by the IoT solution, consider goals around internal capabilities development, gaps identification (processes, policies, technologies, resources, etc.), organization readiness, channel and customer acceptance. Treat your early IoT projects as learning experiences, and use these projects to learn, experiment, uncover challenges, develop the organization and go faster on future projects.

Best Practice #8 – Drive shared ownership and accountability. IoT solutions affect multiple teams across the organization. Because of this, you must establish a structure of shared ownership and accountability to drive project success. Identify and secure the commitment of the critical executive sponsors and  business unit owners. Align the value and relevance of the IoT solution to their team’s goals and needs to drive their ownership.

Best Practice #9 – Establish a learning culture. To ensure that your subsequent IoT projects are successful, you must establish a rapid learning culture right from the start. During the project, establish a process for experimenting, prototyping and problem solving. At the end of the project, document the knowledge and expertise gained, and then develop a system to retain and transfer that knowledge. Identify who the “experts” are, the lessons learned, and project debriefs. Develop a system to share that knowledge across the organization, with solutions vendors, consultants, and other resources.

Best Practice #10 – Be flexible and adapt. Despite careful planning and risk management, your first IoT projects will still be significant learning experiences. You know what you know, but you don’t know what you don’t know. Your planning and risk management is based on what you know. Unforeseen things happen because of the things you, your consultants, or the vendors don’t know. In this type of environment, the project teams should be nimble and agile to respond to the unplanned. Incorporate larger contingencies in project plans. Prepare your sponsors and owners to expect change. Select your project team members for their ability to quickly adapt and learn, as well as for their knowledge and execution ability.

About:

Benson Chan is an innovation catalyst at Strategy of Things, helping companies transform the Internet of Things into the Innovation of Things through its innovation laboratory, research analyst, consulting and acceleration (execution) services. He has over 25 years of scaling innovative businesses and bringing innovations to market for Fortune 500 and start-up companies. Benson shares his deep experiences in strategy, business development, marketing, product management, engineering and operations management to help IoTCentral readers address strategic and practical IoT issues.

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Manufacturers seek quantifiable ROI before making leap to IIoT implementation

By now, most manufacturers have heard of the promise of the Industrial Internet of Things (IIoT).

In this bold new future of manufacturing, newly installed sensors will collect previously unavailable data on equipment, parts, inventory and even personnel that will then be shared with existing systems in an interconnected “smart” system where machines learn from other machines and executives can analyze reports based on the accumulated data.

By doing so, manufacturers can stamp out inefficiencies, eliminate bottlenecks and ultimately streamline operations to become more competitive and profitable.

However, despite the tremendous potential, there is a palpable hesitation by some in the industry to jump into the deep end of the IIoT pool.

When asked, this hesitation stems from one primary concern: If we invest in IIoT, what specific ROI can we expect and when? How will it streamline my process such that it translates into greater efficiencies and actual revenue in the short and long term?

Although it may come as a surprise, the potential return can actually be identified and quantified prior to any implementation. Furthermore, implementations can be scalable for those that want to start with “baby steps.”

In many cases, this is being facilitated by a new breed of managed service providers dedicated to IIoT that have the expertise to conduct in-plant evaluations that pinpoint a specific, achievable ROI.

These managed service providers can then implement and manage all aspects from end-to-end so manufacturers can focus on core competencies and not becoming IIoT experts. Like their IT counterparts, this can often be done on a monthly fee schedule that minimizes, or eliminates, up-front capital investment costs.


DEFINING IIOT

Despite all the fanfare for the Internet of Things, the truth is many manufacturers still have a less-than-complete understanding of what it is and how it applies to industry.

While it might appear complicated from the outside looking in, IIoT is merely a logical extension of the increasing automation and connectivity that has been a part of the plant environment for decades.

In fact, in some ways many of the component parts and pieces required already exist in a plant or are collected by more manual methods.

However, a core principle of the Industrial “Internet of Things” is to vastly supplement and improve upon the data collected through the integration of sensors in items such as products, equipment, and containers that are integral parts of the process.

In many cases, these sensors provide a tremendous wealth of critical information required to increase efficiency and streamline operations.

Armed with this new information, IIoT then seeks to facilitate machine-to-machine intelligence and interaction so that the system can learn to become more efficient based on the available data points and traffic patterns. In this way, the proverbial “left hand” now knows what the “right hand” is doing.

In addition, the mass of data collected can then be turned into reports that can be analyzed by top executives and operations personnel to provide further insights on ways to increase operational savings and revenue opportunities.

In manufacturing, the net result can impact quality control, predictive maintenance, supply chain traceability and efficiency, sustainable and green practices and even customer service.


BRINGING IT ALL TOGETHER

The difficulty, however, comes from bridging the gap between “here” and “there.”

Organizations need to do more than just collect data; it must be turned into actionable insights that increase productivity, generate savings, or uncover new income streams.

For Pacesetter, a national processor and distributor of flat rolled steel that operates processing facilities in Atlanta, Chicago and Houston, IIoT holds great promise.

“At Pacesetter, there are so many ways we can use sensors to streamline our operation, says CEO Aviva Leebow Wolmer. “I believe we need to be constantly investigating new technologies and figuring out how to integrate them into our business.”

Pacesetter has always been a trendsetter in the industry. Despite offering a commodity product, the company often takes an active role in helping its customers identify ways to streamline operations as well.

The company is currently working with Industrial Intelligence, a managed service provider that offers full, turnkey end-to-end installed IIoT solutions, to install sensors in each of its facilities to increase efficiency by using dashboards that allow management to view information in real time.

“Having access to real-time data from the sensors and being able to log in and see it to figure out the answer to a problem or question so you can make a better decision – that type of access is incredible,” says Leebow Wolmer.

She also appreciates the perspective that an outsider can bring to the table.

“Industrial Intelligence is in so many different manufacturing plants in a given year and they see different things,” explains Leebow Wolmer. “They see what works, what doesn’t, and can provide a better overall solution not just from the IIoT perspective but even best practices.”

For Pacesetter, the move to IIoT has already yielded significant returns.

In a recently completed project, Industrial Intelligence installed sensors designed to track production schedules throughout the plant. The information revealed two bottlenecks: one in which coils were not immediately ready for processing – slowing production – and another where the skids on which they are placed for shipping were often not ready.

By making the status of both coil and skids available for real time monitoring and alerting key personnel when production slowed, Pacesetter was able to push the production schedule through the existing ERP system.

This increased productivity at the Atlanta plant by 30%. Similar implementations in the other two facilities yielded similar increases in productivity.


TAKING THE FIRST STEP

According to Darren Tessitore, COO of Industrial Intelligence, the process of examining the possible ROI begins with a factory walk-through with trained expertise in manufacturing process improvement and IoT engineers that understand the back-end technologies.

A detailed analysis is then prepared, outlining the scope of the recommended IIoT implementation, exact areas and opportunities for improvement and the location of new sensors.

“The analysis gives us the ability to build the ROI,” says Tessitore. “We’re going to know exactly how much money this will make by making the changes. This takes much of the risk out of it so executives are not guessing how it might help.”

Once completed, a company like Industrial Intelligence can then provide a turnkey, end-to-end-solution.

According to Tessitore, this covers the entire gamut: all hardware and software, station monitors, etc.; the building of real-time alerts, reports & analytics; training management on how to use data points to increase profits; and even continuously monitoring and improving the system as needed.

“Unless you’re a huge company, you really don’t have somebody who can come in and guide you and create a cost effective solution to help you compete with the larger players in the space,” says Pacesetter’s Leebow Wolmer. “I think that’s what Industrial Intelligence offers that can’t be created on your own.”

“It’s not a one-size-fits-all approach,” she adds. “They have some things that can give you a little bit of IIoT or they can take an entire factory to a whole new level. By doing this they can be cost effective for a variety of sizes of organizations.”

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Not all Devices are IoT or IIoT

Introduction

Business opportunities created by Internet of Things (IoT) and the Industrial IoT (IIoT) are among the most
debated topics, as these are designed to function in a broad range of consumer and industrial applications.
Manufacturers of IoT components believe in this new trend, but many of them still not understand the essence
of the IoT concept. In reality, not every controlled device is an IoT nor IIoT.

The IoT/IIoT concept is a communication-based eco-system in which control devices, CCTV cameras and
industrial sensors communicate via the Internet with cloud-based computer systems and data sources, and
the result of this process is displayed on a computer screen, smartphone or used for optimal activation of a
process. Through an IoT/IIoT ecosystem you may boost productivity and achieve unique benefits. Examples
of IoT/IIoT include applications such as; remote operation of home appliances, medical devices, check on
availability of a product in a store, warnings of unusual conditions and malfunctions and more.

Leading market research firms already estimate that by 2020 there will be over 20 billion devices worldwide,
defined as part of IoT/IIoT systems. Although the forecasted number is growing every year, it is not clear
whether these figures correctly refer to what can be and what cannot be considered IoT or IIoT. It is strongly
recommended that decision factors such as outlined below shall be taken into consideration.

Devices not considered as IoT/IIoT

In reality not all devices can be accepted to the “IoT/IIoT Club”. Through the following three examples I will
try to clarify the main considerations referring to this topic.
a) You purchased a home air conditioner activated by a smartphone or a web based application. If the
packing label shows “Wi-Fi-Ready”, you can do that, but it will not necessarily make it an IoT, since remote
activation by itself is not a sufficient condition to call it an IoT.
b) You consider to add a vibration sensor to a large water pump or gas turbine to diagnose a malfunction.
This is not an IIoT, as the vibration sensor device is reporting to a special PLC and an ICS computer
which control the operation of that machinery and may stop it if a fault is detected.
c) You purchased a CCTV camera, which is connected to a home computer or a VCR for security
surveillance. This is also not an IoT, because 24/7 loop recording system does not require additional data
available from cloud based resources and not require cloud based computing.

Devices considered as IoT/IIoT

Here are three commercial, consumer oriented and industrial examples, that according to listed explanations
are considered appropriate for being considered as IoT/IIoT ecosystem.
a) Computerized control of a washing machine. The IoT ecosystem using the built-in controller which
support the decision related to optimal starting of the washing process. Consequently, the IoT controller
device communicates with cloud based data sources related to the following considerations:
• Is there a report from the electric company on unusually high loading of the power grid at the
neighborhood? If yes, the washing process is delayed.
• Is it forbidden to cause unusual noise in a residential area such as may be caused by the washing
machine? If yes, the washing process is delayed
• Is there sufficient amount of hot water from the sun-roof boiler as required for the washing? If not, the
activation is delayed until electric heating of the water is completed.

The operation of a solar power plant can be controlled by an IIoT process. After the power plant receives
a request to start supplying power, the IIoT ecosystem system checks the following conditions:
• Is the forecasted intensity of sun-rays during the next few hours adequate to generate the required
energy to the grid? If not, the power plant activation is canceled.
• Are there alternative electric power resources that are more suitable to generate electricity for the
requested period? If yes, the power plant activation is rejected.
• If there are no other alternatives, the solar power plant will be activated with limiting conditions, and
the power grid operator will be advised accordingly.
c) An order is received to purchase a certain type meat for home use. Following this requirement, the
customer can start and IoT-based search using his smartphone:
• In which food chain is this item available, and what is the ticket price
• Which stores are active during the hours when the purchase is required
• The outcome of that process shall be a list of options sent to the customer
From the three examples listed above you may learn that the IoT/IIoT concept is applicable when it is
impossible to perform a simple interaction between the requesting entity and the device which provides the
service. IoT/IIoT systems allow such interactive process through cloud-based data resources.

Is there a reason for concerns?

Definitely yes, because huge amounts of cheap IoT components without professional configuration and
without cyber security measures will flood the internet network and allow cyber-attacks from all directions and
for any purpose. Can ordinary home owners properly configure these devices, replace the default password
and detect DDoS-type security breach? Of course not, and that's the problem.
Today, as a result of strong expectations towards IoT market, none wants to remember the early 2000’s and
the dot.com bubble. Then, well-known and professional companies invested billions of dollars in products
that did not provide benefits for which users were willing to pay. The benefits came only years later, and then
more resources were required to create new business models in order to recover their losses.

Summary

We all hope for huge IoT/IIoT deployments in the future, as this is good for users, vendors and also for
innovation. But…., anyone considering to develop a new IoT/IIoT ecosystem, shall focus on finding a real
need and properly design a cloud-data based solution that delivers significant benefits.
Cyber protection for any IT and ICS architecture consists of three essential elements that are achievable: a)
the use of security technologies, b) strict adherence to policies, and c) careful user behavior. This is also true
for IoT/IIoT ecosystems. Innovative technologies, components and architectures that will include cyber
protection as part of the IoT/IIoT ecosystem at no extra cost, will definitely drive the success.

Photo credit Martin Košáň via Flickr.

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As businesses are trying to leverage every opportunity regarding IoT by trying to find ways to partner with top universities and research centers, here is a list of the Top 20 co-occurring topics of the Top 500 Internet of Things Authors in the academic field. This gives an idea of research frontiers of the leaders.
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