The internet is now a given. It’s something that we don’t even consider. It’s always there and we can depend on it to help us just as we can depend on electricity and natural gas to keep us warm or cool.
The way in which we use the internet began as communications and has evolved far beyond that to something that is a necessity and something that is changing lives. We are entering a very unique period in the life of the internet.
IoT is isn't at all new to us though many people are not sure what IoT is and how it’s useful to humanity. It began at MIT and started nearly 20 years ago, in the early part of 2000s. IoT, to simplify the explanation, is nothing more than a network that is designed of all kinds of objects that connect to the internet. Refrigerators, cars, trucks, manufacturing computers, watches, tablets, are all examples of the IoT and each of them has unique capabilities.
Given the changes being made in IoT, this network can now be expanded to include physical items that may not traditionally have been part of the internet. Things like sneakers that count how far you've run or cushion your foot and measure the impact to the body. Street lights connected to the internet can record those who stand beneath them or activity that took place.
Iot, according to companies such as DHL and Cisco, is firing the imagination and creating a broad and diverse array of new jobs and new methods of accomplishing old tasks.
IoT offers us a transition in technology that has been impacting many different industries. IT will continue to do so along the way, impacting more tasks and more companies. It will, as it continues to change and evolve—offer huge implications for the movement of goods and services and the business of logistics.
Today some 15 million devices are connected to the internet. These embed sensors, control computers, help us to analyze our work, to source new data, and to find unparalleled views into operations and information that allow us to improve the speed, improve the products, improve the delivery and improve the overall service to our customers.
The IoT is already changing the way that we do business and the logistics of storage and delivery. It’s doing that by changing how we are making decisions about how goods are trucked, “stored, monitored, serviced, and delivered to customers.”
Trucks and cars carrying goods are already moving by the use of robotics in countries such as Singapore, the UK and the US.
Units for storage are carefully measuring temperature to ensure that goods are stored in the right way to prevent spoilage and saving money for the companies which are using them.
Vast changes and major impacts in how we buy, sell and use goods and services and improvements in the ways that they serve mankind are being wrought by the internet of things every day. Expect the future to be more of the same.
For more information check out our website at www.internetofthingsrecruiting.com
We went to IoT World last week in Santa Clara, California, where over 150 vendors and 10,000 attendees were showing their wares and making connections. More posts on that soon. In the meantime, here's our third issue of the IoTC Bi-Weekly Digest. If you're interested in being featured, we always welcome your contributions on all things IoT Infrastructure, IoT Application Development, IoT Data and IoT Security, and more. All members can post on IoT Central. Consider contributing today. Our guidelines are here.
By David Oro
Last week at IoT World, I stopped by the Buddy Platform booth (namely because of their killer Lego set-up). Buddy provides data hosting and management solutions for manufacturers and vendors of connected ("IoT") devices. Prior to IoT World, I sent Buddy CEO and Co-Founder Dave McLauchlan a few questions. Here's what he had to say.
By Danielle Storey
The technology sector is buzzing with predictions and hype about the Internet of Things (IoT), but many people are still confused about what it means, what the real world opportunities are and why businesses should be looking into IoT.
By Shayla Price
The Internet of Things is changing the world, heralded as one of the most pivotal technology trends of the modern era. We are getting ready to enter a time where everything, quite literally, is connected to the Internet. For the industrial sector, this is a new area of exploration. Factories have smart infrastructures that use sensors to relay data about machine performance. Cities have smart grids that monitor everything from traffic to the energy used by streetlights. Hospitals can monitor the health of high-risk, at-home patients.
In other words, we are entering a hacker's dream world.
By Roger Attick
The Internet of Things (IoT) concept promises to improve our lives by embedding billions of cheap purpose-built sensors into devices, objects and structures that surround us (appliances, homes, clothing, wearables, vehicles, buildings, healthcare tech, industrial equipment, manufacturing, etc.). What this means is that billions of sensors, machines and smart devices will simultaneously collect volumes of big data, while processing real-time fast data from almost everything and...almost everyone!!! IoT vision is not net reality Simply stated, the Internet of Things is all about the power of of connections.
Guest blog post by Vincent Granville
AI was very popular 30 years ago, then disappeared, and is now making a big come back because of new robotic technologies: driver-less cars, automated diagnostic, IoT (including vacuum cleaning and other household robots), automated companies with zero employee, soldier robots, and much more.
Will AI replace data scientists? I think so, though data scientists will be initially replaced by "low intelligence" yet extremely stable and robust systems. There has been a lot of discussions about the automated statistician. I am myself developing data science techniques such as Jackknife regression that are simple, robust, suitable for black-box, machine-to-machine communications or other automated use, and easy to understand and pilot by the layman, just like a Google driver-less car can be "driven" by an 8 years old kid.
My approach to automating data science and data cleaning / EDA (exploratory data analysis) is not really AI: it's just a starting point, but not a permanent solution. In the long term, it is possible that AI will handle complex regression models, far more complex than my Jackknife regression: after all, all the steps of linear or logistics regression modeling, currently handled by human beings spending several days or weeks on the problem, involve extremely repetitive, boring, predictable tasks, and thus it is a good candidate for an AI implementation entirely managed by robots.
As machine learning (ML) more and more involves AI, and the blending of ML and AI is referred to as deep learning, I can see data science evolving to deep data science (DDS) or automated data science (ADS), where AI, robots, or automation at large, take a more prominent role.
True AI systems can even predict travel time in real time based on expected traffic bottlenecks and road closures
Which jobs are threatened by AI?
Just like data science will take years to get a high level automation, where as much as 50% of human tasks are replaced by robots, I believe that these professions are at risk, but the erosion will be modest and slow, taking a lot of time to materialize:
- Teachers: some topics such as mathematics or computer science can be taught by robots, at least for the 10% of students that are self-learners. Generally speaking, topics that are currently taught by robots include flying a plane, training on an AI-powered simulator. Ironically, planes can be flew without human pilots, but studies have shown that passengers would be very scared to board a pilot-less plane. The biggest threat for teachers is not AI though, it is online training.
- Grading student papers, detect plagiarism. But students / authors are getting more sophisticated, using article-generating software powered by AI, to avoid detection. This could lead to an interesting war: AI robots designed for fraud detection fighting against AI robots designed to cheat.
- For publishers, automatically writing high-quality, curated articles in a short amount of time. An article such as this one is a good candidate for automated, AI-powered production. The first step is to identify articles that are good candidates (for curation) for a specific audience; this is also accomplished using AI.
- Can AI writes AI algorithms, or in short, can AI automate AI? I believe so; after all, I was one of the pioneers who wrote programs that write programs (software code compilers or interpreters also fit in this category). I guess this is just an extension of this concept.
- Automated diagnostic (or automated doctor, but also automated lawyer). I guess this will eliminate a small proportion of these practitioners. But what about a robot performing a brain surgery with higher efficiency than a human surgeon? Or a robot manufacturing an ad-hoc, customized client-specific drug for maximum efficiency?
- Automated chefs replacing expensive cooks in a number of restaurants. Or think about a McDonald restaurant where the only human is a security guard - everything else being outsourced to AI-powered robots, including cleaning, preparing food, delivering to customers, processing payments, filing tax returns and accounting, ordering from vendors, and so forth. This would require significant system-to-system communications, but I believe it is feasible.
- Automated policemen or soldiers is a source of concern, as you would have algorithms that decide who to kill or who to arrest. So this might not happen for a long time, though drones are replacing soldiers in a number of wars, and have the power to kill (based on some algorithm) with no one complaining about, as long as it is not happening in US. Terrorists might be attracted too by this type of technology.
- AI will be present in many IoT applications such as smart cities, precision farming, transportation, monitoring (detecting when an offshore oil platform is going to collapse), and so on.
AI and automation has already replaced many data science tasks long ago
Many people talk about the threat of AI, but as of today, many jobs have already been automated, some more than 30 years ago. For instance, during my PhD years, a lot of data transited through tapes between big computer systems, and involved trips to the computer center, interacting with a number of people taking care of the data flow. This has entirely disappeared.
We used to have shared secretaries to write research papers (they could write LaTeX documents), I think this has all but disappeared.
One of the applications that I developed in the eighties was a remote sensing software that could perform image segmentation and clustering, for instance to compute the proportion of various crops in a specific area based on satellite images, without human interactions - thus eliminating all the expensive jobs that were previously performed by humans to accomplish this task.
Those who automate data science are still data scientists. Just like those developing robots to automate brain surgery work in a team, with many members being brain surgeons. it's just shifting the nature of the job rather than eliminating it.
Guest blog post by Bernard Marr
In a meeting with Airbus last week I found out that their forthcoming A380-1000 – the supersized airliner capable of carrying up to 1,000 passengers – will be equipped with 10,000 sensors in each wing.
The current A350 model has a total of close to 6,000 sensors across the entire plane and generates 2.5 Tb of data per day, while the newer model – expected to take to the skies in 2020 – will capture more than triple that amount.
In an industry as driven by technology as the aviation industry, it’s hardly surprising that every element of an aircraft’s performance is being monitored for the potential to make adjustments which could save millions on fuel bills and, more importantly, save lives by improving safety.
So I thought this would be a good opportunity to explore how the aviation industry, just like every other industry, is putting data science to work.
There are 5,000 commercial aircraft in the sky at any one time over the US alone, and 35 million departures each year. In other words the aviation industry is big. And given that every single passenger on each of those flights is putting their life in the hands of not just the pilot, but the technology, the safety measures and regulations in place are extremely complex.
This means that the data it generates is big, and complex too. But airlines have discovered that with the right analytical systems, it can be used to eliminate inefficiencies due to redundancy, predict routes their passengers are likely to need, and improve safety.
Engines are equipped with sensors capturing details of every aspect of their operation, meaning that the impact of humidity, air pressure and temperature can be assessed more accurately. It is far cheaper for a company to be able to predict when a part will fail and have a replacement ready, than to wait for it to fail and take the equipment offline until repairs can be completed.
In fact, Aviation Today reported that it can often take airlines up to six months to source a replacement part, due to inefficient prediction of failures leading to a massive backlog with manufacturers.
On top of this fuel usage can be economized by ensuring engines are always running at optimal efficiency. This not only cuts fuel costs but minimizes environmentally damaging emissions.
In the case of Airbus, they partnered with IBM to develop their own Smarter Fuel system, specifically to target this area of their operation with Big Data and analytics.
Additionally, airlines closely monitor arrival and departure data, correlating it with weather and related data to predict when delays or cancellations are likely – meaning alternative arrangements can be made to get their passengers where they need to be.
Before they even take off, taxi times between the departure gates and runways is also recorded and analyzed, allowing airlines and airport operators to further optimize operational efficiency – meaning less delays and less unhappy passengers.
This sort of predictive analysis is common across all areas of industry but is particularly valuable in commercial aviation, where delays of a few hours can cost companies millions in rearrangements, backup services and lost business (The FAA estimates that delayed flights cost the US aviation industry $22 million per year).
Specialist service providers have already cropped up – masFlight is one – aiming to help airlines and airports make the most of the data they have available to them.
They aggregate data sets including weather information, departure times, radar flight data and submitted flight plans, monitoring 100,000 flights every day, to enable operators to more efficiently plan and deliver their services.
In marketing, too, airlines are beginning to follow the lead of companies such as Amazon by collecting data on their customers, monitoring everything from customer feedback to how they behave when visiting websites to make bookings.
Now we are used to generating and presenting tickets and boarding cards through our smartphones, more information about our journey through the airport, from the time we enter to the time we board our flight can also be tracked. This is useful both to airport operators, managing the flow of people through their facilities, and to airlines who will gather more information on who we are and how we behave.
So businesses in the aviation industry, including Airbus, are making significant steps towards using data to cut waste, improve safety and enhance the customer experience. 10,000 sensors in one wing may sound excessive but with so much at stake – both in terms of profits and human lives – it’s reassuring that nothing will be overlooked.
I hope you found this post interesting. I am always keen to hear your views on the topic and invite you to comment with any thoughts you might have.
About : Bernard Marr is a globally recognized expert in analytics and big data. He helps companies manage, measure, analyze and improve performance using data.
His new book is: Big Data: Using Smart Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance You can read a free sample chapter here.
The observation deck won’t be finished for a few years yet. If you want to see the future of New York, walk north along the High Line, round the curve at the rail yards, and turn your back to the river. Amid the highway ramps and industrial hash of far-west Manhattan, a herd of cranes hoists I-beams into the sky. This is Hudson Yards, the largest private real-estate development in United States history and the test ground for the world’s most ambitious experiment in “smart city” urbanism. 1
Over the next decade, the $20-billion project — spanning seven blocks from 30th to 34th Street, between 10th and 12th Avenues — will add 17 million square feet of commercial, residential, and civic space, much of it housed in signature architecture by the likes of Skidmore, Owings & Merrill; Diller Scofidio + Renfro; and Bjarke Ingels Group. 2But you don’t have to wait that long to see where this is headed. The first office tower, Kohn Pedersen Fox’s 10 Hudson Yards, opens next month, with direct access to the High Line. The new subway stop is already in business (and has already sprung a few leaks); an extension of the 7 train line connects the diverse, middle-class neighborhood of Flushing, Queens, with this emerging island of oligarchs.
Read the complete story here.
The Internet of Things (IoT) concept promises to improve our lives by embedding billions of cheap purpose-built sensors into devices, objects and structures that surround us (appliances, homes, clothing, wearables, vehicles, buildings, healthcare tech, industrial equipment, manufacturing, etc.).
IoT Market Map -- Goldman Sachs
What this means is that billions of sensors, machines and smart devices will simultaneously collect volumes of big data, while processing real-time fast data from almost everything and... almost everyone!!!
IoT vision is not net reality
Simply stated, the Internet of Things is all about the power of connections.
Consumers, for the moment anyway, seem satisfied to have access to gadgets, trendy devices and apps which they believe will make them more efficient (efficient doesn't necessarily mean productive), improve their lives and promote general well-being.
Corporations on the other hand, have a grand vision that convergence of cloud computing, mobility, low-cost sensors, smart devices, ubiquitous networks and fast-data will help them achieve competitive advantages, market dominance, unyielding brand power and shareholder riches.
Global Enterprises (and big venture capital firms) will spend billions on the race for IoT supremacy. These titans of business are chomping at the bit to develop IoT platforms, machine learning algorithms, AI software applications & advanced predictive analytics. The end-game of these initiatives is to deploy IoT platforms on a large scale for;
- real-time monitoring, control & tracking (retail, autonomous vehicles, digital health, industrial & manufacturing systems, etc.)
- assessment of consumers, their emotions & buying sentiment,
- managing smart systems and operational processes,
- reducing operating costs & increasing efficiencies,
- predicting outcomes, and equipment failures, and
- monetization of consumer & commercial big data, etc.
IoT reality is still just a vision
No technology vendor (hardware or software), service provider, consulting firm or self-proclaimed expert can fulfill the IoT vision alone.
Recent history with tech hype-cycles has proven time and again that 'industry experts' are not very accurate predicting the future... in life or in business!
Having said this, it only makes sense that fulfilling the promise of IoT demands close collaboration & communication among many stake-holders.
A tech ecosystem is born
IoT & Industrial IoT comprise a rapidly developing tech ecosystem. Momentum is building quickly and will drive sustainable future demand for;
- low-cost hardware platforms (sensors, smart devices, etc.),
- a stable base of suppliers, developers, vendors & distribution,
- interoperability & security (standards, encryption, API's, etc.),
- local to global telecom & wireless services,
- edge to cloud networks & data centers,
- professional services firms (and self-proclaimed experts),
- global strategic partnerships,
- education and STEM initiatives, and
- broad vertical market development.
I'll close with one final thought; "True IoT leaders and visionaries will first ask why, not how..!"
Home Automation DIY Case Study
The following is from a Mind Commerce interview with residential owner/installer/operator:
“ I got into the home automation craze by accident when one of my managers described what he was doing. After looking at it, the added convenience, security, and cost savings made me a believer. The overall category of devices that I use are the Internet of Things (IoT). ”
“ My setup is as follows:
- I have an Amazon Echo that allows me to issue voice commands to the majority of my IoT devices. It also will play music from my Amazon Prime account and allow me to order merchandise (all voice of course). It additionally allows me to keep a TODO and shopping list that is synchronized to my Alexa app on my iPhone. As I think of items, I just tell Alexa (the name for the Echo), and she will add the items to the list. I use this all the time. You can also set timers and alarms vocally, which is another well-used feature. There's tons more. The Echo talks WiFi.
- I use a Wink Hub to interface the Echo to devices that don't directly talk over WiFi, or that the Echo doesn't directly support. The Wink Hub talks Z-Wave, Zigbee, WiFi, and Lutron's proprietary communications (dimmers). The Wink Hub also has a nice APP that lets me control everything directly from my cellphone if I want.
- I use Luton dimmers that allow me to turn on, turn off, or set the dimming level for my most commonly used lights. The echo supports this so I can say "Alexa set living room lights to XX%" and it happens.
- I have a Rain Machine which is a connected sprinkler controller. I can turn on stations from the Echo, but I don't. What it allows me to do is to set the watering parameters and then it connects to NOAA and it will modify my preferences based on how much rain has fallen. Money saver. It has a great APP and will tell me how much each station actually watered per week. A real money saver in Florida.
- The Ecobee 3 thermostat was an expensive but awesome IoT purchase that also saved me a lot of money this past winter. It is very smart and connects to the Echo directly (WiFi). I can tell Alexa to raise or lower the temperature by voice. Setup couldn't be any simpler, and the APP is awesome. Conventional wisdom in the winter is to lower your temperature at night and then have it increase before you wake to save money. Wrong! The Ecobee tracks when your fan and compressor run (view on the website). I found out that turning the temperature down by 4 degrees overnight was causing my heat strips (expensive) to turn on for a couple of hours around 5AM to bring the temperature back up. I was much better off just leaving it one degree less all the time.
- For my garage door controller, I bought an IoT box that allows me to view the status of the garage door and to remotely open or close the door by using the Wink APP. Really nice when I can't remember if I closed the door, or left it open. This doesn't work with the Echo by design (having a crook yell into your house "Alexa open the garage door" wouldn't be a good thing).
- Nest Cam is an awesome security device. When I'm on travel I can view what's going on in the house and even hear what's going on. It's got 1080p resolution and night IR capability (see at night with the lights off). I can even talk to my cat through it. I pay for the cloud recording service, so when it's on, a month of recording is held on the cloud, which would be useful if the house is ever robbed. The problem is I don't want it recording while I'm home. That is solved by...
- Leviton makes smart bricks that plug into an outlet and let you plug an appliance (anything) into it and control that appliance on/off state through Wink or the Echo. So when I leave, I can just vocally tell the Nest Cam to turn on, or if I forget, I can just use the Wink APP to turn it on remotely. I use these to control the Nest Cam, my DirecTV internet device, and my Amazon Fire TV. Whey have them sucking energy all the time when I use them maybe 2% of the time? “
As an advanced user*, he also had this to say:
- “ The is a function call IFTT (If This Then That) that works with the Echo, Wink and the IoT devices to allow creation of recipes that handle what to do if something happens. For example, I set up an IFTT that when I ask the Echo where my cellphone is, the IFTT will call the phone so it rings. The possibilities are limitless. Think Geo-fencing or linking input from IoT sensors to automatically cause actions. “
*Note: Remember, this is a more advanced, tech user. However, IoT is increasingly becoming part of the consumer lexicon!!
This infographic was originally published by Intel and can be found here. It dates back to 2014 but still provides a very comprehensive view of this fast expanding field.
Originally posted on Data Science Central
Our second issue of the IoTC Bi-Weekly Digest is below. If you're interested in being featured, we always welcome your contributions on all things IoT Infrastructure, IoT Application Development, IoT Data and IoT Security, and more. All members can post on IoT Central. Consider contributing today. Our guidelines are here.
By David Oro
Just ahead of the Internet of Things World conference taking place May 10–12 at the Santa Clara Convention Center in Silicon Valley, we were lucky enough to catch up with one of the conference speakers, Ken Finnegan, Chief Technology Officer, IDA Technology Ireland. We asked Mr. Finnegan about IoT and Smart Cities, IoT implementations in Dublin, and his thoughts on making cities smarter. Here’s what we learned.
By Ian Skerrett
Today we release the results of our second annual IoT Developer Survey. Like last year it provides an interesting insight into how developers are building IoT solutions. This year the Eclipse IoT Working Group partnered with IEEE IoT and theAGILE-IoT research project to expand the scope and respondent pool for the survey. Thanks to this partnership, we had 528 participants in the survey, up from 392 last year. The partnership also allowed us to analyze the data to look for any significant difference between the different IoT communities.
What options do you have for remotely monitoring water and fluids with Industrial IoT sensor telemetry?
By Pawei Sasik
IIoT or Industrial IoT (Internet of Things) is everywhere. It’s across all industries, from high tech transport, to natural resources and governments. IIoT software and hardware is deployed for numerous, varying applications, and it’s critical to understand just what the customer needs. One of the areas that we’ve seen recent growth is water and fluid monitoring. Water comes to us as a life sustaining asset and also as a force of destruction. The utility of water needs to be measured and monitored in order to effectively and efficiently use our greatest natural resource. Similarly, monitoring the destructive force of water can be just as important. Let’s talk about the different ways that you can measure and monitor water!
By Thierry Lillete
As the platform race continues to mature for the IoT, we found a great post by by Thierry Lillette that looks into the platforms, ecosystems and products. Good reading for any IoT and digital professional.
By Bernard Marr
We’ve had software as a service, platform as a service and data as a service. Now, by mixing them all together and massively upscaling the amount of data involved, we’ve arrived at Big Data as a Service (BDaaS). It might not be a term you’re familiar with yet – but it suitably describes a fast-growing new market. In the last few years many businesses have sprung up offering cloud based Big Data services to help other companies and organizations solve their data dilemmas.
By David Oro
Phillip Zito at the highly resourceful blog Building Automation Monthly has consolidated multiple IoT Frameworks and Offerings into the IoT Database. You will see links to the Frameworks and Offerings below. He says over time that he will be working on providing summary articles on each Framework and Offering. He could use your help. If you have an offering/framework you would like added to this list feel free to add it in the comments. You can find the IoT Database here.
By David Oro
It’s still early days for the IoT but everyday a little part of its burgeoning ecosystem becomes a factor in our lives, whether we know it or not. From industrial tools to farming to cities to grocery aisles and everything in between, the IoT is there. Here are 10 IoT case studies that show just where some of these technologies and applications are being applied.
While discrete manufacturing is used in a diverse range of industries, including automotive, aerospace, defense, construction, industrial machinery, and high tech, all of them face common and tough challenges such as higher resource volatility, more competition, increasing customer expectations, and shorter innovation cycles.
According to a study by a Roland Berger (see chart), product complexity has increased dramatically in the past 15 years. Manufacturers have to cope with two overlapping trends: the variety of products is constantly increasing and has more than doubled in the past 15 years, and, in parallel, product lifecycles have gotten about 25% shorter. These factors are putting an increasing pressure on margins, on supply and procurement systems, and on overall business models. According to Roland Berger, managing this complexity could reduce costs by roughly 3% – and certainly digitization can help improve this margin.
The threats and potentials of digitization
Adapting to the age of hyperconnectivity is a matter of life and death for the majority of companies, according to a study by the Economist Intelligence Unit. More than half of enterprises feel very strong competitive pressure from digital offerings by their traditional competition, established companies using digital to enter their market, and digital startups. Certainly, the competition is not waiting, and neither will today’s well-informed digital customers, who want more choice, better customization, and more information around the buying process. While digitization might add another disruptive dimension to an already rising complexity, discrete manufacturers are seeking the benefits of digitization. They are already proactively exploring the use of the IoT to better connect their supply chains, assets, and products, according to an IDC white paper, The Internet of Things and Digital Transformation: A Tale of Four Industries, sponsored by SAP.
Most manufacturers start with less complex projects, such as enhanced visibility or tracking, and progress to more sophisticated processes that require automated or predictive workflows, according to IDC. The findings of the study suggest that companies should start their IoT projects with the overarching goal of a live business operation already in mind. By combining three IoT use cases for manufacturing, i.e. connecting products, creating a connected shop floor with customization, and extending digital business models (see chart), companies will create a competitive business operation that fully exploits the digital opportunities.
Connecting products to improve innovation
Using IoT for innovation is a highly underestimated potential of digitization. A significant percentage of new products fail, and the associated R&D and marketing costs are lost. Customers already expect their products to come with a certain degree of interactivity and this demand will certainly grow in the future. According some estimates on the adoption of connected technology by consumers, the ratio of connected and interactive products will rise to approximately 20% on average by 2020, according to Forbes. This is a conservative estimate, and in some segments the ratio might increase much faster.
By digitizing current products and launching fully digitized ones, manufacturers can significantly reduce the risk of new product failures, as IoT-based products will enable them to monitor the actual use and performance of their products, get live feedback from their customers, and adopt future product innovation. IDC expects that by 2017, 60% of global manufacturers will use IoT to sense data from connected products and analyze that data to optimize the product portfolios, performance, and manufacturing processes. Similarly, the integration of IT assets and information with operational technology in the plant and the supply chain is also on the roadmap, if not already started.
Connecting the shop floor
Digitization offers the possibility to oversee every step in the manufacturing process, from customer demand, through production, and across the complete supply chain. The IDC study identified two IoT use cases – strategic asset management and customer experience – that seem to be very attractive for discrete manufacturing.
1. Strategic asset management
Manufacturers should start to digitize all of their assets in the production process and use IoT-based preventive and predictive maintenance scenarios in the plant and supply chain to reduce downtime and improve utilization. Using the information generated from digitization and IoT, businesses can evaluate use patterns and maintenance routines of their inventory and assets and optimize operations. Fixed assets can account for as much as one-third of all operating costs, so under today’s cost pressures a digital asset management surely matters. To fully use the potential of IoT and the real-time information gathered from assets, devices, and machines, companies need to ramp up their analytical and decision-making capabilities. Anecdotally, companies report that IoT use cases (such as remote maintenance) changed the way they thought about data and got them thinking significantly differently about information and insights.
2. Customization for customer experience
Demand for more choice, flexibility, and customized products is growing fast and estimated to be 15% of all products by 2020, according to MIT Smart Customization Group. Depending on size, material, and complexity, that percentage might be significantly higher. However complex the challenge for manufacturers might be, connected production in real-time is the basis, and it needs the right data from production capabilities, supply, equipment, and workforce, combined with all customer preferences. Getting the customer into the customization and production process is increasingly important for an improved customer experience, so IoT should be used to connect the products and, with it, the customer. This will not only give companies valuable data about user preferences and ideas for product innovation and improvements, but it will allow them to plan the customization of products much more efficiently.
Digitally enhanced business models
Digitization is by now a synonym for disruption. According to a study by the Economist Intelligence Unit, 60% of companies think that digitization is the biggest risk they face. More than half of companies feel competitive pressure from digital offerings by their traditional competition and digital startups. As IDC found, discrete manufacturers are already actively exploring the IoT opportunities, so the change is already underway.
As we pointed out previously, the customer experience of choosing and buying a product is increasingly important, but it does not stop there. IoT-connected products will get the customer into an ongoing interaction with the product vendor and/or retailer, enhancing the buying and use experience. Moreover, companies can use this connection to expand their business models. In its study, IDC mentions a wider range of ideas that manufacturers already explore, such as remote maintenance, refill and replenishment, contracting, product performance, training, and location-based services. While they may not be applicable for all companies, they show the wide range of possibilities and opportunities. Digitization may be a threat for some traditional business models and companies, but it offers huge potentials for those who focus on the customer experience.
Creating a live business operation
The huge potential that IoT offers is less the physical connection of things, machines, and devices, and more the opportunity to create a live business operation based on an advanced data strategy and analytics. While all aspects of IoT have large innovation opportunities on their own, the combination of connected products, customization, and digitally expanded business models promises the biggest benefits for discrete manufacturers. Thus any IoT strategy – wherever it starts – should be created with a larger digitization goal in mind.
- Connecting products and strategic asset management has big potentials for discrete industries.
- The combination of connected products, customization, and digitally expanded business models promises the biggest benefits.
- Companies should create a live business operation with advanced data and analytical skills to use the full potential of IoT.
For more details and information, please read IDC’s IoT whitepaper IoT and Digital Transformation: A Tale of Four Industries and look for future IoT papers that delve deeper into the IDC study’s findings.
Just ahead of the Internet of Things World conference taking place May 10–12 at the Santa Clara Convention Center in Silicon Valley, we were lucky enough to catch up with one of the conference speakers, Ken Finnegan, Chief Technology Officer, IDA Technology Ireland. He advises and provides strategic insights into technology trends both nationally and globally for the agency and client companies. He has worked in the software, telecommunications and big data industries for 15 years before joining the IDA in 2014. The IDA is Ireland's inward investment promotion agency, it is a non-commercial, semi-state body promoting Foreign Direct Investment into Ireland through a wide range of services.
We asked Mr. Finnegan about IoT and Smart Cities, IoT implementations in Dublin, and his thoughts on making cities smarter. Here’s what we learned.
What are a few examples of IoT-based technologies that have been implemented throughout Dublin?
There are some really great projects happening in Ireland. The approach that Dublin has taken is a balanced top down - bottom up approach. What I mean by this is that the smart initiative is being driven by city leaders with support from government agencies (e.g. IDA Ireland, Enterprise Ireland and Science Foundation Ireland) at the top, whilst at the same time engaging with the citizens and companies in order to identify and seek solutions to the real needs of the city.
There are five pillars to the Smart Dublin strategy. These include:
- Smart Government
- Smart Mobility
- Smart Environment
- Smart Living
- Smart People
The principles followed:
- How to use smart technologies to improve city livability and competitiveness:
- Taking a challenge based approach to procurement to deliver better quality outcomes for the city.
- Positioning Dublin as the place to pilot and scale new smart city technology opportunities.
Understanding the key areas of focus and the driving principles are vital to describing the challenges and demonstrating that top down bottom up approach.
A recently completed Smart City challenge that is a fantastic demonstration of IoT in the city was “Keeping Our City Streets Clean.“
A critical role of the city council is that of street cleaning and managing waste across busy city center areas in particular. There is a network of over 3,500 street bins that are manually emptied on a regular basis - the timing of which varies depending on the profile of the street. This street cleaning service is critical to maintaining a clean and litter free city. There has been an increasing trend of successful deployment of smart bin technologies in cities that incorporate features such as:
- Sensors that communicate back to the street cleaners when they are full
- Use of accompanying software that allow for optimization of routes for cleaning schedules
- Use of software applications that deliver real-time data information (through a web portal or smartphone) on each bin status, their inventory management and other efficiency related data
The result was self-compacting bins that send an email when they need to be emptied!
Smart Bins are solar-powered, Wi-Fi enabled bins that are being installed in towns, villages and residential areas across the country to replace traditional public litter bins.
There are currently 401 Smart Bins installed in the south county area. The project is managed by the County Council by the Environment Department with the purpose to improve the efficiency of waste management.
Other examples can be found here including this video of Croke Park Smart Stadium.
Since transitioning to a smart city, what benefits has the city of Dublin experienced? And what plans do you have to make Dublin even smarter?
Without a doubt the biggest benefit Dublin and Ireland’s other cities have seen is a demonstration of the power of collaboration to uncover value.
IDA Ireland has been successful in attracting and supporting multinationals here for a long time. With the combination of engagement with our multinational companies, a vibrant small-to-medium enterprise and start-up community, an openness for business from the cities, the youngest, digitally savvy population in Europe, a highly connected research ecosystem that is easily accessed by industry and support from the government - there is a lot happening.
For example, Dublin has what we call ‘Silicon Docks’. It’s a part of the city that has the European HQ’s for Google, Facebook, Airbnb, Twitter, LinkedIn, LogMeIn, Adroll, Accenture, Zalando, Tripadvisor and more.
Dublin City Corporation are planning to make this part of the city the most ‘densely sensored’ urban area in the world - producing lots of data that will be accessible by companies, government, academia and citizens. We anticipate that this is going to be a very powerful demonstration of Ireland’s capabilities to design and develop the sensors, connect them over multiple transmission types and finally with one of Europe’s largest data analytics research centers here, uncover, discover and predict value.
Central to the smart city goals is also to ensure that the infrastructure in place, the LORA (Low Powered Radio) transmission standards are currently being rolled out across the entire island. This is funded by Science Foundation Ireland and coordinated by the CONNECT Research center and allows companies to conduct robust due diligence into what transmission standard works for them. Companies can also access and rent the live radio spectrum, access the Sigfox network and lots more infrastructure; the building blocks are in place for technical solutions.
Ireland seems to have a head start when it comes to the innovation in the area of IoT and smart cities. What other cities have you admired in their innovation, implementations and adoption to make their cities smarter?
A city I really respect for embracing and encouraging technology is Amsterdam.
Amsterdam is my second home, I lived there after graduating university and it was where a young Ken Finnegan learned the power and beauty of innovation. That is a city that is not afraid to positively leverage emergent technologies. I have seen cities, companies, government and people look at innovation as a threat and to try and tame it. This never works, if there is a smarter way to do things, do it. When policy tries to limit adoption of innovation or when companies fail to recognize it, they are only delaying its ubiquitous arrival and ultimately lose opportunities for growth and success. Amsterdam has the right attitude. It may not know what it’s dealing with but they know there is value to be exploited somehow. I would love to see a twining of Amsterdam and Dublin. I think they are two European cities that are extremely likeminded in approach.
Ireland seems to be all in on smart cities - enlisting both the public and private sector, and educational institutions - towards creating smart cities. What’s your advice for other government entities and the many private vendors in this space?
Indeed governments, academia and the private sector all play an essential part and each entity has ideas about what value is and how it will be generated. Simply my advice is to start the conversation.
Government can facilitate conversation with all the entities. We have a strong appetite for change and growth and a characteristic in Ireland I come across every day is the idea of coopetition. The idea of cooperating together whilst possibly in competition. We all wear the green jersey in Ireland, we are very proud of this green island, but we also want to develop the industry ultimately making it stronger for all in order to grow and win. By not talking to each, you limit growth opportunities, when you sit with competitor and others you need to figure out the safe ground and see how you can work together to succeed.
Next we have to realize that government and industries have to engage with the end-users. We see that the citizen or what I term pro-citizen (professional citizen – the skilled and informed people that live, work and play in the cities, know the fabric of the city – plumbers, binmen, clubber, doctors, civil servants, sports members, teachers, social workers, bar staff, etc.), as the consumers of smart city good and services. These citizens provide the suggested personalized solutions of the problems they encounter in day-to-day life. It’s the application of a User Design approach to Smart cities.
Finally we have being listening to the narrative about the power of big data for years now. In order to harness the power it essential that data is accessible to all. For example Dublinked is a regional data sharing initiative that has previously unreleased public operational data being made available online for others to research or reuse. With the initial data coming from Dublin City (4 boroughs), public and private organizations in Dublin are linking up with Dublinked to share their data and invite research collaborations. The information is curated by Maynooth University to ensure ideas can be commercialized as easily as possible and to minimize legal or technical barriers that can be impediments for small and medium businesses (SMEs) seeking to develop and prove business ideas.
Smart cities are predicated on the advancement of IoT technologies. Do you see IoT as an opportunity for economic development and job creation? If so, how?
Yes for both cases.
In our five-year strategy launched in 2015, Wining 2020, IoT is the number one strategic technological area we are focusing on. If we didn’t believe IoT would increase economic development or create jobs there is absolutely no way it would be there. We have done our homework, we have listened to our clients and we have mobilized the organization to ensure that each person know exactly why Ireland is the global location for the Internet of Things. In addition to this, we are working with other government agencies to ensure that the environment is right for our clients to be successful. For example our sister agency Science Foundation Ireland has funded multiple research centers of scale (€50m +) so that industry can leverage the quality research coming from the academic system. They have also funded the roll out of transmission network s across the entire land that can be leveraged by industry to research, test and develop innovations. Between IDA Ireland, Enterprise Ireland and Science Foundation Ireland, there are many tools we provide by which industry can leverage to test and trail their products and services before commercializing. Our client companies are trailing these, not in a confine test lab, but literally out in the field, in the cities, in our bays and on our highways because Ireland is connected.
You’ll be speaking at IoT World. What should the audience expect to hear from you?
1. Ireland is open for business. If you have a problem that needs to be solved, if you want to service the European, Middle East and African markets, if you need infrastructure for research and development, or simply looking for a location with accessible and available talent, we are ready for to have that conversation.
2. IoT has gained a lot of talk time over the past 5 years, but the conversation for IoT have been developing in Ireland more than 30 years. We are home to 10 out of the top 10 born on the internet/content companies, 9 of the top 10 information communication technology, 15 of the top 20 pharmaceutical and life science companies, fintech, engineering, food etc. companies. Many of these companies are developing their IoT solutions by working together here. It’s truly an agile and collaborative hotspot to be. Take a look at the past two years and the companies that have decided to move here, there is a very convincing track record.
3. The environment is right. With one of the youngest and tech savvy populations in Europe, the biggest names in Industry, proactive government agencies and an academic scene focused on impact for industry, IDA Ireland want to partner and support companies ready to grow and succeed in the Smart IoT arena.
Today we release the results of our second annual IoT Developer Survey. Like last year it provides an interesting insight into how developers are building IoT solutions.
This year the Eclipse IoT Working Group partnered with IEEE IoT and the AGILE-IoT research project to expand the scope and respondent pool for the survey. Thanks to this partnership, we had 528 participants in the survey, up from 392 last year. The partnership also allowed us to analyze the data to look for any significant difference between the different IoT communities.
As with any surveys of this nature, I encourage readers to see these results as one data point that should be compared with other data and industry trends. These results will have certain biases but I do believe these results identify some interesting trends in the IoT industry.
Key Trends for IoT developers
- Companies are shipping IoT solutions today. 46% of the respondents claim their company develops and deploys an IoT solution today. Another 29% plan to do so in the next 6 months. This is a clear indication the industry is maturing quickly.
- Security continues to be a key concern. It’s not a big surprise that security continues to be the top concern in IoT. Interoperability is the second key concern. I do believe we are on the way to solving some of the interoperability issues with projects like Eclipse Hono, Eclipse Smarthome and Eclipse Kura. I also think some of the work the AGILE-IoT project is doing will address these issues. However, it still seems the IoT industry still needs to focus on security. It is a difficult issue that needs to be solved.For companies that have deployed a solution today, performance is rising to the third key concern. It is not clear what the performance issues are, but it is something that warrants more investigation.
- MQTT and HTTP are the dominant message protocols.Without a doubt MQTT has become a pervasive and widely used protocol for IoT. HTTP being the other protocol.
The other messaging protocol supported in the Eclipse IoT community is CoAP. It did not receive as much support, but it does appear to have support in certain industries. For instance, the use of CoAP increases if the respondent is in the IoT Platforms or Smart Cities industry. The fact IoT Platforms are supporting CoAP is expected and a good thing. It does seem Smart Cities industry is using CoAP but I am not sure where or how. If anyone has details, please leave a comment.As an aside, the success of MQTT is a testament to IBM’s strategy to standardize MQTT at OASIS and start the Eclipse Paho project. It really is a perfect case study for using open source and open standards to gain broad industry adoption. For example, 1) MQTT is now supported by IBM Bluemix, Amazon AWS IoT, MS Azure IoT, plus every other IoT middleware platform in the market, 2) the new Arduino board is also using MQTT to communicate with their cloud, and 3) Eclipse Paho and Eclipse Mosquitto are some of the most popular and active projects at Eclipse. MQTT is everywhere. Well done IBM.
- Linux is the dominant IoT operating system. Over 70% of the respondents claimed they use Linux for their IoT operating system. The next more popular section at 23% was No OS/Bare metal. In the last number of years, a number of new IoT operating systems have been introduced (ex. ARM mbed, Contiki, RIOT, Zephyr) but the adoption still hasn’t materialized. It seems many companies are using Yocto to create their own Linux distro for their IoT solution. It will be interesting to watch how these other operating systems grow in comparison to Linux.
- Amazon leads in IoT cloud services. Not terribly surprising Amazon came out on top as the top cloud service provider. However, Private/On premise was a close second so I think this is an indication that IoT cloud services is still in its infancy. What did surprise me was that Microsoft Azure was number 3 in the survey and does even better when a company has a deployed solution. This seems to reflect MS Azure’s heavy emphasis on IoT use cases.
- Open source is pervasive in IoT. I strongly believe open source is critical to the success of the IoT industry. Therefore, I was encouraged to see 58% of the respondents are actively engaged with open source. I think it is a great statement on the work we have been doing at Eclipse IoT to create an open source community for the IoT industry.
Trends between 2015 and 2016
This is the second year we have done this type of survey so I was curious what has changed between 2015 and 2016. Interestingly enough, not a lot has changed. Many of the trends and highlights mentioned above are consistent with the 2015 results. This consistency would appear to confirm that the results are a good reflection of how developers are building IoT solutions.
Thank you to everyone who participated in the survey. We definitely appreciate your input. The complete results are available on slideshareand the raw data in xls and ods format. Feel free to leave a comment or contact me if you have any questions.
In The Great IOT Recruiting Rush, I introduced the industries that are heating up and the single main skill for the successful IOT practitioner. Here, I give you a targeted checklist for IOT recruiting.
Earlier this month, I published a post about which industries were heating up in IOT recruiting. Obvious players like IBM and Cisco topped the list, of course, but, increasingly, non-technology companies are joining the IOT hiring frenzy.
With all of this going on, it’s quite challenging to nail down the skills that a top IOT recruit will need. Of course, many of these are industry-specific or specifically outward facing (customer experience and wearables) or inward facing (M2M connectivity that extends out to others in the supply chain but stops at the customer service portal). As I place people in this brave new world, I have identified several key traits that they must possess. I’ve come up with a five-point plan so that you can not only use these traits to make your next hire—but to make the next hire that fits with your culture and IOT strategy.
You’ve heard that every business is a digital business, right? Well every IOT person is a business-person first and foremost as a result. Make sure your recruits can interact with business partners effectively (ask what projects they’ve worked on and about the length and depth of their interaction with its executive sponsor) and the business problems that they have solved with their IT prowess.
Even if the candidate has only worked on so-called terrestrial IT projects, take the time to understand how deep her understanding is of cloud-based technologies in her industry. If you’ve got an entry-level IOT person, they may not have much experience in the IOT—but they should be able to converse intelligently about Cloud-based systems and the business opportunities they hold.
Your senior people will probably have a wider view, with an awareness (if not a command) of what’s going on in the Industrial Internet and the customer-facing nodes on the IOT. At the end of the day, creating cloud-based business solutions with links to machines, systems or objects is what it’s all about.
One of the biggest issues is the security threats inherent in the IOT. Your junior-to-senior level people must have a firm grasp of data security in their industry—and must be actively involved in following the ways that the IOT community is battling them.
Here’s one I get all of the time—“people who are great at leading IOT strategy aren’t necessarily the most personable of people.” That’s simply not true. The IOT consultants and professionals I work with are aware that they are part of a business ecosystem—and that their success boils down to not only survival of the fittest but the survival of the most collaborative, the most innovative, the most respectful of what others in the organization bring to the table. Listen, your IOT projects might be the priciest items on your CEO’s docket this quarter. And where there is much opportunity, a ton of budget and a lot at stake (market differentiation anyone?) there are going to be some interpersonal challenges to overcome. Find out if your prospective recruit can tell you about a “people-problem” he solved or ask about “a time when you had to play politics at work.” This is code for a time when they had to use EI skills to get something done.
I am tired of the cliché about the unbalanced, uber-creative innovator (you know, the nutty professor type) not being able to buckle down and get things done. Your IOT recruits should have big ideas but the ability to place their attention on the minutiae of a key IOT project. These skills are not mutually exclusive in the best candidates I’ve seen. In fact, the innovators are often the best at making sure they have team members who love to juggle the details—and know when to escalate a problem to the appropriate person. Ask if your candidate has had the opportunity to bring an idea to the project phase and how it went. Also ask about what he thinks the “next great IOT frontier” might be. If he is not thinking about this, he’s not energized by his own industry. And those are the people who can drive IOT change for you.
If you want help finding the people who encapsulate the skills (dare we say gifts) that will supercharge your IOT strategy, Click here to schedule a call.
What options do you have for remotely monitoring Water and Fluids with Industrial IoT sensor telemetry?
IIoT or Industrial IoT (Internet of Things) is everywhere. It’s across all industries, from high tech transport, to natural resources and governments. IIoT software and hardware is deployed for numerous, varying applications, and it’s critical to understand just what the customer needs. Especially since the customer can’t always articulate exactly what the remote monitoring and sensor telemetry should do. According to a study performed by Verizon: the worldwide Internet of Things market spend will grow from $591.7 billion in 2014 to $1.3 trillion in 2019. That’s tremendous.
One of the areas that we’ve seen recent growth is water and fluid monitoring. Water comes to us as a life sustaining asset and also as a force of destruction. The utility of water needs to be measured and monitored in order to effectively and efficiently use our greatest natural resource. Similarly, monitoring the destructive force of water can be just as important. Let’s talk about the different ways that you can measure and monitor water!
Flow meters calculate the amount of water that flows through them. Flow meters are everywhere from your house to your office, to anywhere and everywhere water is used. Measuring water flow is a need recognized across industries, from agriculture to commercial, pharmaceuticals, and oil and gas. Flow meters in an IIoT solution provide not only a total flow amount, but allow you to utilize real time data to predict and adjust consumption. Further still, real time analysis allows immediate recognition of catastrophic events such as a burst pipe. The analysis will be drawn out further to establish predictive failure behavior and potentially prevent massive water loss issues like the ones that happened in Los Angeles and Hollywood Hills.
Almost certainly this one is all about protecting assets. There are essentially four ways that we have used to detect presence, quantity, volume, and levels of water. Each of these fits quite well for a particular purpose. They also compliment each other nicely!
Presence of Water: The Rope Sensor
Rope sensors are great and they come in a variety of lengths. A rope sensor will tell you if you have water present at any point along the sensor. Imagine a large trailer with rope sensors running along the bottom of the trailer. If you have a spill in that trailer, truck, or vehicle and any fluid reaches the rope sensor, then you’ll receive an alert and immediately know there’s a problem.
Rope sensors are also great for flood detection. Because you can purchase these sensors in practically any length, you can lay them across a flood channel. If any portion of that rope sensor gets wet then you know you have water present. However, in terms of flood detection rope sensors will tell you if there is water, but they won’t tell you how much.
Presence of Water: Yes or No
If your rope sensor went off on a flood channel you might want to know how much water is flowing through. Depending on the lay of the land there are a number of different applications that we use to provide this information.
Ultrasonic, Ultrasound, Pulse, and Radar Sensors
If you have a fixed structure next to or going over a flood channel then a great solution is an ultrasonic sensor. Essentially, once the sensor is fixed in place it will continuously ping the ground. When the reading between the sensor and the ground becomes more compact, you can calculate that distance and in turn determine how much water is flowing through the channel and the flood level. Also note that radar and ultrasonic fluid level sensors are quite useful for remotely monitoring levels and volumes of liquid products in assets like tanks!
Another way that we have measured quantity of water is by using a pressure transducer. A sensor with a membrane sits at the bottom of a water well, lake, or a reservoir, or a flood channel. As the water increases above the sensor so does the pressure on the sensor’s membrane. The higher the pressure the more water you have moving through!
Making things Digital
Water metering and water detection are now all IIoT solutions. All of these meters / sensors connect to sensor hub connector hardware that sends data out into the internets and into a cloud data analysis solution. Whether you’re monitoring agriculture / viticulture, oil / gas / mining, municipal water treatment facilities or other water plants, nowadays you can obtain a cost-effective, rapidly deployable monitoring solution.
Starting this week, we're going to compile the best of IoT Central membership content in our new Bi-Weekly Digest. If you're interested in being featured, we always welcome your contributions on all things IoT Infrastructure, IoT Application Development, IoT Data and IoT Security, and more. All members can post on IoT Central. Consider contributing today. Our guidelines are here.
By Marcus Jensen
Technological advancements and the surge of mobile platforms have announced the new era of global economy, and the booming app market is expanding with lightning speed. Big Data has a powerful influence on business operation on a global scale, although the rates of adoption are not that convincing. What is more, the advent of the Internet of Things (IoT) means that it will not be long before all household items are equipped with wireless capacity. For an app market, which relies heavily on knowledge and data, particularly user feedback, this has strong implications. It is time to think big in terms of data.
By Asim Roy
As we move towards widespread deployment of sensor-based technologies, three issues come to the fore: (1) many of the these applications will need machine learning to be localized and personalized, (2) machine learning needs to be simplified and automated, and (3) machine learning needs to be hardware-based.
By John Berard
The Online Trust Alliance (OTA) has been at the forefront of helping build consumer confidence in the technology products that have helped remake our day. So, it was no surprise it moved to create a set of guidelines around the products and services that are part of the Internet of Things (IoT).
The Internet of Things has been labeled as the next ‘Industrial Revolution,’ by many experts that have predicted how it will be able to change the way various industries, businesses, consumers, and even governments, interact with the physical world in the future. Here are other ways on how the IoT will impact, challenge, and change business in 2016.
By David Oro
It’s still early days for the IoT but everyday a little part of its burgeoning ecosystem becomes a factor in our lives, whether we know it or not. From industrial tools to farming to cities to grocery aisles and everything in between, the IoT is there. Here are 10 IoT case studies that show just where some of these technologies and applications are being applied.
Guest blog post by Eduardo Siman
If you follow news about the Internet of Things, you will have read quite a few articles that attempt to predict the number of connected devices by the year 2020. Eduardo breaks it down with this chart.
If you follow news about the Internet of Things, you will have read quite a few articles that attempt to predict the number of connected devices by the year 2020.
The chart displayed above, from iot-analytics.com gives a nice comparison of some of the predictions from major IoT players like Cisco and Ericsson as well as IT research companies like Gartner and IDC have made recently. The range for 2020 is between 18 Billion and 50 Billion.
The first thing we notice in the chart is - they don’t all start in the same place! The initiation point ranges from 6 B to 14 B for 2014. That’s like having 10 stock analysts predict the future price of a stock in 5 years and all 10 have a different price on their Bloomberg terminal. Certainly a cause for worry. The second key point is that the rate of growth varies tremendously - from 14% to 23%. If this were a discounted cash flow model, and these ranges were being used to predict sales growth, the model wouldn’t have much validity would it?
So why don’t we, for the fun of it, try to do the math on this one? Let's start by getting one thing straight - we will try to calculate the maximum number of connected devices by 2020. Not the mean or median or most likely - the maximum. This will make our choice of numbers way easier - we will choose the highest plausible number for each part of our calculation. Ok let's get started.
Part I - The Humans and their Toys
There are currently 7.4 Billion people on Earth. (http://www.worldometers.info/world-population/) There are 3.36 Billion people connected to the Internet (http://www.internetworldstats.com/stats.htm). In addition, there are around 2 Billion smartphones in the wild - give or take a few million. (http://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/) So - using the “maximum” adage we discussed earlier - lets assume the following:
1) By 2020, each person who currently owns a smartphone will also own a laptop or some other kind of personal computer, including tablets. (This is NOT true, especially in Sub-Saharan Africa and Latin America where smartphones tend to be the only device people own, but its safe to say this would represent a reasonable Maximum)
2) The whole population of the Earth will have access to the internet by 2020. Again - who the hell knows - but its a good maximum. The world population will be around 7.7 Billion (http://www.worldometers.info/world-population/) at that time - at least that is the highest number I could fine from a reputable looking source.
And now for the real wild assumptions. Lets say that the ratio of A) peeps who own a smartphone to B) peeps who have internet will stay the same. Now that requires an intellectual leap of faith. We know internet access will not go down, but smartphone access might hit a peak at some point before 2020. Here we are assuming it doesn’t. More people get internet, and thus more people get smartphones. Now - when we combine B) with 1) and 2) we are saying that (2/3.36)*7.7 = 4.58 B people will have a smartphone and a personal computer by 2020. So this brings us to 9.16 Billion connected devices that people use to access the internet by 2020.
Part II - The Industrial IoT
But what about the Industrial Internet of Things? Arduino, Raspberry Pi, sensors made by Ericsson, routers made by Cisco, drones, cars and planes? Well we can’t calculate that one based on the population of earth. But what about silicon chip manufacturing? Lets make some more assumptions:
3) This one is massive. Lets say 35% of all silicon chip shipments in 2020 will go into some kind of IoT device (not including those used by people directly). The raspberry pi 2 has a 900 MHz quad-core ARM Cortex A7 processor. Now suspend disbelief and imagine that every single factor floor in the world that makes silicon chips and processors will be rolling out this processor’s descendants in 2020. According to SEMI, in Q3 2015 there were 2,591 Millions of Square Inches (MSI) of silicon materials shipped. In June 2015, Freescale semiconductors revealed the i.MX 6Dual SCM processor - which measures in at 17mm X 14mm X height. (http://www.zdnet.com/article/freescale-launches-smallest-ever-dime-sized-iot-processor/) That is .66929 Inches * .551 Inches = .3688 square inches. You can make 7.025 Billion (2.591/.3688) of these processors in one quarter in 2016.
4) Great, so let's say this becomes the norm in 2020. If these IoT chips represented 35% of all the silicon chips produced in the world, that would be .35 * 7.025 Billion in one quarter and .35 * 28.1 Billion = 9.835 Billion in one year.
5) For the sake of keeping this article at less than a million pages, let's say that the number in 4) will be the number of Industrial IoT chips we have in the wild in 2020.
Great. We are done! Adding the results from part I and II we get: 9.16 Billion + 9.835 Billion = 18.995 Billion connected devices by 2020
Hey that’s just barely above the lowest number on the chart! Either our calculations are too conservative or everyone else is too optimistic.
Of course you could make the argument that using 35% in assumption 3 is a bit arbitrary. Granted. But given the fact that WSTS said smartphones and computers alone made up for 65% of all semiconductors in 2014 (blog.semiconductors.org) it doesn’t seem like such a crazy assumption. Going with the mantra of reaching the absolute maximum number given somewhat reasonable assumptions, we could say 50% (gasp!) of all semiconductor production will go towards industrial IoT in 2020 which would lead to 14.05 + 9.16 = 23.21 Billion devices. That’s still 5 billion less than the second lowest estimate (from IT research group IDC) on the chart.
Conclusion: If someone tells you there will be 50 Billion connected devices by 2020, tell them to read this article.
Originally posted on Data Science Central
It’s still early days for the IoT but everyday a little part of its burgeoning ecosystem becomes a factor in our lives, whether we know it or not. From industrial tools to farming to cities to grocery aisles and everything in between, the IoT is there. Here are 10 IoT case studies that show just where some of these technologies and applications are being applied.
1) Bytes and Bushels - Farming on an Industrial Scale
Farming and IoT seem to be the leading implementations on an industrial scale. I wrote on this last year, but the two New York Times pieces on Tom Farms, a multi-generation, family owned farm in North Indiana, is still one of the most comprehensive, and personal, IoT case studies I’ve seen to date. And it’s not just words, be sure to watch the multimedia video. Stories are here and here.
2) The Tesla IoT Car: Case Study
MITCNC, the MIT Club of Northern California, is the regional alumni club of Massachusetts Institute of Technology in Northern California. They have a blog at https://blogmitcnc.org/ where they post on emerging trends and discoveries in science and technology. Displaying their best Car & Driver reviewer, while keeping their propeller hats on to look at IoT, data, privacy and security, this is a unique look at the most talked about car this century. Story here.
3) GE’s Big Bet on Data and Analytics
Here’s a timely new case study from MIT Sloan Management Review that looks at how GE is seeking opportunities in the Internet of Things with industrial analytics. GE is leading the development of a new breed of operational technology (OT) that literally sits on top of industrial machinery. Long known as the technology that controls and monitors machines, OT now goes beyond these functions by connecting machines via the cloud and using data analytics to help predict breakdowns and assess the machines’ overall health. I’m really glad to see someone dive into this as I think GE’s big swing is still not yet fully appreciated. It soon will be. Case study here.
4) Can a Cow be an IoT Platform
One of my favorite stories on the IoT is penned by Bill Vorhies, President & Chief Data Scientist at Data-Magnum. It’s been on IoT Central for a while now, but I thought it important to include in this collection. Bill’s report recaps Microsoft’s Joseph Sirosh for a surprising conversation about a farmer’s dilemma, a professor’s ingenuity and how cloud, data and devices came together to fundamentally re-imagine an age old way of doing business. You can read Bill’s post here or watch the entertaining video below.
5) Global Smart Cities
In 2013, the UK government’s Department for Business, Innovation and Skills commissioned a study that looked at six global cities that are paving the way in smart city investment. It looked at how Chicago, Rio De Janeiro, Stockholm, Boston, Barcelona and Hong Kong tackled particular challenges when responding to the opportunities that a ‘smart city’ and private sector innovators might bring. Worth a read. Case study is here.
Photo courtesy of TVILIGHT BV
6) PTC Thingworx - All Traffic Solutions
Thingworx, a PTC company, has an IoT platform designed to build and run IoT applications, and enable customers to transform their products and services, innovate and unlock new business models. They have a plethora of case studies, but one that caught my eye was on All Traffic Solutions. The company has been at the forefront of the wireless market for over a decade but now sells its traffic safety products throughout the United States and 20 countries globally. That reach has provided a good deal of field-based insight that, over the last five years, All Traffic Solutions has channeled into developing innovative new web-based and IoT-connected signs that are incredibly smart, yet simple to use, adding significant value to the company’s hardware for its customers. Case study here.
7) Stanley Black and Decker
Managing a complex manufacturing facility is a challenge and this case study from Cisco showcases how Stanley Black & Decker operates one of its largest tool manufacturing plants in Reynosa, Mexico, which serves the North American market. Opened in 2005, the Reynosa plant primarily manufactures dozens of products, such as jigsaws, planers, cordless drills, floodlights, and screwdrivers for the DeWALT brand and lawnmowers for the Black & Decker brand. With 40 multiproduct manufacturing lines and thousands of employees, the plant produces millions of power tools each year. This case study shows how IoT technologies help with production visibility and flexibility. Case study here. Great video below.
8) SLAC National Accelerator Laboratory
Since its opening in 1962, SLAC National Accelerator Laboratory has been helping create the future. Six scientists have been awarded Nobel prizes for work done at SLAC, and more than 1,000 scientific papers are published each year based on research at the Palo Alto-based lab. The team is now working on a future plan to take data from all intelligent sensors that monitor the vast systems at SLAC and feed the data into the cloud where it can be processed, analyzed, and delivered back to control engineers. Case study here.
9) The Supermarket of the Future: Designing for humans
It’s not just about technology, but applying technology to improve the human experience. This case study on Italy’s biggest grocery cooperative shows how it might be done...and I like it. Coop Italia’s “supermarket of the future,” designed by Carlo Ratti, has won rave reviews, thanks to a digital design that created a more human shopping experience using a range of off-the-shelf technology. Read more about it here.
10) IoT for Electronic Medical Records
The need to cut cost, improve medical care, and adopt electronic medical records (EMR) is driving hospitals to implement information technology solutions that streamline procedures such as billing, medical imaging, and electronic medical records processing. In this case study from Intel, it shows how their partner NEXCOM developed a medical informatics solution based on technologies from the Internet of Things to help overcome communication barriers between medical devices and IT networks. The solution turns medical device data into electronic medical records and sends them to the hospital’s private cloud, where data analytics can be performed to better evaluate a patient’s condition. Read more about it here.
Matt notes "The IoT today is largely at this inflection point where “the future is already here but it is not evenly distributed”. From ingestibles, wearables, AR/VR headsets to connected homes and factories, drones, autonomous cars and smart cities, a whole new world (and computing paradigm) is emerging in front of us. But as of right now, it just feels a little patchy, and it doesn’t always look good, or work great – yet."
The chart above is great, but it's his thoughtful and detailed blog post that's definitely worth your time. He covers the booming investment, the seemingly glacial pace for the end user, jockeying by large corporations, and what it all means for start-ups.
Guest blog post by Bernard Marr
What do you think of when you think of "big data"?
For many, it's a nebulous term that invokes images of huge server farms humming away. Or perhaps you think of receiving some kind of personalized advertisement from a retailer.
But big data is so much deeper and broader than that. I believe there are 10 major areas in which big data is currently being used to excellent advantage in practice - but within those arenas, data can be put to almost any purpose.
1. Understanding and Targeting Customers
This is one of the biggest and most publicized areas of big data use today. Here, big data is used to better understand customers and their behaviors and preferences. Companies are keen to expand their traditional data sets with social media data, browser logs as well as text analytics and sensor data to get a more complete picture of their customers. The big objective, in many cases, is to create predictive models.
You might remember the example of U.S. retailer Target, who is now able to very accurately predict when one of their customers will expect a baby. Using big data, Telecom companies can now better predict customer churn; Wal-Mart can predict what products will sell; and car insurance companies understand how well their customers actually drive.
Ski resorts are even using data to understand and target their patrons. RFID tags inserted into lift tickets can cut back on fraud and wait times at the lifts, as well as help ski resorts understand traffic patterns, which lifts and runs are most popular at which times of day, and even help track the movements of an individual skier if he were to become lost.
Imagine being an avid skier and receiving customized invitations from your favorite resort when there's fresh powder on your favorite run, or text alerts letting you know when the lift lines are shortest. They've also taken the data to the people, providing websites and apps that will display your day's stats, from how many runs you slalomed to how many vertical feet you traversed, which you can then share on social media or use to compete with family and friends.
Even government election campaigns can be optimized using big data analytics. Some believe Obama's win after the 2012 presidential election campaign was due to his team's superior ability to use big data analytics.
2. Understanding and Optimizing Business Processes
Big data is also increasingly used to optimize business processes. Retailers are able to optimize their stock based on predictions generated from social media data, web search trends and weather forecasts.
One particular business process that is seeing a lot of big data analytics is supply chain or delivery route optimization. Here, geographic positioning and radio frequency identification sensors are used to track goods or delivery vehicles and optimize routes by integrating live traffic data, etc. HR business processes are also being improved using big data analytics.
This includes the optimization of talent acquisition - Moneyball style - as well as the measurement of company culture and staff engagement using big data tools. For example, one company, Sociometric Solutions, puts sensors into employee name badges that can detect social dynamics in the workplace. The sensors report on how employees move around the workplace, with whom they speak, and even the tone of voice they use when communicating.
One of the company's clients, Bank of America, noticed that its top performing employees at call centers were those who took breaks together. They instituted group break policies and performance improved 23 percent.
You may have seen the RFID tags you can attach to things like your phone, your keys, or your glasses, which can then help you locate those things when they inevitably get lost. But suppose you could take that technology to the next level and createsmart labels that could stick on practically anything. Plus, they can tell you a lot more than just where a thing is; they can tell you its temperature, the moisture level, whether or not it's moving, and more.
Suddenly, this unlocks a whole new realm of "small data;" if big data is looking at vast quantities of information and analyzing it for patterns, then small data is about looking at the data for an individual product - say, a container of yogurt in a shipment - and being able to know if it's likely to go off before it reaches the store.
This part of the Internet of Things holds incredible promise for improving everything from logistics to health care, and I believe we're still just on the cusp of understanding what this incredible technology can do - as when electricity was only used to power light bulbs.
3. Personal Quantification and Performance Optimization
Big data is not just for companies and governments but also for all of us individually. We can now benefit from the data generated from wearable devices such as smart watches or smart bracelets. Take the Up band from Jawbone as an example: the armband collects data on our calorie consumption, activity levels, and our sleep patterns. While it gives individuals rich insights, the real value is in analyzing the collective data.
In Jawbone's case, the company now collects 60 years worth of sleep data every night. Analyzing such volumes of data will bring entirely new insights that it can feed back to individual users.
The other area where we benefit from big data analytics is finding love - online this is. Most online dating sites apply big data tools and algorithms to find us the most appropriate matches.
4. Improving Healthcare and Public Health
The computing power of big data analytics enables us to decode entire DNA strings in minutes and will allow us to find new cures and better understand and predict disease patterns. Just think of what happens when all the individual data from smart watches and wearable devices can be used to apply it to millions of people and their various diseases. The clinical trials of the future won't be limited by small sample sizes but could potentially include everyone!
Apple's new health app, called ResearchKit, has effectively just turned your phone into a biomedical research device. Researchers can now create studies through which they collect data and input from users phones to compile data for health studies. Your phone might track how many steps you take in a day, or prompt you to answer questions about how you feel after your chemo, or how your Parkinson's disease is progressing. It's hoped that making the process easier and more automatic will dramatically increase the number of participants a study can attract as well as the fidelity of the data.
Big data techniques are already being used to monitor babies in a specialist premature and sick baby unit. By recording and analyzing every heartbeat and breathing pattern of every baby, the unit was able to develop algorithms that can now predict infections 24 hours before any physical symptoms appear. That way, the team can intervene early and save fragile babies in an environment where every hour counts.
What's more, big data analytics allow us to monitor and predict the developments of epidemics and disease outbreaks. Integrating data from medical records with social media analytics enables us to monitor flu outbreaks in real-time, simply by listening to what people are saying, i.e. "Feeling rubbish today - in bed with a cold".
Of course, while much has been made in the past of Google's ability to predict flu outbreaks based on search traffic, their model didn't work in 2014. Google itself admits that just because you search for "flu symptoms," it doesn't mean you're sick.
5. Improving Sports Performance
Most elite sports have now embraced big data analytics. We have the IBM SlamTracker tool for tennis tournaments; we use video analytics that track the performance of every player in a football or baseball game, and sensor technology in sports equipment such as basket balls or golf clubs allows us to get feedback (via smart phones and cloud servers) on our game and how to improve it. Many elite sports teams also track athletes outside of the sporting environment - using smart technology to track nutrition and sleep, as well as social media conversations to monitor emotional wellbeing.
The NFL has developed its own platform of applications to assist all 32 teams in making the best decisions based on everything from the condition of the grass on the field, to the weather, to statistics about an individual player's performance while in university. It is all in the name of strategy as well as reducing player injuries.
One of the really cool new things I have come across is a smart yoga mat: sensors embedded in the mat will be able to provide feedback on your postures, score your practice, and even guide you through an at-home practice.
6. Improving Science and Research
Science and research is currently being transformed by the new possibilities big data brings. Take, for example, CERN, the nuclear physics lab with its Large Hadron Collider, the world's largest and most powerful particle accelerator. Experiments to unlock the secrets of our universe - how it started and works - generate huge amounts of data.
The CERN data center has 65,000 processors to analyze its 30 petabytes of data. However, it uses the computing powers of thousands of computers distributed across 150 data centers worldwide to analyze the data. Such computing powers can be leveraged to transform so many other areas of science and research.
The computing power of big data could also be applied to any set of data, opening up new sources to scientists. Census data and other government collected data can more easily be accessed and analyzed by researchers to create bigger and better pictures of our health and social sciences.
7. Optimizing Machine and Device Performance
Big data analytics help machines and devices become smarter and more autonomous. For example, big data tools are used to operate Google's self-driving car. The Toyota Prius is fitted with cameras, GPS as well as powerful computers and sensors to safely drive on the road without the intervention of human beings. We can even use big data tools to optimize the performance of computers and data warehouses.
Xcel Energy initiated one of the first ever tests of a " smart grid" in Boulder, Colorado, installing smart meters on customers' homes that would allow them to log into a website and see their energy usage in real time. The smart grid would also theoretically allow power companies to predict usage in order to plan for future infrastructure needs and prevent brown out scenarios.
In Ireland, grocery chain Tescos has its warehouse employees wear armbands that track the goods they take from the shelves, distributes tasks, and even forecasts completion time for a job.
8. Improving Security and Law Enforcement
Big data is applied heavily in improving security and enabling law enforcement. I am sure you are aware of the revelations that the National Security Agency (NSA) in the U.S. uses big data analytics to foil terrorist plots (and maybe spy on us). Others use big data techniques to detect and prevent cyber attacks. Police forces use big data tools to catch criminals and even predict criminal activity and credit card companies use big data use it to detect fraudulent transactions.
In February 2014, the Chicago Police Department sent uniformed officers to make "custom notification" visits to individuals they had identified as likely to commit a crime through a computer generated list. The idea was to prevent crime by providing certain individuals with information about job training programs, or let them know about increased penalties for people with certain backgrounds. But many community groups cried foul and called the practice profiling.
9. Improving and Optimizing Cities and Countries
Big data is used to improve many aspects of our cities and countries. For example, it allows cities to optimize traffic flows based on real time traffic information as well as social media and weather data. A number of cities are currently piloting big data analytics with the aim of turning themselves into Smart Cities, where the transport infrastructure and utility processes are all joined up. Where a bus would wait for a delayed train and where traffic signals predict traffic volumes and operate to minimize jams.
The city of Long Beach, California is using smart water meters to detect illegal watering in real time and have been used to help some homeowners cut their water usage by as much as 80 percent. That's vital when the state is going through its worst drought in recorded history and the governor has enacted the first-ever state-wide water restrictions.
Los Angeles uses data from magnetic road sensors and traffic cameras to control traffic lights and thus the flow (or congestion) of traffic around the city. The computerized system controls 4,500 traffic signals around the city and has reduced traffic congestion by an estimated 16 percent.
A tech startup called Veniam is testing a new way to create mobile wi-fi hotspots all over the city in Porto, Portugal. More than 600 city buses and taxis have been equipped with wifi transmitters, creating the largest free wi-fi hotspot in the world. Veniam sells the routers and service to the city, which in turn provides the wi-fi free to citizens, like a public utility. In exchange, the city gets an enormous amount of data - with the idea being that the data can be used to offset the cost of the wi-fi in other areas. For example, in Porto, sensors tell the city's waste management department when dumpsters are full, so they don't waste time, man hours, or fuel emptying containers that are only partly full.
10. Financial Trading
My final category of big data application comes from financial trading. High-Frequency Trading (HFT) is an area where big data finds a lot of use today. Here, big data algorithms are used to make trading decisions. Today, the majority of equity trading now takes place via data algorithms that increasingly take into account signals from social media networks and news websites to make, buy and sell decisions in split seconds.
Computers are programmed with complex algorithms that scan markets for a set of customizable conditions and search for trading opportunities. The programs can be designed to work with no human interaction or with human interaction, depending on the needs and desires of the client.
The most sophisticated of these programs are now also designed to change as markets change, rather than being hardcoded.
For me, the 10 categories I have outlined here represent the areas in which big data is applied the most. Of course there are so many other applications of big data and there will be many new categories as the tools become more widespread.
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