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. With only a handful of lines of code added to any connected device, Buddy claims that they can host the telemetry data generated by these devices in various regions around the world, as well shape and query the data prior to pushing it into any business intelligence (BI) toolset desired. In addition to telemetry management, Buddy enables M2M scenarios by exposing query results on the telemetry stream via real-time RESTful APIs, as well as a messaging mechanism for external control of devices.
Prior to IoT World, I sent Buddy CEO and Co-Founder Dave McLauchlan a few questions. Here's what he had to say.
What is the Buddy Platform?
Buddy Platform is a highly secure, cloud-based platform that takes and processes raw data from hundreds of millions of connected devices, appliances and sensors, then makes it accessible in real-time for businesses. The platform has significant capabilities to manage billions of transactions across millions of devices in real time and at a global scale.
Buddy’s enterprise-ready solution allows organizations to own the data without investing in data infrastructure. In many cases the companies that make devices with the most potential in their device data are not traditional data companies - they make appliances, vehicles, heavy equipment in farming, mining and manufacturing. These organizations are able to speed up their time to market and skip building out an internal data infrastructure team that can be expensive and resource heavy.
In preparation for massive IoT growth in the next decade, Buddy is focused on how internet connected devices can provide enormous amounts of valuable data to improve and enhance insights and actions across industries. From mining, manufacturing, energy and resources to connected cities, our technology can help businesses improve performance, safety, and functionality across operations.
We are based in Seattle, WA and have an engineering office in Adelaide, South Australia. In December 2015 we listed on the Australian Securities Exchange under the ticker symbol BUD.
Tell us how mobile is the gateway and hub for IoT.
There is a very strong correlation in the consumer IoT space between mobile applications and IoT devices because mobile apps are the control point. You could say an IoT platform isn’t complete without good, strong mobile support. This approach is a main differentiator for Buddy, our system is a platform for Things and Apps, you can see data from both come through your Buddy account and have a more unified view. Given our heritage as a Mobile as a Backend service, and our capabilities now in IoT we are uniquely positioned against others in the space.
What trends are you seeing in the silicon industry to address IoT?
More and more silicon organizations, companies and manufacturers are looking to get deeper integration with device management through data management, so that when they sell silicon, the data can be deployed and managed for the customer. Increasingly, customers of silicon vendors are looking for solutions that include a robust, scalable and secure cloud platform. We think this trend will continue, and that has already led to great partnerships between Buddy and companies like Marvell and Gimbal.
Much of the attention in IoT is focused on consumer technologies, but the real action, often unrealized by the average person, is happening in the industrial sector. What are you most excited about in IoT and what can we expect from it?
IoT is still managing it’s way through an enormous hype cycle and it’s true, things like wearables and home automation garner much of the attention. While these areas are certainly very exciting because they are the most tangible to people, what’s happening in industrial IOT is just as exciting in that it will also be powering great new experiences and services, but as an enabler rather than being front and center on store shelves. We are seeing great opportunity in the energy sector for IoT, and how that translates into business value for utilities, cities and buildings. Everything from solar panels, to automated meters are becoming connected which means governments, real estate managers and homeowners have a better view into how they are using and producing energy. That translates into cost savings, efficiency and increased awareness that can have real impact in the lives of people, and the health of our environment and planet.
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.
At a fundamental and simplistic level the Internet of Things refers to 'physical objects which linked via wired or wireless networks'
These physical objects could be anything (such as medical machines, vehicles, building systems, signage, toasters, smoke alarms, temperature sensors, weather monitors, intelligent tags or rubbish bins for example). Almost any object, in any sector, in any location could potentially join the Internet of Things, so its no wonder that Gartner predict there will be 50 billion devices connected by 2020 (and other analysts estimate several orders of magnitude more).
Typically the Internet of Things is used to gather data and insight, find efficiency, automate tasks or improve an experience or service. At Smarter Technology Solutions (STS) we put this down to a simple formula, with greater insight, comes better decisions.
I know what you're thinking, why would you connect an object like a rubbish bin to the Internet?
Well its a simple example but it has tremendous flow on effects. Simply tracking the fill level of a rubbish bin using a smart sensor, councils and waste providers can find out a few important facts such as fill-level trends, how often the bin really needs emptying and when, to better plan waste collection services (eg timing of bin collection near food outlets to avoid lunchtimes) and to identify areas that may need more/less bins (to assist with city/service planning).
By collecting just the fill level data of a waste bin the following benefits could be attained:
Reduction in cost as less bin collections = less waste trucks on the road, no unnecessary collections for a bin that's 20% full, less labour to complete waste collection. This also provides a level of operational efficiency and optimized processes.
Environmental benefit - where waste is not overflowing and truck usage is reduced, flow on environmental impact, pollution and fuel consumption is minimized. By ensuring waste bins are placed in convenient locations, littering and scattered waste is also minimized.
Service improvements - truck collection routes can be optimized, waste bins can be collected at convenient times and planning of future/additional services can be amended as the data to trend and verify assumptions is available.
More complex examples of IoT include:
Intelligent transport systems which update digital signage on the highway and adjusts the traffic lights in real time to divert traffic, optimise traffic flow and reduce congestion;
A farm which uses sensors to measure soil moisture, chemical levels and weather patterns, adjusting the watering and treatment schedules accordingly;
The building which draws the blinds to block out the afternoon sun, reducing the need to consume more power cooling the building and to keep the environment comfortable;
Health-care devices which monitor patients and auto-alert medical practitioners once certain symptoms or attributes are detected;
Trucks which automatically detect mechanical anomalies and auto schedule themselves in for preventative maintenance once they reach certain thresholds;
Asset tracking of fleet vehicles within a services company which provides operations staff with fleet visibility to quickly dispatch the closest resource to a job based on proximity to the next task;
Water/gas/electric meters which sends in their own reading in on a monthly basis and trends analysis which can detect potential water/gas leaks; or
A retail store which analyses your in-store behavior or purchasing patterns and recommend products to you based on previous choices and your personal preferences.
At Smarter Technology Solutions we specialize in consulting with organizations to understand the benefits of IoT, design best fit solutions, engineer and implement solutions as well as supporting the ongoing support needs of the organization. This results in 3 key outcomes:
Discovery of New Opportunities - With better visibility, trends, opportunities, correlations and inefficiencies can be understood. From this, products, services and business models can be adjusted or changed to achieve competitive advantage.
Improved Efficiency - By identifying inefficiencies in existing business practices, work-flows can be improved and more automated services can be provided.
Improved Services - With trends and real time data businesses are able make smarter decisions and alter the way you services are delivered.
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.
Recent attacks, like the Christmas 2015 attack on the Ukraine power grid, have shown that the Internet of Things possesses severe vulnerabilities. These weak points can be everything from back doors that allow a hacker access to a system to lack of proper use by untrained workers. If your business uses IoT devices, there’s a good chance they are not secure.
Why are so many systems left vulnerable? Weaknesses often come from the same set of five drivers:
Whether your company is struggling because your devices were deployed too quickly or operational costs constraints got in the way, your team must take measures to fix security risks. Here are four security flaws:
1. Lack of Encryption
Any device that is connected to the Internet to relay data needs encryption. When communication between devices and facility machines are now encrypted, it provides a doorway for hackers to send malicious updates, steal data, and even take control of the system.
In 2014, an Israeli security firm took control of cars using a specific connected telematics device that failed to use proper encryption.
2. Failing to Install Updates
Once you have a machine-to-machine communication system working properly, it can be easy to forget to install the necessary updates to keep the network secure.
Yet, hackers are constantly updating their strategies and tactics. Failing to install updates and patches leaves your system vulnerable.
Even if you’re worried about breaking integrations between systems, you should at the least install every security update released by the vendor. These updates are specifically designed to address vulnerabilities discovered in your devices. After all, if your vendor releases a security update, it’s because they found a problem.
You also should know that updates and patches are not always the final solution to security vulnerabilities. Unfortunately, many manufacturers are not able or willing to provide the necessary support to continue updating their devices.
To avoid this risk, shop carefully for systems that provide updates and are backed by a trusted company.
3. Poorly Built Networks
The modern industrial network is designed to get tasks done. If the design focuses too much on completing that task, it will leave weak points in security. Things that are obvious when building IT networks are sometimes less obvious when creating industrial DNP3 and other network architecture.
The solution to this risk is fairly simple. Those tasked with building industrial networks need to ensure they are partnering with IT professionals to build networks that are safer from attacks. Security features, like deep packet inspection and network segmentation, should be in place from the beginning.
4. Sensors Outside of the Company's Control
Most of the sensors and other connected pieces that make up a network are controlled by the company. But for some companies, that is not the case. For example, power companies have sensors in their customer's homes.
Sensors outside of the company's immediate control are hard to secure, which gives hackers access. Currently, cloud-based security using public key services to authenticate devices may be the best solution to this problem.
Don't Take The Risk
Industrial security breaches can cause devastating consequences. Therefore, the above risks need to be addressed.
As more industrial facilities rely on the Internet of Things, it's important for company teams to be aware of the potential vulnerabilities. Take security into full consideration.
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?
Three things:
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.
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.
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,
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;
Editors Note: Members of IoT Central are encouraged to participate in Ventana Research's study. The author of the blog shares details below.
The emerging Internet of Things (IoT) is an extension of digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This innovation means that virtually any device can generate and transmit data about its operations – data to which analytics can be applied to facilitate monitoring and a range of automatic functions. To do these tasks IoT requires what Ventana Research calls operational intelligence (OI), a discipline that has evolved from the capture and analysis of instrumentation, networking and machine-to-machine interactions of many types. We define operational intelligence as a set of event-centered information and analytic processes operating across an organization that enable people to use that event information to take effective actions and make optimal decisions. Ventana Research first began covering operational intelligence over a decade ago.
In many industries, organizations can gain competitive advantage if they reduce the elapsed time between an event occurring and actions taken or decisions made in response to it. Existing business intelligence (BI) tools provide useful analysis of and reporting on data drawn from previously recorded transactions, but to improve competitiveness and maximize efficiencies organizations are concluding that employees and processes in IT, business operations and front-line customer sales, service and support also need to be able to detect and respond to events as they happen.
Both business objectives and regulations are driving demand for new operational intelligence technology and practices. By using them many activities can be managed better, among them manufacturing, customer engagement processes, algorithmic trading, dynamic pricing, yield management, risk management, security, fraud detection, surveillance, supply chain and call center optimization, online commerce and gaming. Success in efforts to combat money laundering, terrorism or other criminal behavior also depends on reducing information latency through the application of new techniques.
The evolution of operational intelligence, especially in conjunction with IoT, is encouraging companies to revisit their priorities and spending for information technology and application management. However, sorting out the range of options poses a challenge for both business and IT leaders. Some see potential value in expanding their network infrastructure to support OI. Others are implementing event processing (EP) systems that employ new technology to detect meaningful patterns, anomalies and relationships among events. Increasingly, organizations are using dashboards, visualization and modeling to notify nontechnical people of events and enable them to understand their significance and take appropriate and immediate action.
As with any innovation, using OI for IoT may require substantial changes to organizations. These are among the challenges they face as they consider adopting this evolving operational intelligence:
They find it difficult to evaluate the business value of enabling real-time sensing of data and event streams using radio frequency identification (RFID) tags, agents and other systems embedded not only in physical locations like warehouses but also in business processes, networks, mobile devices, data appliances and other technologies.
They lack an IT architecture that can support and integrate these systems as the volume, variety and frequency of information increase. In addition, our previous operational intelligence research shows that these data sources are incomplete or inadequate in nearly two out of five organizations.
They are uncertain how to set reasonable business and IT expectations, priorities and implementation plans for important technologies that may conflict or overlap. These can include BI, event processing, business process management, rules management, network upgrades, and new or modified applications and databases.
They don’t understand how to create a personalized user experience that enables nontechnical employees in different roles to monitor data or event streams, identify significant changes, quickly understand the correlation between events and develop a context adequate to enable determining the right decisions or actions to take.
Today’s fast-paced, 24-by-7 world has forced organizations to reduce the latency between when transactions and other data are recorded and when applications and BI systems are made aware of them and thus can take action. Furthermore, the introduction of low-cost sensors and the instrumentation of devices ranging from appliances and airline engines to crop management and animal feeding systems creates opportunities that have never before existed. Technological developments such as smart utility meters, RFID and embedded computing devices for environmental monitoring, surveillance and other tasks also are creating demand for tools that can provide insights in real time from continuous streams of event data.
As organizations expand business intelligence to serve operational needs by deploying dashboards and other portals, they are recognizing the need to implement technology and develop practices that collect events, correlate them into meaningful patterns and use workflow, rules and analytics to guide how employees and automated processes should react. In financial services, online commerce and other industries, for example, some organizations have built proprietary systems or have gone offshore to employ large teams of technicians at outsourcing providers to monitor transactions and event streams for specific patterns and anomalies. To reduce the cost, complexity and imperfections in these procedures, organizations now are seeking technology that can standardize and automate event processing and notify appropriate personnel of significant events in real time.
Conventional database systems are geared to manage discrete sets of data for standard BI queries, but event streams from sources such as sensing devices typically are continuous, and their analysis requires tools designed to enable users to understand causality, patterns, time relationships and other factors. These requirements have led to innovation in event stream processing, event modeling, visualization and analytics. More recently the advent of open source and Hadoop-related big data technologies such as Flume, Kafka, Spark and Storm are enabling a new foundation for operational intelligence. Innovation in the past few years has occurred in both the open source community and proprietary implementations.
Many of the early adopters of operational intelligence technologies were in financial services and intelligence, online services and security. However, as organizations across a range of other industries seek new competitive advantages from information or require real-time insight for risk management and regulatory compliance, demand is increasing broadly for OI technologies. Organizations are considering how to incorporate event-driven architectures, monitor network activity for significant event patterns and bring event notification and insight to users through both existing and new dashboards and portals.
To help understand how organizations are tackling these changes Ventana Research is conducting benchmark research on The Internet of Things and Operational Intelligence. The research will explore how organizations are aligning themselves to take advantage of trends in operational intelligence and IoT. Such alignment involves not just information and technology, but people andprocesses as well. For instance, IoT can have a major impact on business processes, but only if organizations can realign IT systems to a discover-and-adapt rather than a model-and-apply paradigm. For instance, business processes are often outlined in PDF documents or through business process systems. However, these processes are often carried out in an uneven fashion different from the way the model was conceived. As more process flows are directly instrumented and some processes carried out by machines, the ability to model directly based on the discovery of those event flows and to adapt to them (either through human learning or machine learning) becomes key to successful organizational processes.
By determining how organizations are addressing the challenges of implementing these technologies and aligning them with business priorities, this research will explore a number of key issues, the following among them:
What is the nature of the evolving market opportunity? What industries and LOBs are most likely to adopt OI for IoT?
What is the current thinking of business and IT management about the potential of improving processes, practices and people resources through implementation of these technologies?
How far along are organizations in articulating operational intelligence and IoT objectives and implementing technologies, including event processing?
Compared to IT management, what influence do various business functions, including finance and operations management, have on the process of acquiring and deploying these event-centered technologies?
What suppliers are organizations evaluating to support operational intelligence and IoT, including for complex event processing, event modeling, visualization, activity monitoring, and workflow, process and rules management?
Who are the key decision-makers and influencers within organizations?
Please join us in this research. Fill out the surveyto share your organization’s existing and planned investments in the Internet of Things and operational intelligence. Watch this space for a report of the findings when the research is completed.
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.
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.
Top IoT programming languages: Java, C, JavaScript, Python. Not surprising to see these languages as being the most popular for developers. I do find some people question the use of Java in IoT. The Eclipse IoT community has a number of Java projects, so there is some bias in the results toward Java. However, even when removing the respondents from the Eclipse IoT community, the top 3 languages are C, Python and Java.
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.
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. It will play a big part in the IoT. From our friends at R2D3 is a very interesting visual introduction to machine learning. Check it out here.
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.
Some estimate that business IT spending on cloud-based, x-as-a-service activity will increase from about 15% today to 35% by 2021. Given that it is estimated that the global Big Data market will be worth $88 billion by that point, we can see that the forecast value of the BDaaS market could be $30 billion.
So, here I will attempt to give a brief(ish) overview of the concept, as well as examples of how it is being put into practice in real life businesses and organizations around the world.
What is BDaaS?
Big Data refers to the ever-growing amount of information we are creating and storing, and the analysis and use of this data. In a business sense, it particularly refers to applying insights gleaned from this analysis in order to drive business growth.
At the moment, BDaaS it is a somewhat nebulous term, which is often used to describe a wide variety of outsourcing of various Big Data functions to the cloud.
This can range from the supply of data, to the supply of analytical tools with which to interrogate the data (often through a web dashboard or control panel) to carrying out the actual analysis and providing reports. Some BDaaS providers also include consulting and advisory services within their BDaaS packages.
So, in many ways, BDaaS encompasses elements of what has become known as software as a service, platform as a service, data as a service, and so on – and applies them to solving Big Data problems.
Why is BDaaS useful?
There are several advantages to outsourcing or virtualizing your analytics activities involving large datasets.
The popularity of Hadoop has to some extent democratized Big Data – anyone can use cheap off-the-shelf hardware and open source software to analyze data, if they invest time learning how. But most commercial Big Data initiatives will still involve money being spent up front on components and infrastructure. When a large company launches a major initiative, this is likely to be substantial.
On top of upfront costs, storing and managing large quantities of information requires an ongoing investment of time and resources. When you use BDaaS, all of the techy “nuts and bolts” are, in theory, out of sight and out of mind, leaving you free to concentrate on business issues.
BDaaS providers generally take this on for the customer – they have everything set up and ready to go – and you simply rent the use of their cloud-based storage and analytics engines and pay either for the time you use them or the amount of data crunched.
Additionally BDaaS providers often take on the cost of compliance and data protection. When the data is stored on their servers, they are (generally) responsible for it.
Who provides and uses BDaaS?
A good example is IBM’s Analytics for Twitter service, which provides businesses with access to data and analytics on Twitter’s 500 million tweets per day and 280 million monthly active users.
As well as the “firehose” of tweets it provides analytics tools and applications for making sense of that messy, unstructured data and has trained 4,000 consultants to help businesses put plans into action to profit from them.
Another is agricultural manufacturers John Deere, which fits all of its tractors with sensors that stream data about the machinery as well as soil and crop conditions to the MyJohnDeere.com and Farmsight services. Farmers can subscribe to access analytical intelligence on everything from when to order spare parts to where to plant crops.
The arrival of Apple’s Watch – perhaps the device that will bring consumer wearables into the mainstream – will doubtlessly bring with it a tsunami of new BDaaS apps. They will soak up the data from the presumed millions of people who will soon be using it for everything from monitoring their heart rate to arranging their social calendar to remote controlling their home entertainment. Then they will find innovative ways to package it and sell it back to us. Apple and IBM have just announced their collaboration on a big data health platform.
In sales and marketing, BDaaS is increasingly playing its part, too. Many companies now offer customer profiling services, including Acxiom – the world’s biggest seller of direct marketing data. By applying analytics to the massive amount of personal data they collect, they can more effectively profile us as consumers and hand their own customers potential leads.
Amazon’s AWS as well as Google’s AdSense and AdWords are better known services that would also fall under the banner. They are all used by thousands of small to medium-sized businesses to host data infrastructure, and target their marketing at relevant niches where potential customers could be lurking.
The future of BDaaS?
The term may be rather unwieldy and inelegant (I’ve written before that I’m not even particularly a fan of the term Big Data, so BDaaS is a further step into the ridiculous) but the concept is rock solid.
As more and more companies realize the worth of implementing Big Data strategies, more services will emerge to support them. Data analysis can and generally does bring positive change to any organization that takes it seriously, and this includes smaller scale operations which won’t have the expertise (or budget to develop that expertise) to do it themselves.
With the growth in popularity of software as a service, we are increasingly used to working in a virtualized environment via a web interface, and integrating analytics into this process is a natural next step. We can already see that it is making Big Data projects viable for many businesses that previously would have considered them out of reach – and I think it is something we will see and hear a lot more about in the near future.
The ‘connected’ car, not to be confused with the self-driving, autonomous car, is defined as any vehicle equipped with Internet access that allows data to be sent to and from the vehicle.
Since the automobiles were invented, car makers have been trying to add features which may reduce driver error. Today’s car has the computing power of 20 personal computers, features about 100 million lines of programming code, and processes up to 25 gigabytes of data an hour.
Digital technology is also changing how we use and interact with our cars, and in more ways than you probably realize.
The market for smart vehicles is certainly set for takeoff and many analysts predict they could revolutionize the world of automobiles in much the same way smartphones have changed the face of telecommunications.
Is your car connected to the Internet? Millions of vehicles around the world had embedded Internet access, offering their drivers a multitude of smart options and benefits. These include better engine controls, automatic crash notifications and safety alerts, to name just a few. Owners can also interact with their connected vehicles through apps from any distance.
Vehicle-to-vehicle communications, for example, could help automobiles detect one another's presence and location to avoid accidents. That could be especially useful when it comes to driver-less cars - another advance already very much in development. Similar technology could help ensure that cars and their drivers slow down for school zones or stop at red lights.
Connected vehicle technologies provide the tools to make transformational improvements in safety, to significantly reduce the number of lives lost each year through connected vehicle crash prevention applications.
The Connected Car will be optimized to track and report its own diagnostics, which is part of its appeal for safety conscious drivers.
Connected cars give superior Infotainment services like navigation, traffic, weather, mobile apps, emails and also entertainment.
Auto insurers also have much to gain from the connected car revolution, as personalized, behavior based premiums are already becoming new industry standard.
OEMS and dealers must embrace the
Big Data revolution now, so they’re ready to harness the plethora of data that will become available as more and more connected cars hit the roads.
Cloud computing powers much of the audio streaming capabilities and dashboard app functions that are becoming more commonplace in autos.
In the next 5 years it seems that non-connected cars will become a thing of the past. Here are some good examples of connected cars:
Mercedes-Benz models introduced this year can link directly to Nest, the Internet of Things powered smart home system, to remotely activate a home’s temperature controls prior to arrival.
Audi has developed a 12.3 inch, 3d graphics fully digital dashboard in partnership with NVIDIA.
Telematics Company OnStar can shut down your stolen car remotely helping police solve the case.
ParkMe covers real time dynamic parking information and guide drivers to open parking lots and meters. It if further integrating with mobile payments.
The next wave is driver-less, fully equipped and connected car, where there will be no steering wheels, brakes, gas pedals and other major devices. You just have to sit back, relax and enjoy the ride!!
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 iswater 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
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 inLos AngelesandHollywood Hills.
Water Detection
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!
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.
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.
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.
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.
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.
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.
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.
Though Big Data and Internet of Things have been around for some time now, these notions are actually still emerging. And without a doubt we shall see great benefits from both of these in developing new products, especially apps.
Read more…
Posted by Asim Roy on April 12, 2016 at 19:48 in OSes
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.
Beginning of the era of personalization of machine learning
Imagine a complex plant or machinery being equipped with all kinds of sensors to monitor and control its performance and to predict potential points of failure. Such plants can range from an oil rig out in the ocean to an automated production line. Or such complex plants can be human beings, perhaps millions of them, who are being monitored with a variety of devices in a hospital or at home. Although we can use some standard models to monitor and compare performance of these physical systems, it would make more sense to either rebuild these models from scratch or adjust them to individual situations. This would be similar to what we do in economics. Although we might have some standard models to predict GDP and other economic variables, we would need to adjust each one of them to individual countries or regions to take into account their individual differences. The same principle of adjustment to individual situations would apply to physical systems that are sensor-based. And, similar to adjusting or rebuilding models of various economic phenomena, the millions of sensor-based models of our physical systems would have to be adjusted or rebuilt to account for differences in plant behavior. We are, therefore, entering an era of personalization of machine learning at a scale that we have never imagined before. The scenario is scary because we wouldn’t have the resources to pay attention to these millions of individual models. Cisco projects 50 billion devices to be connected by 2020 and the global IoT market size to be over $14 trillion by 2022 [1, 2].
The need for simplification and automation of machine learning technologies
If this scenario of widespread deployment of personalized machine learning is to play out, we absolutely need automation of machine learning to the extent that requires less expert assistance. Machine learning cannot continue to depend on high levels of professional expertise. It has to be simplified to be similar to automobiles and spreadsheets where some basic training at a high school can certify one to use these tools. Once we simplify the usage of machine learning tools, it would lead to widespread deployment and usage of sensor-based technologies that also use machine learning and would create plenty of new jobs worldwide. Thus, simplification and automation of machine learning technologies is critical to the economics of deployment and usage of sensor-based systems. It should also open the door to many new kinds of devices and technologies.
The need for hardware-based localized machine learning for "anytime, anywhere" deployment and usage
Although we talk about the Internet of Things, it would simply be too expensive to transmit all of the sensor-based data to a cloud-based platform for analysis and interpretation. It would make sense to process most of the data locally. Many experts predict that, in the future, about 60% of the data would be processed at the local level, in local networks - most of it may simply be discarded after processing and only some stored locally. There is a name for this kind of local processing – it’s called “edge computing” [3].
The main characteristics of data generated by these sensor-based systems are: high-velocity, high volume, high-dimensional and streaming. There are not many machine learning technologies that can learn in such an environment other than hardware-based neural network learning systems. The advantages of neural network systems are: (1) learning involves simple computations, (2) learning can take advantage of massively parallel brain-like computations, (3) they can learn from all of the data instead of samples of data, (4) scalability issues are non-existent, and (4) implementations on massively parallel hardware can provide real-time predictions in micro seconds. Thus, massively parallel neural network hardware can be particularly useful with high velocity streaming data in these sensor-based systems. Researchers at Arizona State University, in particular, are working on such a technology and it is available for licensing [4].
Conclusions
Hardware-based localized learning and monitoring will not only reduce the volume of Internet traffic and its cost, it will also reduce (or even eliminate) the dependence on a single control center, such as the cloud, for decision-making and control. Localized learning and monitoring will allow for distributed decision-making and control of machinery and equipment in IoT.
We are gradually moving to an era where machine learning can be deployed on an “anytime, anywhere” basis even when there is no access to a network and/or a cloud facility.
References
Gartner (2013). "Forecast: The Internet of Things, Worldwide, 2013."
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.
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.
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).
That framework took another step forward this month when the OTA released its Trust Framework of 30 recommendations for consumer-facing IoT companies seeking to build out this network of connected devices.
At first blush, the list of recommendations seems complete, but a longer look suggest is may be both too long and not long enough.
Too long because any list of 30 “must-haves” becomes more a barrier to entry than a glide path to market share. Too short because the biggest danger to consumer privacy, security and trust is a product no longer supported by a company that has moved on or shut down.
Too long? Rather than seek to create a granular set of prescriptive recommendations, it would be better to focus on a shorter and more effective set of requirements. I count five: encryption, authentication, fault tolerance, security and user control to review, change or delete. The ability to easily integrate and interoperate might be a sixth, but the market for consumer IoT is not so mature as to make that necessary – just yet.
Too short? The biggest dangers to consumers are IoT products no longer supported, either because it didn’t gain traction or the company has ceased to operate. It does not take long for a technology product to develop security holes if upgrades are not made. These holes are the source of the greatest vulnerability for the growth of the IoT market.
The OTA framework doesn’t answer all the questions raised by the expansion of the IoT, but it ought to be a real conversation starter – both for consumers and industry.
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 
