IoT Agenda

January 26, 2016  1:52 PM

Elluminance aims to solve Industrial IoT big data challenges

Sharon Shea Sharon Shea Profile: Sharon Shea
Internet of Things, iot

Big data for the Industrial Internet of Things is far different from big data for the Internet of Things, namely because what takes seconds — or more — must now take microseconds or less.

To overcome the time constraints associated with Industrial IoT and provide real-time monitoring, gathering and analyzing of IIoT data, elluminance Monday announced new product set that should help organizations capitalize on the insights derived from physical and real-world events, sensors and actuators, instrumentation, and software/IT infrastructure.

The Austin, Tex.-based company’s Real-time Data Platform and Time to Insight are deployed on National Instruments technology — which uses field programmable gate arrays (FPGAs) — and backend technology runs on Hewlett Packard Enterprise’s Moonshot development platform.

“The feedback data from sensors is under-utilized,” said Barry Hutt, elluminance CEO. The company’s diagnostic, predictive and prescriptive technology, he continued, are critical to harnessing the value of real-time industrial data to, for example, prevent failures in industrial engines or build a smart grid that can automatically detect and respond to issues (such as a crack in a utility pipe) or seamlessly put energy back onto the grid.

“I could just predict a behavior,” Hutt said, “But before I even know I have a problem, I’ve already fixed it by deriving from lots of different sources of data.”

Venture-backed elluminance, which was founded in October 2015, is able to do this as it is comprised of experts from various backgrounds — including sensors, instrumentation, IT and hardware — all places data is derived from.

This team of experts also knows that real-time computation and algorithms are two of the most costly barriers of IIoT analytics.

“Real-time doesn’t just mean fast,” said Darren Schmidt, chief technology officer of elluminance, “It means reliable and stable.”

Elluminance is prepared to help every step of the way — from sensor to backend. Its technologies connect data with the appropriate sense of real time — be it with FPGAs, CPUs or GPUs — as well as the proper algorithm which can pull value from operational technology. The company works with clients to map out the problem, response time (be it categorized “slow” at 10+ seconds or mission critical at 20 μs) and problem size, and then connect it with the proper algorithm, execution environment and data management solution.

“As the new networks link data from sensors to IT analytics systems, new and compelling insights and knowledge will be revealed, and those will boost operational efficiencies. The wisdom gained will enhance decision making and transform businesses,” said Hutt in a press release. “Our roots run deep in the technologies that are driving the growth of the Industrial IoT. Our customers reach new understandings of complex real world problems that can lead to ground-breaking solutions in months instead of years.”

January 21, 2016  9:32 AM

IoT enhances customer engagement for brands and marketers

Scott Amyx Scott Amyx Profile: Scott Amyx
Customer engagement, Internet of Things, iot

Consumer data is collected largely through tools like online metrics and surveys, but it is difficult to effectively gather information about customer engagement offline. Hard metrics on real emotional brand engagement have not been readily available for advertisers and marketers — until now. IoT devices provide enhanced capabilities to measure engagement, allowing businesses to develop richer customer profiles and create more effective marketing campaigns.

Engagement redux

The tech tools and techniques used to acquire data on the Internet rely on the participant’s engagement with metrics such as total interactions, interaction rate, clicks, likes, follows and shares. Offline data collection is largely limited to the survey, which does not always deliver accurate representations of real consumer feeling. This is not to say that the current metrics lack value — indeed, they provide a foundation for approaching brand engagement. However, they fail to provide a complete picture of the consumer.

The Interactive Advertising Bureau defines three major forms of ad engagement as cognitive (changes in a customer’s awareness, interest and intent), emotional/affective (feelings elicited by the ad or campaign) and physical/behavioral (engagement that requires user-initiated interaction). Cognitive and emotional metrics are generated mainly through surveys, while behavioral data are drawn from the Web and social analytics. Online and offline, surveys form one of the largest components of data collection, but they are not without problems. Research has shown that issues like non-responses, language and cultural misunderstandings, technology and response issues, and personality/individual interaction can all result in the aggregation of inaccurate data.

Don’t overdo it: Cognitive load

Cognitive engagement is vital to the success of any brand. Cognitive load theory drives many campaigns with the idea that effective advertising triggers the intrinsic and germane loads while avoiding the extraneous load. A successful campaign never forces consumers to spend inordinate amounts of time trying to understand your product. The problem is that it is not always clear how to avoid burdening the consumer with an extraneous load.

Technology is cracking the code on cognitive load. Always-on, wearable computing interfaces that understand the user’s current task type and load are positioned enhance data collection with reliable information. For example, the Wearable Computing Lab at the Swiss Federal Institute of Technology in Zurich has tapped electrodermal activity to elucidate the stress from the cognitive load through EDA measurement against six classifiers. Other researchers are exploiting computer vision cameras to quantify blink patterns to estimate cognitive and perceptual loads.

Getting emotional

Surveys are primarily used to measure emotional reactions (like brand perception, brand favorability and brand loyalty), yet they can overlook subtle cues that are vital to understanding authentic responses. Cues such as voice alterations, micro-expressions and other “non-verbal leakage” contain an enterprise’s treasure trove of insight. IoT devices can elucidate these types of cues to provide richer insights into actual human responses. For example, Affectiva’s software derives its emotion analytics from video facial recognition, which can analyze facial expressions instantaneously. Emotient (now owned by Apple) and Eyeris EmoVu are also using facial recognition and computer vision, and are able to examine a response right down to the micro-expression. Beyond Verbal uses voice analysis to decode emotions. Others, like Sentiance, are using wearables and smartphones to understand situational and contextual engagements to increase mobile conversion. Neuromarketing is experiencing a revolution: instead of simply using fMRIs to identify responses, biometrics, eye tracking, facial recognition and even EEG are being used to measure consumers’ emotional response to brand engagement. Innerscope Research (now part of Nielsen) and Ipsos are on the cutting edge of this trend.

IoT in action

Wearables are of particular importance in recording and analyzing behavioral metrics since many of the online metrics can be recreated in an offline context. For example, shopping in a retail store takes on a new dimension when seen through tracking devices. Evaluating what the consumer looks at, how long she spends examining an item or how she interacts with the store, representatives or products can be transformed into useful profile data. Combining in-store data with that derived from other sources can give further insight into consumer behavior. For example, IBM’s use of weather data elucidated the insights that consumers were more likely to avoid purchasing ice cream when it was above 77°F (it might melt) and were more open to advertising on beautiful sunny days.

Consumer-centered engagement

Brands and enterprises need to embrace new forms of data collection to enhance the consumer experience, increase brand engagement and drive growing sales. IoT devices bring new capabilities and opportunities to develop firm metrics. Understanding real emotional engagement with a brand via cognitive, emotional and behavioral metrics can only take on validity once we have a more complete picture of consumer behavior — and then use that data to develop a customer-centered approach.

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.

January 14, 2016  4:20 PM

Haute IoT: Smart garments and e-textiles

Scott Amyx Scott Amyx Profile: Scott Amyx
Internet of Things, iot, smart home

Smart garments and e-textiles (which meld traditional fabrics with cutting-edge technology) are altering the landscape of fashion, apparel, retail and furnishing sectors. While the methods for incorporating the technology vary (for example, placing sensors into a compression shirt or weaving special fibers into a dress), these fabrics not only allow an individual to enjoy cutting-edge style, but also harness the abilities of IoT. Current research that addresses issues in smart garments and e-textiles has uncovered a wide range of uses, from the utilitarian (measuring your heart rate) to the fantastic (light-up skirts). There are distinct advantages to bringing these technologies to your customers, but businesses must also support a strong commitment to consumer privacy in order to fully realize their benefits.

Global opportunity

Cisco indicated that IoT will create $14.4 trillion of value in the next decade, offering the opportunity to increase global corporate profits by 21%. Firms slow to adopt risk profit, market share and potential long-term viability. There is a tremendous amount of global potential, especially in countries with large capacity IoT opportunities such as China, the U.S., Germany, the U.K., Mexico and Australia.

Research from Gartner noted that smart garment sales were about 100,000 units in 2015, but current expectations for shipments are on track to hit 26 million units in 2016. During 2013, U.S. retail sales of clothing, shoes and accessories stores hit $244 billion. The global market for smart fabrics alone is forecasted to grow to around $2 billion dollars by 2018, a 64% increase over its current market value.

There is clearly strong potential for smart garment and e-textile growth — however, maximizing the opportunity involves understanding the best prospects and creating the right approach.

Optimizing life

Smart garments are more transformative than wrist wearables that provide step counts or heart rates. Industry- and government-supported research is making significant inroads to bringing real-life solutions to healthcare, athletics and fashion. These enhancements create value, boost health insights and reduce costs. For example, Eccrine Systems Inc. has created a patch that examines the chemical composition of sweat while researchers at Georgia Tech have developed haptic gloves that stimulate the hands of stroke victims to enhance their recovery times. The utilization of smart garments and e-textiles in athletics is projected to increase as player health concerns take center stage. Connected shirts, like Hexoskin, relay vitals to trainers while IoT helmets, like ShockBox, warn coaches about impacts. A common lament for online shoppers is that it is difficult to judge the correct fit of a garment, a problem solved by companies such as LikeAGlove, whose leggings take a wearer’s exact measurements and send them to an app to recommend pairs of pants that will best fit the individual’s body type.

Opportunities everywhere

While healthcare, athletics and fashion are beginning to enjoy a boost from e-textiles, every industry will be affected by these fabrics. For example, energy efficiency can be improved in homes that use technology like temperature-sensitive shades (FlipFlic and Control4 have solutions). Smart rugs can monitor the gait of the independent elderly to recognize potential balance problems or predict falls (University of Manchester). Employees in dangerous occupations benefit from real-time data while supervisors can pinpoint problems before they start (whole buildings can incorporate IoT, an idea being capitalized on by Siemens). Autos will benefit from smart fabrics in the seats, shades, flooring and interior lining.

Of course, smart cities are already in the works (AT&T), and e-textiles can contribute to safety on public transportation, sidewalks and parks. IoT-sensing capabilities currently found in smart garments and e-textiles can be complemented with visual and audio human-computer interfaces; the increasing amount of digital signage in public spaces is an area of untapped potential — every flat surface can be a point of interaction, such as the outside of buildings and hotels or the inside of retail stores and subways.

Privacy matters

The ubiquity of smart garments and e-textiles naturally highlights security and privacy concerns. The implementation of connected devices and fabrics requires a strong foundation of privacy — consumers must feel that their data is secure and that the company cares. Creating a company culture that respects customer privacy can be supported through the hiring of a chief privacy officer and by implementing industry best practices.

Smart materials have the potential to be infused into just about everything on or around us — our bodies, homes, cars, buildings and cities. Industries such as apparel and textile manufacturing traditionally have had very low profit margins. They now have the potential to increase these margins and drive top-line growth by incorporating smart materials into their manufacturing and consumer products. However, protecting consumers and respecting privacy are key issues for enterprises to consider as they move into this data-driven environment. How will major fashion, apparel, retail and furnishing brands strike a fine-balance?

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.

January 7, 2016  7:15 PM

Future behemoths of the IoT

Robert Richardson Robert Richardson Profile: Robert Richardson
Internet of Things, iot

My colleague Jon Brown, vice president of market intelligence here at TechTarget, posed an interesting question the other day. What was the billion-dollar breakthrough business enabled by the Internet of Things?

After all, he pointed out, other technology revolutions have produced enormous, dominant companies like GE and Ford. In the PC era, Microsoft and Apple. In the Internet era, Amazon and Google. If you look at a technology like genetics, it’s easy to see how a technology like CRISPR could result in billion-dollar companies.

But what about the Internet of Things? It’s easy to see significant incremental improvements such as lower costs for logistics or, as GE likes to talk about, 1% improvements. But dominant new businesses that couldn’t exist without the new development?rawr-dinosaur-800px

My answer is that at least one of the dominant companies is already here in the form of Apple. I think the smartphone (and specifically the iPhone) is the first glimpse most of us had of the Internet of Things. It’s mobile, it’s packed with sensors, it leverages a Web back end for key functionality. And it gets increasingly hard to imagine living without one.

The incremental cost factor

The mobile phone world also gives us a clue about future dominant businesses: they are driven by the way a new infrastructure makes the marginal cost of certain applications low enough that they are worth doing in a widespread way. Consider, for example, Twitter. Its genesis was the arrival of essentially free SMS text messaging. It would almost certainly not be worth building out mobile data networks or the Internet in order to broadcast 140-character updates on our latest meal to the world. But when it costs next to nothing, suddenly everyone wants to join the Twitterati.

Whether Twitter enhances humanity or is a lasting company, it did essentially create one-sided “following.” This is an enormously useful capability in all sorts of contexts.

Darned nearly every iPhone and Android app you can think of would not be worth creating smartphones and 4G LTE networks just to have it. But at least a few of those apps are enormously valuable once you’ve got the infrastructure already in place.

IoT has the makings of a different and vastly more pervasive information infrastructure. The importance of IoT’s presumably rapid build-out is not that there will be 20 or 40 or 117 billion “things” on the Internet by 2020, but that they will be building an infrastructure with entirely new trust relationship systems, with data aggregation capabilities that enable analytics on a scale we haven’t seen before, and that the administration (if it can be called that) of the infrastructure will have migrated to a place where the things (including IT network components) are considerably more self-organizing than they are at present.

The question then becomes: why is it suddenly so much cheaper to do that it’s worth doing on a global scale? Therein lie the dominant behemoths of the IoT era.

January 4, 2016  5:18 PM

But Bruce, Philips hews to open standard Hue

Robert Richardson Robert Richardson Profile: Robert Richardson
Internet of Things, iot, Philips

Noted cryptographer and security expert Bruce Schneier published an opinion piece in the Atlantic Monthly across the Christmas holiday, meaning it probably was largely overlooked. Which may be just as well, because he got it (uncharacteristically, to be fair) wrong.

Actually, his main point he got absolutely right: companies that clamp down control over their proprietary protocols stand to hurt the overall emergence of the Internet of Things. No argument there. When John Deere says farmers can’t fix their own tractors, it is attempting a power and money grab directly against its own core customers.

brain light bulb

Brainy lights, but will they be open minded?

But Schneier’s main example has to do with light bulbs. Speaking of the Philips Hue IoT light bulbs, he notes that “in mid-December, the company pushed out a software update that made the system incompatible with some other manufacturers’ light bulbs, including bulbs that had previously been supported.”

Which sound like poor sportsmanship on Philips’ part (and it was, and the company got sufficiently roughed up by popular outcry that it backed down). Philips customers complained that Hue products are supposed to be compliant with the Zigbee wireless mesh standard. The light bulbs from other manufacturers that the Hue hub no longer controlled were in fact Zigbee compliant.

It’s a good thing

What’s missing from Schneier’s analysis is mention of the possibility that this actually a case of an open standard working the way we hope it will. Zigbee, as far as I’m aware, isn’t a standard that prevents a controller from deciding which things it will communicate with. If Philips doesn’t want to talk to the other guy’s light bulbs, it’s hard to see how that’s actually something that “undercuts the purpose of having smart objects in the first place. We’ll want our light bulbs to communicate with a central controller, regardless of manufacturer.”

We do want that interoperability, to be sure. But just because Philips won’t make a fully interoperable hub doesn’t mean that competitors won’t. And it doesn’t mean that Philips customers won’t have a cow when Philips tries to take functionality out of products they’ve already paid for. They have the expectation of interoperability because Zigbee is open. With the case of HP printers that reject competitor ink cartridges, the public unfortunately didn’t have the expectation that HP printers would use an open standard cartridge, because there isn’t one.

Schneier gets sidetracked on the way in which the Digital Millennium Copyright Act can be used to prevent researchers from figuring out how the software on the Philips hub works. It certainly can be used that way, which is only one of a number of aspects of DMCA that make it breathtakingly bad legislation.

If Philips had the market dominance to just stick it to light bulb customers and force them to lump it, it’s true and regrettable that the DMCA could be used to punish anyone who figured out a workaround that enabled connection with those other bulbs. Be that as it may, the Hue product is part of a larger, open Zigbee ecosystem.

This is a case where open standards exerted pressure in just the sort of way we want them to. It’s also a good argument for the development for open source products that work within these standards. There’s an open-source Zigbee stack; there’s also open-source Zigbee hardware.

December 31, 2015  1:23 PM

IBM’s Watson IoT expansion: Nexus of the future

Scott Amyx Scott Amyx Profile: Scott Amyx
Analytics, IBM Watson, Internet of Things, iot

IBM’s launch of its new Watson IoT Center in Munich allows it to get a running start on the amalgamation of IoT and the rise of analytics. Management of big data sets is well beyond the abilities of individual — or even teams of — analysts, and the administration of information does not even touch on the facility to leverage this data to deliver benefits. Gartner sees over 6 billion connected devices by next year, so issues with data aggregation and use will grow as more objects come online. This is a problem that IBM is attempting to solve with its new approach using the cognitive abilities of its Watson computing platform.

“The Internet of Things will soon be the largest source of data on the planet,” noted Harriet Green, IBM’s newly-minted General Manager of Watson IoT and Education, “Yet 90% of that data is never acted upon.”

IBM’s pivot towards IoT allows it to assist companies and innovators incorporate sensor technology more efficiently through management and utilization of the data it offers.

Watson in Germany

The Munich Watson supercenter marks the beginning of a new approach to managing IoT and big data. It is the first time that IBM has operated an HQ outside of the U.S., signaling its commitment to the companies that currently form the backbone of one of Germany’s fastest-growing business hubs. The move to Munich locates IBM at the center of the developing world of the industrial IoT: Munich is a hive of business activity, home to appliance, electronics and auto manufacturers, healthcare enterprises and technology companies. This well-developed ecosystem boasts a number of veteran companies interested in tapping into IoT to streamline operations; it also provides a foundation for the fast expansion of IoT. IBM already has its finger on the pulse of manufacturers. For example, Siemens, which employs over 300,000 workers and touches areas as diverse as healthcare and energy, is betting on its partnership with IBM to develop smart buildings. Munich is also home to one of Germany’s “Big 3” automakers. BMW (which also owns Rolls-Royce) has been using IBM’s predictive analytics to enhance new model rollouts and streamline production, maintenance and repair processes.

Investment in IoT

IBM’s launch of its headquarters in Munich was preceded by its March commitment to invest $3 billion in its IoT unit. Pinning its hopes on the rapid rise of the evolving data-rich environment has moved IBM to unveil another eight Watson Client Experience Centers that span global tech hotspots like Beijing, Tokyo, Seoul, Sao Paolo and multiple sites in the U.S. The Munich campus itself will host 1,000 workers, including developers, researchers and support staff, a number that will be matched by its other teams across the globe. The recent disconnect between the American and European approaches to data privacy issues highlighted by the strike-down of the Safe Harbor pact has reinforced the importance of data management, so IBM’s biggest expansion in Germany in 20 years will be an interesting experiment in effectively managing big data under more limited parameters.

Relating man and machine

IBM’s approach to analytics focuses on not only aggregating the data from IoT, but on allowing for the comprehension and leveraging of the patterns that emerge from it through the incorporation of machine learning. The open, cloud-based Watson platform is designed to create a synergy between man and machine in order to enhance the complete range of human experience, from the industrial processes that deliver goods to the everyday flow of life.

IBM’s four “families” of APIs include Natural Language Processing (NLP), Machine Learning, Video and Image Analytics, and Text Analytics. Collectively, these APIs provide a foundation for speeding the development of data-enriched ideas, processes, goods and services. IBM’s partners have access to not only the APIs, but also benefit from the knowledge, tools and support services delivered through its IoT centers. The NLP is the API that most directly serves to ensure the rapid acceptance of analytics-based systems, since it will be the “face” — or perhaps, the voice — of the technology. NLP allows individuals to interact with computers by skipping the programming language. Users can instead simply ask questions about problems or have the system deliver understandable, useful data using regular speech. The Machine Learning API is the workhorse, constantly processing data and monitoring information to develop correlations between data sets. Not only does it keep tabs on incoming information, but the API also identifies patterns and trends. The Video and Image Analytics API harvests the data found in images, making it possible to identify locations based on photos or videos, as well as pinpoint patterns. The Text Analytics API mines the data that typically is forgotten — call center records, blogs, social media engagements, user comments, tweets and logs. It uncovers correlations between the conversations or notes and other data sets to highlight areas of concern or trends.

The advent of IBM’s new IoT centers is poised to drive innovation in IoT and analytics, providing a springboard to the spread of the technology. Smart buildings, cars, gadgets, appliances and medical devices are only the beginning. As more connected objects and services come online, IBM has positioned itself as the nexus of analytics understanding and development, and has sounded its call-to-arms: the time to implement IoT is now.

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.

December 30, 2015  5:55 PM

The thing about things is…

Sharon Shea Sharon Shea Profile: Sharon Shea
Internet of Things, iot

The exact number of “things” connecting to the Internet has been the subject of predictions for some time now. Research giant Gartner suggests 20.8 billion devices will connect by 2020 while Cisco and Frost & Sullivan agree that number is more like 50 billion.

The potential revenue stream of IoT is also subject to a lively debate. IDC predicts IoT spending will reach nearly $1.3 trillion in 2015 while Business Insider believes $6 trillion will be spent on IoT solutions in the next five years. In yet another generous guestimate, Cisco says the technologies and their associated services will create $14.4 trillion for companies by 2022. (Business Insider says $600 billion by 2019 while IDC believes revenue will exceed $7 trillion by 2020.) We think it’s like asking the value that the Internet brings to business worldwide: it’s something you could potentially estimate, but it’s also kind of missing the point.

The fact of the matter is that the Internet of Things is coming — and so is the buzz surrounding its potential. Sensors gonna sense. Sure, doing nothing is an option, but it will greatly hinder a company’s chances of gaining from the phenomena (to throw another stat in here, Verizon predicts organizations that use IoT technologies will become at least 10% more profitable by 2025.)

That brings us to what the Internet of Things is really about.

However cool and helpful the technologies, apps and gizmos may be, the Internet of Things at its core is not the cup that tells you how hydrated you are or the app that reminds you to take your daily medications.

The Internet of Things is about embracing technology to do things smarter, better and overall more efficiently. It’s about new and emerging technologies as well as innovative ways to use data collected by smart things. It’s about changing industries, companies and people’s lives for the better, improving user experience and learning in ways one never thought possible before. It’s about solving problems, saving money, changing the world.

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