The IoT Can Improve Safety and Profitability of Inherently Dangerous Job Sites

You may remember I wrote several months ago about a collaboration between SAP and SK Solutions in Dubai (interesting factoid: Dubai is home to almost 25% of the world’s cranes [assume most of the rest nest at Sand Hill, LOL], and they are increasingly huge, and that makes them difficult to choreograph.

I’m returning to the subject today, with a slightly broader emphasis on how the IoT might manage a range of dangerous job sites, such as mining and off-shore oil rigs, allowing us to do now that we couldn’t do before, one of my IoT Essential Truths.

I’m driven in part by home-town preoccupation with Boston’s bid for the 2024 Olympics, and the inevitable questions that raises on the part of those still smarting from our totally-botched handling of the last big construction project in these parts, the infamous “Big Dig” tunnel and highway project.

I’m one of those incurable optimists who think that part of ensuring that the Olympics would have a positive “legacy” (another big pre-occupation in these parts) would be to transform the city and state into the leading example of large-scale Internet of Things implementation.

There are a couple of lessons from SAP and SK Solutions’ collaboration in Dubai that would be relevant here:

    • The system is real-time: the only way the Boston Olympic sites could be finished in time would be through maximizing efficiency every day. Think how hard that is with a major construction project: as with “for want of a nail the kingdom was lost,” the sensitive interdependence between every truck and subcontractor on the site — many of which might be too small to invest in automation themselves — is critical. If information about one sub being late isn’t shared, in real-time, with all the other players, the delays — and potential collisions — will only pile up. The system includes an auto-pilot that makes immediate adjustments to eliminate operator errors. By contrast, historical data that’s only analyzed after the fact won’t be helpful, because there’s no do-overs, no 2025 Olympics!
    • The data is shared: that’s another key IoT Essential Truth.  “Decision-makers using SK Solutions on a daily basis span the entire organization. Besides health and safety officers, people responsible for logistics, human resources, operations and maintenance are among the typical users.”  The more former information silos share the data, the more likely they are to find synergistic solutions.
    • The system is inclusive, both in terms of data collection and benefits: SK Solutions’ Founder and Inventor Séverin Kezeu, came up with his collision-avoidance software pre-IoT, but when the IoT became practical he partnered with SAP, Cisco, and Honeywell to integrate and slice and dice the data yielded by the sensors they installed on cranes and vehicles and other sources.  For example, the height of these cranes makes them vulnerable to sudden weather changes, so weather data such as wind speed and direction must be factored in, as well as the “machinery’s position, movement, weight, and inertia…. The information is delivered on dashboards and mobile devices, visualized with live 3-D images with customizable views. It’s also incredibly precise.”As a result, by using SAP’s HANA platform, a system developed to reduce construction accidents also makes predictive maintenance of the cranes and other equipment, and lets the construction companies monitor Key Performance Indicators (KPIs) such as asset saturation, usage rates, and collisions avoided.  McKinsey reports that construction site efficiency could improve dramatically due to better coordination: “One study found that buffers built into construction project schedules allowed for unexpected delays resulting in 70 to 80 percent idle time at the worksite.Visibility alone can allow for shorter buffers to be built into the construction process.”

Several other great IoT solutions come to mind at the same time, both relating to dangerous industries. Off-shore oil rigs and mining were treated at length in the recent McKinsey omnibus IoT forecast, “The Internet of Things: Mapping the Value Beyond the Hype:”

  • off-shore rigs: “Much of the data collected by these sensors [30,000 on some rigs] today is used to monitor discrete machines or systems. Individual equipment manufacturers collect performance data from their own machines and the data can be used to schedule maintenance. Interoperability would significantly improve performance by combining sensor data from different machines and systems to provide decision makers with an integrated view of performance across an entire factory or oil rig. Our research shows that more than half of the potential issues that can be identified by predictive analysis in such environments require data from multiple IoT systems. Oil and gas experts interviewed for this research estimate that interoperability could improve the effectiveness of equipment maintenance in their industry by 100 to 200 percent.” (my emphasis). 
  • mining: “In one mining case study, using automated equipment in an underground mine increased productivity by 25 percent. A breakdown of underground mining activity indicates that teleremote hauling can increase active production time in mines by as much as nine hours every day by eliminating the need for shift changes of car operators and reducing the downtime for the blasting process. Another source of operating efficiency is the use of real-time data to manage IoT systems across different worksites, an example of the need for interoperability. In the most advanced implementations, dashboards optimized for smartphones are used to present output from sophisticated algorithms that perform complex, real-time optimizations. In one case study from the Canadian tar sands, advanced analytics raised daily production by 5 to 8 percent, by allowing managers to schedule and allocate staff and equipment more effectively. In another example, when Rio Tinto’s (one mine) crews are preparing a new site for blasting, they are collecting information on the geological formation where they are working. Operations managers can provide blasting crews with detailed information to calibrate their use of explosives better, allowing them to adjust for the characteristics of the ore in different parts of the pit.”
 In all of these cases, the safety and productivity problems — and solutions are intertwined.  As McKinsey puts it:
“Downtime, whether from repairs, breakdowns, or maintenance, can keep machinery out of use 40 percent of the time or more. The unique requirements of each job make it difficult to streamline work with simple, repeatable steps, which is how processes are optimized in other industries. Finally, worksite operations involve complex supply chains, which in mining and oil and gas often extend to remote and harsh locations.”
Could it be that the IoT will finally tame these most extreme work situations, and bring order, safety, and increased profitability?  I’m betting on it.

McKinsey IoT Report Nails It: Interoperability is Key!

I’ll be posting on various aspects of McKinsey’s new “The Internet of Things: Mapping the Value Beyond the Hype” report for quite some time.

First of all, it’s big: 148 pages in the online edition, making it the longest IoT analysis I’ve seen! Second, it’s exhaustive and insightful. Third, as with several other IoT landmarks, such as Google’s purchase of Nest and GE’s divestiture of its non-industrial internet division, the fact that a leading consulting firm would put such an emphasis on the IoT has tremendous symbolic importance.

McKinsey report — The IoT: Mapping the Value Beyond the Hype

My favorite finding:

“Interoperability is critical to maximizing the value of the Internet of Things. On average, 40 percent of the total value that can be unlocked requires different IoT systems to work together. Without these benefits, the maximum value of the applications we size would be only about $7 trillion per year in 2025, rather than $11.1 trillion.” (my emphasis)

This goes along with my most basic IoT Essential Truth, “share data.”  I’ve been preaching this mantra since my 2011 book, Data Dynamite (which, if I may toot my own horn, I believe remains the only book to focus on the sweeping benefits of a paradigm shift from hoarding data to sharing it).

I was excited to see that the specific example they zeroed in on was offshore oil rigs, which I focused on in my op-ed on “real-time regulations,” because sharing the data from the rig’s sensors could both boost operating efficiency and reduce the chance of catastrophic failure. The paper points out that there can be 30,000 sensors on an rig, but most of them function in isolation, to monitor a single machine or system:

“Interoperability would significantly improve performance by combining sensor data from different machines and systems to provide decision makers with an integrated view of performance across an entire factory or oil rig. Our research shows that more than half of the potential issues that can be identified by predictive analysis in such environments require data from multiple IoT systems. Oil and gas experts interviewed for this research estimate that interoperability could improve the effectiveness of equipment maintenance in their industry by 100 to 200 percent.”

Yet, the researchers found that only about 1% of the rig data was being used, because it rarely was shared off the rig with other in the company and its ecosystem!

The section on interoperability goes on to talk about the benefits — and challenges — of linking sensor systems in examples such as urban traffic regulation, that could link not only data from stationary sensors and cameras, but also thousands of real-time feeds from individual cars and trucks, parking meters — and even non-traffic data that could have a huge impact on performance, such as weather forecasts.  

While more work needs to be done on the technical side to increase the ease of interoperability, either through the growing number of interface standards or middleware, it seems to me that a shift in management mindset is as critical as sensor and analysis technology to take advantage of this huge increase in data:

“A critical challenge is to use the flood of big data generated by IoT devices for prediction and optimization. Where IoT data are being used, they are often used only for anomaly detection or real-time control, rather than for optimization or prediction, which we know from our study of big data is where much additional value can be derived. For example, in manufacturing, an increasing number of machines are ‘wired,’ but this instrumentation is used primarily to control the tools or to send alarms when it detects something out of tolerance. The data from these tools are often not analyzed (or even collected in a place where they could be analyzed), even though the data could be used to optimize processes and head off disruptions.”

I urge you to download the whole report. I’ll blog more about it in coming weeks.

Every IoT office needs this graphic on privacy and security

Long-time readers know that I frequently rant that privacy and security are Job 1 when it comes to the IoT.  

No apologies: it’s because I spent many years in corporate crisis management, and I learned the hard way that public trust is hard to earn, easy to lose, and, once lost, difficult or impossible to regain.

That’s why I was so glad to see this really informative, attractive, and scary infographic from Zora Lopez at Computer Science Zone, because it lays everything out so vividly.  Among the key points:

  1. (seen this before, but it still astounds me) In 2011, 20 typical households generated as much data as the entire Internet did as recently as 2008.
  2. the number of really-large (on scale of e-Bay, Target, etc.) data thefts grow annually.
  3. the bad guys particularly go after extremely sensitive data such as health, identity and financial.

It concludes with a particularly sobering reminder (you may remember my comment on the enthusiastic guys who presented at Wearables + Things and cheerfully commented that they would eventually get around to privacy and security — NOT!):

The barrier to entry in tech has never been lower, leaving many new organizations to later grapple with unsatisfactory security.” (my emphasis)

So: print a copy of the following for every employee and new hire, and put it on the cube’s wall immediately (here’s the original URL: http://www.computersciencezone.org/wp-content/uploads/2015/04/Security-and-the-Internet-of-Things.jpg#sthash.c6u2POMr.dpuf)

IoT Privacy and Security, from Computer Science Zone

Intel’s IoT tech improves its own manufacturing efficiency

This demonstration IoT manufacturing project hits my buttons!

I love IoT-enabled manufacturing (what I call “precision manufacturing“) and I REALLY love companies (such as GE, at its Durathon battery plant) that eat their own dogfood by applying their IoT technology internally.  Gotta walk the talk!

 

That’s why I was happy to learn how Intel is  applied its own IoT technology to its own factories. In the accompanying video, Intel VP for IoT operations and group marketing Frank James says:

“The real opportunity is how to combine … data differently, which will ultimately give you insights not only into how your factory is running but, what’s more important, will let you predict how your factory will run the next minute, the next hour, the next shift, the next day.”

The pilot factory automation project is a collaboration with Mitsubishi Electric (more points for a key IoT “Essential Truth” — collaboration!).  The project, at Intel’s Malaysia manufacturing facility, combines two critical components, end-to-end IoT connectivity and big data analytics. The benefits were impressive: $9 million in cost avoidance and improved decision making, plus:

  • improved equipment uptime
  • increased yield and productivity
  • predictive maintenance
  • reduced component failures.

That hard-to-quantify improved decision making, BTW, is one of the things that doesn’t get enough discussion when we talk about IoT benefits: decision-making improves when there is more data to consider, more people to analyze and discuss it simultaneously (not sequentially, as in the past), and when you’ve got tools such as data dashboards to allow visualizing the data and its patterns.

The companies plan to roll out the services commercially this year.

Here are the specs:

“Using an Intel® Atom™ processor-based IoT gateway called the C Controller from Mitsubishi Electric’s iQ-Platform, Intel was able to securely gather and aggregate data for the analytics server. Data was then processed using Revolution R Enterprise* software from Revolution Analytics*, an analytics software solution that uses the open source R statistics language, which was hosted on Cloudera Enterprise*, the foundation of an enterprise data hub.”

 

Virtual Sensor Networks: a key #IoT tool?

I was once again honored to be a guest on Coffee Break With Game Changers Radio today with David Jonker and Ira Berk of SAP — it’s always a delight to have a dialogue on the Internet of Things with these two brainy guys (and hats off as well to moderator/host Bonnie Graham!).

Toward the end of the show, Ira brought up a concept that was new to me: virtual sensor networks.

I’ve got sensors on the brain right now, because I’m frankly worried that sensors that don’t have adequate baked-in security and privacy protections and which can’t be ungraded as new opportunities and threats present themselves may be a threat to the IoT because they typically remain in use for so many years. Ah, but that’s a topic for another post.

According to Wikipedia, Virtual sensor networks are an:

“… emerging form of collaborative wireless sensor networks. In contrast to early wireless sensor networks that were dedicated to a specific application (e.g., target tracking), VSNs enable multi-purpose, collaborative, and resource efficient WSNs. The key idea difference of VSNs is the collaboration and resource sharing….
“… A VSN can be formed by providing logical connectivity among collaborative sensors. Nodes can be grouped into different VSNs based on the phenomenon they track (e.g., rock slides vs. animal crossing) or the task they perform. VSNs are expected to provide the protocol support for formation, usage, adaptation, and maintenance of subset of sensors collaborating on a specific task(s). Even the nodes that do not sense the particular event/phenomenon could be part of a VSN as far as they are willing to allow sensing nodes to communicate through them. Thus, VSNs make use of intermediate nodes, networks, or other VSNs to efficiently deliver messages across members of a VSN.”

Makes sense to me: collaboration is a critical basic component of the human aspect of the IoT (one of my IoT “Essential Truths), so why shouldn’t that extend to the mechanics as well?). If you have a variety of sensors already deployed in a given area, why should you have to deploy a whole new set of single-purpose ones to monitor a different condition if data could be synthesized from the existing sensors to effectively yield the same needed information?

2008 article on the concept said the virtual sensor networks are particularly relevant to three categories where data is* needed:

“Firstly, VSNs are useful in geographically overlapped applications, e.g., monitoring rockslides and animal crossing within a mountainous terrain. Different types of devices that detect these phenomena can relay each other for data transfer without having to deploy separate networks (Fig. 1). Secondly, VSNs are useful in logically separating multipurpose sensor networks, e.g., smart neighborhood systems with multifunctional sensor nodes. Thirdly, VSNs can be used to enhance efficiency of systems that track dynamic phenomena such as subsurface chemical plumes that migrate, split, or merge. Such networks may involve dynamically varying subsets of sensors.”

That article went on to propose a flexible, self-organizing “cluster-tree” approach to create the VSN, using tracking of a pollution plume as an example:

“…  a subset of nodes organizes themselves to form a VSN to track a specific plume. Whenever a node detects a relevant event for the first time it sends a message towards the root of the cluster tree indicating that it is aware of the phenomenon and wants to collaborate with similar nodes. The node may join an existing VSN or makes it possible for other nodes that wish to form a VSN, to find it. Use of a cluster tree or a similar structure guarantees that two or more nodes observing the same phenomenon will discover each other. Simulation based results show that our approach is more efficient and reliable than Rumor Routing and is able to combine all the nodes that collaborate on a specific task into a VSN.”

I suspect the virtual sensor network concept will become particularly widespread as part of “smart city” deployments: cash-strapped municipalities will want to get as much bang for the buck possible from already-deployed sensors, without having to install new ones. Bet my friends in Spain at Libellium will be in the forefront of this movement!

Thanks, Ira!


*BTW: if any members of the Grammar Police are lurking out there (I’m a retired lt. colonel of the Mass. State Grammar Police myself), you may take umbrage at “data is.”  Strictly speaking, the proper usage in the past has been “data are,” but the alternative is becoming so widespread that it’s becoming acceptable usage. So sue me…

 

Deloitte’s IoT “Information Value Loop”: critical attitudinal shift

Ever so often it’s good to step back from the day-to-day minutia of current Internet of Things projects, and get some perspective on the long-term prospects and challenges.

That’s what Deloitte did last December, when it held an “Internet of Things Grand Challenge Workshop,” with a focus on the all-important “forging the path to revenue generation.”

The attendees included two of my idols: John Seely Brown and John Hagel, of Deloitte’s “Center for the Edge” (love the pun in that title!).

The results were recently released, and bear close examination, especially the concept of how to foster what they call the “Information Value Loop”:

Deloitte IoT Information Value Loop

Deloitte IoT Information Value Loop

“The underlying asset that the IoT creates and exploits is information, yet we lack a well- developed, practical guide to understand how information creates value and how companies can effectively capture value. The ‘Information Value Loop’ describes how information creates value, how to increase that value, and how understanding the relevant technology is central to positioning an organization to capture value. The Information Value Loop is one way to begin making sense of the changes we face. The Loop consists of three interconnected elements: stages, value drivers, and technologies. Where the stages and value drivers are general principles defining if and how information creates value under any circumstances, it is the specifics of today’s technology that connect the Loop to the challenges and opportunities created by the IoT.”

This fits nicely with one of my IoT Esssential Truths,” that we need to turn linear information flows into cyclical ones to fully capitalize on the IoT.  No pussy-footin’ about this for these guys: “For information to create any value at all, it must pass through all the stages of the Loop. This is a binary outcome: should the flow of information be blocked completely at any stage, no value is created by that information.”

IMHO, this is also going to be one of the biggest challenges of the IoT for management: in the days when it was sooo difficult to gather and disseminate information, it made sense for those in the C-suite to control it, and parcel out what they felt was relevant, to whom and when they felt it was relevant. More often than not, the flow was linear and hierarchical, with one information silo in the company handing on the results to the next after they’d processed it. That didn’t allow any of the critical advantages the IoT brings, of allowing everyone who needs it to share real-time data instantly.  But saying we need to change those information management practices is one thing: actually having senior management give up their gatekeeper functions is another, and shouldn’t be understated as a challenge.

So here are some of the other key points in the conference proceedings:

  • In line with the multi-step strategy I outlined in Managing the Internet of Things Revolution, they concluded that incremental improvements to existing processes and products are important, but will only take you so far, at which point radical innovation will be crucial: “At first blush, the early IoT emphasis on sustaining innovation seems reasonable. Performance and cost improvement are seldom absent from the priorities of stakeholders; they are relatively easy to measure and their impact is likely more immediate than any investment that is truly disruptive. Put simply, the business case for an IoT application that focuses on operational efficiencies is relatively easy to make. Many decision makers are hard-wired to prefer the path of less resistance and, for many, truly innovative IoT applications seem too far-flung and abstract to risk pursuing. Still, organizations cannot innovate from the cost side forever.”
  • Melding the public and private, “Cities have inherent societal challenges in place to serve as natural incubators of IoT solutions.” Yeah!
  • As in everything else, those contrarian Millennials (who aren’t so hung up on buying stuff and often prefer to just use it)  are likely to save us when it comes to the IoT:  “From an innovation perspective … some of the new technologies are first marketed at the consumers. Thus, many believe that near-term innovation in IoT applications will come out of the consumer sector – spurred by the emergence of the tech-savvy Millennial consumers as a driving economic force.”
  • As I’ve written before, while some customers will still prefer to buy products outright, the IoT will probably bring a shift from selling products to marketing services based on those products, creating new revenue streams and long-term relationships with customers: “As IoT makes successful forays into the world of consumer and industrial products, it may radically change the producer—buyer transactional model from one based on capital expenditure to one based on operating expenditure. Specifically, in a widely adopted IoT world, buyers may be more apt to purchase product service outcomes on some kind of “per unit” basis, rather than the product itself and in so doing, render the physical product as something more of an afterthought. The manufacturer would then gradually transform into a service provider, operating on a complete awareness of each product’s need for replenishment, repair, replacement, etc.”

    Or, a hybrid model may emerge: “What may ultimately happen in a relatively connected product world is that many may accept the notion of the smartly connected product, but in a limited way. Such people will want to own the smartly connected product outright, but will also accept the idea of sharing the usage data to the limited extent that the sellers use such data in relatively benign ways, such as providing advice on more efficient usage, etc. The outcome here will also rely upon a long term total cost of ownership (TCO) perspective. With any fundamental purchasing model changes (as is taking place in owned vs. cloud resources in the network / IT world), not all suppliers will be able to reap additional economic benefit under the service model. Buyers will eventually recognize the increase in TCO and revert back to the more economical business model if the economic rents are too high.”

  • It’s likely that those players in the IoT ecosystem who create value-added data interpretation will be the most valuable and profitable: “…are certain building blocks of the IoT network “more equal” than others?

    “Some have argued that the holy grail of the IoT value loop resides in the data and that those in the IoT ecosystem who aggregate and transform massive amounts of raw data into commercially useful intelligence capture the real value in the IoT environment. This notion holds that commercially useful data provide insights that drive action and ultimately represent the reason that the end user pursues a smart solution in the first place. Put another way, the end customer is more apt to pay for a more comprehensive treatment of raw data than for a better sensor. Indeed, some even believe that as time passes, the gap in relative value captured by those who curate and analyze the data and the rest of the IoT ecosystem will only widen and that, on a long-term basis, players within the “non-data” part of the IoT ecosystem will need to develop some data analytics capabilities simply to differentiate themselves as something more than commodity providers. Of course, some think that the emphasis on data is overblown and argue that where the real value in the IoT ecosystem is captured depends on application. Time will tell of course. But there can be little doubt that the collection and enhancement of data is highly coveted, and analytics and the ability to make use of the vast quantities of information that is captured will serve as critical elements to virtually any IoT solution.”

I urge you to download and closely analyze the entire report. It’s one of the most thoughtful and visionary pieces of IoT theory I’ve seen (no doubt because of its roundtable origins: in keeping with the above-mentioned need for cyclical information flow for the IoT [and, IMHO, creativity in general], the more insights you can bring together on a real-time basis, the richer the outcome. Bravo!

 

The Internet of Things’ Essential Truths

I’ve been writing about what I call the Internet of Things’ “Essential Truths” for three years now, and decided the time was long overview to codify them and present them in a single post to make them easy to refer to.

As I’ve said, the IoT really will bring about a total paradigm shift, because, for the the first time, it will be possible for everyone who needs it to share real-time information instantly. That really does change everything, obliterating the “Collective Blindness” that has hampered both daily operations and long-term strategy in the past. As a result, we must rethink a wide range of management shibboleths (OK, OK, that was gratuitous, but I’ve always wanted to use the word, and it seemed relevant here, LOL):

  1. First, we must share data. Tesla leads the way with its patent sharing. In the past, proprietary knowledge led to wealth: your win was my loss. Now, we must automatically ask “who else can use this information?” and, even in the case of competitors, “can we mutually profit from sharing this information?” Closed systems and proprietary standards are the biggest obstacle to the IoT.
  2. Second, we must use the Internet of Things to empower workers. With the IoT, it is technically possible for everyone who could do their job better because of access to real-time information to share it instantly, so management must begin with a new premise: information should be shared with the entire workforce. Limiting access must be justified.
  3. Third, we must close the loop. We must redesign our data management processes to capitalize on new information, creating continuous feedback loops.
  4. Fourth, we must rethink products’ roles. Rolls-Royce jet engines feed back a constant stream of real-time data on their operations. Real-time field data lets companies have a sustained dialogue with products and their customers, increasingly allowing them to market products as services, with benefits including new revenue streams.
  5. Fifth, we must develop new skills to listen to products and understand their signals. IBM scientists and medical experts jointly analyzed data from sick preemies’ bassinettes & realized they could diagnose infections a day before there was any visible sign. It’s not enough to have vast data streams: we need to understand them.
  6. Sixth, we must democratize innovation. The wildly-popular IFTTT web site allows anyone to create new “recipes” to exploit unforeseen aspects of IoT products – and doesn’t require any tech skills to use. By sharing IoT data, we empower everyone who has access to develop new ways to capitalize on that data, speading the IoT’s development.
  7. Seventh, and perhaps most important, we must take privacy and security seriously. What responsible parent would put an IoT baby monitor in their baby’s room after the highly-publicized incident when a hacker exploited the manufacturer’s disregard for privacy and spewed a string of obscenities at the baby? Unless everyone in the field takes privacy and security seriously, the public may lose faith in the IoT.

There you have ’em: my best analysis of how the Internet of Things will require a revolution not just in technology, but also management strategy and practices. What do you think?

Apple ResearchKit will launch medical research paradigm shift to crowd-sourcing

Amidst the hoopla about the new MacBook and much-anticipated Apple Watch, Apple snuck something into Monday’s event that blew me away (obligatory disclaimer: I work part-time at The Apple Store, but the opinions expressed here are mine).

My Heart Counts app

Four years after I proselytized about the virtues of democratizing data in my Data Dynamite: how liberating data will transform our world book (BTW: pardon the hubris, but I still think it’s the best thing out there about the attitudinal shift needed to capitalize on sharing data), I was so excited to learn about the new ResearchKit.

Tag line? “Now everybody can do their part to advance medical research.”

The other new announcements might improve your quality of life. This one might save it!

As Senior VP of Operations Jeff Williams said in announcing the kit,  the process of medical research ” ..hasn’t changed in decades.” That’s not really true: as I wrote in my book, the Quantified Self movement has been sharing data for several years, as well as groups such as CureTogether and PatientsLikeMe. However, what is definitely true is that no one has harnessed the incredible power of the smartphone for this common goal until now, and that’s really incredible. It’s a great example of my IoT Essential Truth of asking “who else could use this data?

A range of factors cast a pall over traditional medical research.

Researchers have had to cast a broad net even to get 50-100 volunteers for a clinical trial (and may have to pay them, to boot, placing the results validity when applied to the general population in doubt).  The data has often been subjective (in the example Williams mentioned, Parkinson’s patients are classified by a doctor simply on the basis of walking a few feet). Also, communication about the project has been almost exclusively one way, from the researcher to the patient, and limited, at best.

What if, instead, you just had to turn on your phone and open a simple app to participate? As the website says, “Each one [smartphone] is equipped with powerful processors and advanced sensors that can track movement, take measurements, and record information — functions that are perfect for medical studies.” Suddenly research can be worldwide, and involve millions of diverse participants, increasing the data’s amount and validity (There’s a crowdsourcing research precedent: lot of us have been participating in scientific crowdsourcing for almost 20 years, by installing the SETI@Home software that runs in the background on our computers, analyzing data from deep space to see if ET is trying to check in)!

Polymath/medical data guru John Halamka, MD wrote me that:

“Enabling patients to donate data for clinical research will accelerate the ‘learning healthcare system’ envisioned by the Institute of Medicine.   I look forward to testing out Research Kit myself!”

The new apps developed using ResearchKit harvest information from the Health app that Apple introduced as part of iOS8. According to Apple:

“When granted permission by the user, apps can access data from the Health app such as weight, blood pressure, glucose levels and asthma inhaler use, which are measured by third-party devices and apps…. ResearchKit can also request from a user, access to the accelerometer, microphone, gyroscope and GPS sensors in iPhone to gain insight into a patient’s gait, motor impairment, fitness, speech and memory.

Apple announced that it has already collaborated with some of the world’s most prestigious medical institutions, including Mass General, Dana-Farber, Stanford Medical, Cornell and many others, to develop apps using ResearchKit. The first five apps target asthma, breast cancer, cardiovascular disease, diabetes and Parkinson’s disease.  My favorite, because it affects the largest number of people, is the My Heart Counts one. It uses the iPhone’s built-in motion sensors to track participants’ activity, collecting data during a 6-minute walk test from those who are able to walk that long. If participants also have a wearable activity device connecting with the Health app (aside: still don’t know why my Jawbone UP data doesn’t flow to the Health app, even though I made the link) , they are encouraged to use that as well. Participants will also enter data about their heart disease risk factors and their lab tests readings to get feedback on their chances of developing heart disease and their “heart age.” Imagine the treasure trove of cardiac data it will yield!

 A critical aspect of why I think ResearchKit will be have a significant impact is that Apple decided t0 make it open source, so that anyone can tinker with the code and improve it (aside: has Apple EVER made ANYTHING open source? Doubt it! That alone is noteworthy).  Also, it’s important to note, in light of the extreme sensitivity of any personal health data, that Apple guarantees that it will not have access to any of the personal data.

Because of my preoccupation with “Smart Aging,” I’m really interested in whether any researchers will specifically target seniors with ResearchKit apps. I’ll be watching carefully when the Apple Watch comes out April 24th to see if seniors buy them (not terribly optimistic, I must admit, because of both the cost and the large number of seniors I help at The Apple Store who are befuddled by even Apple’s user-friendly technology) because the watch is a familiar form factor for them (I haven’t worn a watch since I got my first cell phone, and most young people I know have never had one) and might be willing to use them to participate in these projects.

N0w, if you’ll excuse me, I just downloaded the My Heart Counts app, and must find out my “heart age!”


 

Doh!  Just after I posted this, I saw a really important post on Ars Technica pointing out that this brave new world of medical research won’t go anywhere unless the FDA approves:

“As much as Silicon Valley likes to think of itself as a force for good, disrupting this and pivoting that, it sometimes forgets that there’s a wider world out there. And when it comes to using devices in the practice of medicine, that world contains three very important letters: FDA. That’s right, the US Food and Drug Administration, which Congress has empowered to regulate the marketing and research uses of medical devices.

“Oddly, not once in any of the announcement of ResearchKit did we see mention of premarket approval, 510k submission, or even investigational device exemptions. Which is odd, because several of the uses touted in the announcement aren’t going to be possible without getting the FDA to say yes.”

I remember reading that Apple had reached out to the FDA during development of the Apple Watch, so I’m sure none of this comes as a surprise to them, and any medical researcher worth his or her salt is also aware of that factor. However, the FDA is definitely going to have a role in this issue going forward, and that’s as it should be — as I’ve said before, with any aspect of the IoT, privacy and security is Job One.

 

 

IFTTT DO apps: neat extension of my fav #IoT crowdsourcing tool!

Have I told you lately how much I love IFTTT? Of course!  As I’ve said, I think they are a phenomenal example of my IoT “Essential Truth” question: who else can use this data?

IFTTT_DO_buttonNow, they’ve come up with 3 new apps, the “DO button,” “DO camera,” and “DO Note,” that make this great tool even more versatile!

With a DO “recipe,” you simply tap on the appropriate app, and the “recipe” runs. Presto! Change-o!

As a consultant who must bill for his time, I particularly like the one that lets you “Track Your Work hours” on Google Drive, but you’re sure to find your own favorites in categories such as play, work, home, families, and essentials. Some are just fun, and some will increase your productivity or help manage your household more easily (hmm: not sure where “post a note to your dog’s timeline” fits in (aside to my sons: feel free to “send notes to your data via email”.  If past experience is any indication, there should be many, many more helpful “Do” recipes as soon as users are familiar with how to create them.

As I’ve said before, it’s no reflection on the talented engineers at HUE, NEST, et. al., but there’s simply no way they could possibly visualize all the ways that their devices could be used and/or combined with others, and that’s why IFTTT, by adding the crowdsourcing component and democratizing data, is so important to speeding the IoT’s deployment.

“Enchanted Objects” — adding delight to the IoT formula

Posted on 21st January 2015 in design, Essential Truths, Internet of Things, marketing, smart home

For good reason, most discussions of opportunities with the Internet of Things focus on the potential to improve businesses’ operating efficiency or creating new revenue streams.

But what if the IoT could also bring out the hidden 6-yr. old in each of us? What if it could allow us to invent — enchanted objects?

That’s the premise of IoT polymath David Rose’s Enchanted Objects: Design, Human Desire, and the Internet of Things.

Enchanted Objects: Design, Human Desire, and the Internet of Things

Rose is both a stalwart of the MIT Media Lab and a pioneering, serial IoT entrepreneur. Oh, and he’s got an impish grin that shows you he is still as delighted at tinkering with things as he was as a little boy in his grandfather’s workshop:

“Grandfather’s tools were constructed and used with a respect for human capabilities and preferences. They fit human bodies and minds. They were a pleasure to work with and to display. They made us feel powerful, more skilled and capable than we were without them. They hung or nestled quietly, each in its place, and never made us feel stupid or overwhelmed. They were, in a word, enchanting.”

Rose fears that’s not the path we’re heading down with most current techno-products, dismissing them as “cold, black slabs … [resulting in a ] colder, more isolated, less humane world. Perhaps it is more efficient, but we are less happy.”  Yea!

By contrast, enchanted objects resonate with our deepest desires:

“The experiences that do enchant us reach into our hearts and souls. They come from the exotic place of  ‘once upon a time.’ They help us realize fundamental human desires. The fantastic technologies we have invented over the centuries , the ones of ancient tales and science fiction, enable us to do things that human beings earnestly want to do but cannot do without a little (or a lot) of help from technology. They make it possible to fly, communicate without words, be invisible, live forever, withstand powerful forces, protect ourselves from any harm, see farther and travel faster than the greatest athletes. They are tools that make us incredible, supercapable versions of ourselves. These are the visions and stories of our most beloved authors of fiction and fantasy — Tolkien and C. S. Lewis and J. K. Rowling and the Grimms — and the realities of fantastic characters such as Cinderella, Dick Tracy, James Bond, Superman, and Wonder Woman. The designers creating enchanted objects must, therefore, think of themselves as something more than manipulators of materials and masters of form. They must think beyond pixels, connectivity, miniaturization , and the cloud. Our training may be as engineers and scientists, but we must also see ourselves as wizards and artists, enchanters and storytellers, psychologists and behaviorists.”(my emphasis).

Rose discusses a number of the products he’s designed, such as the Ambient Orb, which can be hacked to unobtrusively (the physiological phenomenon that makes them work is called “pre-attentive processing” in case you’re looking for a term to throw around at a cocktail party…) display all sorts of information, from stock market trends to energy consumption and the Ambient Umbrella, whose handle glows if rain is predicted (that one hasn’t been a big success, which I predicted — it’s as easy to lose an expensive, “smart” umbrella as a $10 one. I prefer the IFTTT recipe that has your HUE lights blink blue if rain is predicted, reminding you to take your utterly conventional, cheap umbrella…), as well as one of my favorites, the Vitality Glow Cap, which can reduce the billions in wasted medical spending attributable to people not taking their prescriptions.

Skype Cabinet

And then there’s one that every child or grandparent will love, the Skype Cabinet, a square that sits in your living room, and, when the door is opened, shazaam, there is your grandchild or grandparent, instantly connected with you via Skype. Enchantment indeed!

However, the real meat of the book is his methodology for those of us to whom enchantment doesn’t come as naturally. First, Rose lists seven basic human drives that designers should try to satisfy: omniscience, telepathy (human-to-human communication), safekeeping, immortality, teleportation (that’s high on my personal list after my recent up-close-and-personal encounters with rogue deer.), and expression.

Then Rose explains how technology, especially sensors, will allow meeting these desires through products that sense their surroundings and can interact with us.  In terms of my IoT “Essential Truths,” I’d classify enchanted objects as exemplifying “What Can You Do Now That You Couldn’t Do Before,” because we really couldn’t interact with products in the past.  Other examples in this category that I’ve cited before range from the WeMo switches that helped me make peace with my wife and the life-saving Tell-Spec that lets you find food allergies.

Other thought-provoking sections of the book include “Seven Abilities of Enchantment,  “Five Steps on the Ladder of Enchantment,” and “Six Future Fantasies,” the latter of which is must reading for product designers and would-be entrepreneurs who want to come up with fundamentally new products that will exploit the IoT’s full potential for transformation.

The other day I finally met with Mahira Kalim, the SAP IoT marketing director who whipped my thinking into shape for the “Managing the Internet of Things Revolution” i-guide.  She asked me for examples of the kind of radical transformation through the IoT that are already in existence.  I suspect that some of Rose’s inventions fall into that category, but, more important, Enchanted Objects provides the roadmap and checklist for those who want to create the next ones!  Get it, devour it, and profit from it!

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