Neato! Just heard from SAP that reaction to “Managing the Internet of Things Revolution,” my e-guide to IoT strategy for C-level executives, has been so positive that they’re translating it into 4 languages. C’est magnifique!
As I’ve remarked before, writing the Managing the Internet of Things Revolution e-guide to IoT strategy for SAP was an eye-opener for me, shifting my attention from the eye-popping opportunities for radical reinvention through the IoT (products as services, user-customizable products, seamless smart phone-car integration, etc.) to very practical ways the IoT could begin optimizing companies’ current operations TODAY (BTW: much-deserved shout-out to SAP’s Mahira Kalim: it was dialogue with her that led to this insight!).
In that vein, I was blown away at this week’s IoT Global Summit by the roll-out of Egburt by Camgian (little confusing, BTW: the company site touts a new Egburt site, but I couldn’t find anything separate from the company’s existing site).
Egburt stresses two crucial, inter-related obstacles to widespread IoT solution deployment by mainstream businesses:
- low cost-of-ownership sensing (by using very little energy, thereby extending battery life)
- reducing potentially huge cloud-computing costs (because of the sheer volume of 24/7 sensor data) by allowing “fog computing,” where the processing would be done right at the collection process, with only the small amount of really relevant data being passed on to a central location.
The highlight of the product launch was a live demo of Egburt in real-time use at a chain of dollar stores in the south, monitoring a wide range of factors, from floor traffic to freezer operation (Camgian pointed out the system paid for itself in the first month of operation when it recorded failure of a freezer when the store was unoccupied, in time for immediate repairs to avoid loss of frozen foods).
Think about it: the very volume of Big Data possible with constant monitoring by a whole range of sensors can also be the IoT’s undoing. Since all that’s of interest in many cases is data that deviates from the norm, doesn’t it make sense to process that data at the collection point, then only pass on the deviations?
The company has targeted three IoT segments:
- retail to reduce heating and lighting, and maximize sales through tracking foot traffic patterns to optimize product placement.
- infrastructure: with sensors at key points such as bridges that will detect flooding and stress.
- smart cities: optimizing emergency response.
In a sponsored white paper by ABI Research, “Evolution of the Internet of Things: from connected to intelligent devices,” they documented the benefits of going beyond first-generation, “connected,” IoT devices that were just sensors collecting and passing on data, to a second generation of “intelligent ones” such as Egburt the combine sensors and processing and offer not only lower operating costs but also — critically — more data security:
- “Communication Latency: Handling more processing at the network’s edge reduces latency from the device’s actions. Use cases that are highly time-sensitive and require immediate analysis of, or response to, the collected sensor data are, in general, unfeasible under cloud- centric IoT architectures, especially if the data are sent over long distances.
- “Data Security: By and large, sensitive and business-critical operational data are safer when encrypted adequately on the endpoint level. Unintelligent devices transmitting frequent and badly secured payloads to the cloud are generally more vulnerable to hacking and interception by unauthorized parties. Additionally, many enterprises may need to secure and control their machine data on the edge level for compliance reasons.
“Total Cost of Ownership: Perhaps most significantly, the paradigm shift can reduce the IoT systems’ total cost of ownership, or TCO. Intelligent devices are usually more expensive than less sophisticated alternatives, but their TCO over a long service life can be substantially lower.”
IMHO, for the IoT to be widely deployed, especially in SMEs, devices such as Egburt that reduce the cost of collecting and processing data are a critical component.
(PROMINENT DISCLAIMER: I actually won a FitBit in Camgian’s drawing at the conference. That has no impact on this review. Had I won the iPhone 6 that they also gave away, I would have totally been in the bag, LOL…)
When I buy the much-hyped smart refrigerator, you’ll know I’ve officially gone around the bend, and have officially surrendered to IoT hype: it makes sense for those who buy a ton of processed foods with bar codes on them, but I just can’t see the value to those of us who buy a lot of label-less veggies from farmers markets, for example.
In a close second place on my personal list of those IoT devices that violate one of my Essential Truths of the IoT: “just because you can do something doesn’t mean you should” would be a smart washing machine.
As the Washington Post wrote about Whirlpool’s $1,699 “smart” washer,
“Few expected ‘smart’ machines would fly off the shelves. They’re expensive, and Americans don’t typically replace their washers and dryers all that often. But analysts say the problem is bigger than that. Today’s smartest washer and dryer set won’t fold your clothes, erase wrinkles or stop you from mixing reds and whites. It won’t even move a load from one machine to the other. So what’s the point?”
I know there are going to be some false starts in creating IoT-enabled products that really do provide value, and good for Whirlpool for experimenting, but I do wonder whether something we used to call “common sense” is sorely lacking in some companies’ IoT decision-making.
IMHO, it would really be helpful if my washer and dryer could go on late at night to take advantage of utilities’ off-peak pricing as part of their smart grid initiatives (to their credit, as you’ll see from the photo of the companion smart dryer, a smart grid link is part of these appliances)
. However, I suspect that would be easily possible if the utilities just published APIs so some smart IFTTT user could create a “recipe” that would turn on an utterly-conventional washer that was plugged into a WeMo smart plug (hmm: did a search for that, and found a recipe that would automatically turn off a washer plugged into a WeMo if a Nest alarm detected a fire: nice, but rather low on my list of what I’d want to have done in case of a fire….).
So, yea, smart appliances, but let’s also make sure that one of the questions companies ask before committing to a really expensive initiative is: “do we really need it?”
I’ll be live-blogging for the next two days from the 2nd Internet of Things Global Summit.
- Edith Ramirez, FTC chair:
- potential for astounding benefits to society, transforming every activity
- risks: very technology that allows this can also gather info for companies and your next employer
- possible consumer loss of confidence in connected devices if they don’t think privacy w
- 3 challenges:
- adverse uses
- security of the data
- collection of the data
- key steps companies should take:
- security front and center
- deidentify data
- transparent policies
- data will provide “startlingly complete pictures of us” — sensors can already identify our moods, even progression of neurological diseases
- how will the data be used? will TV habits be shared with potential employers? Will it paint picture of you that others will see, but you won’t
- will it exacerbate current socio-economic disparities?
- potential for data breaches such as Target grows as more data is collected
- FTC found some companies don’t take even most basic protections. Small size and cheap cost of some sensors may inhibit data protections
- build security in from beginning
- security risk assessment
- test security measures before launch
- implement defense and depth approach
- encryption, especially for health data.
- FTC action against TrendNet
- follow principle of “data minimization,” only what’s needed, and dispose of it afterwards.
- she’s skeptical of belief that there should be no limits on collection of data (because of possible benefits)
- de-identified data: need dual approach — commit to not re-identify data
- clear and simple notice to consumers about possible use of data.
- Apple touting that it doesn’t sell data from Health App — critical to building consumer trust
- transparency: major FTC priority. FTC review of mobile apps showed broad and vague standards on data collection & use.
- Ilkka Lakaniemi, chair, FIWARE Future Internet PPP, EU perspective on IoT:
- lot easier to start IoT businesses in Silicon Valley because of redundant regulations in EU
- Open Standard Platform + Sustainable Innovation Ecosystem. “Synergy Platform”
- Mark Bartolomeo, vp of integrated solutions, Verizon:
- Bakken Shale area visit: “landscape of IoT” solutions — pipeline monitoring, water monitoring, etc.
- concerned about rapid urbanization: 30% of city congestion caused by drivers looking for parking. $120B wasted in time and fuel yearly.
- cars: “seamless nodes” of system.
- market drivers & barriers:
- increased operational efficiency, new revenue streams, better service, comply with regulators, build competitive edge
- fragmented ecosystem, complex development, significant back end obstacles
- they want integrated systems.
- need to remove barriers: aging infrastructure, congestion, public safety, economics
- remove complexity
- economies of scale: common services
- trend to car sharing, smart grid
- yea: highlighting intellistreets — one of my 1st fav IoT devices!!
- Verizon working primarily on parking & traffic congestion on the East Coast, and water management in CA.
- Nigel Cameron: nation-state receding, cities and corporations on ascendency
- Sokwoo Rhee, NIST: Cyber-Physical Systems — emphasis on systems dynamics, data fed back into system, makes it autonomous. Did Smart America Challenge with White House. Fragmentation on device level. Demonstrate tangible effects through collaborations. Examples: health care systems, transactive energy management, smart emergency response, water distribution, air quality. 24 projects. Round Two is application of the projects to actual cities. Now 26 teams.
- Joseph Bradley, VP, IoT Practice, Cisco Consulting: value isn’t in the devices, but the connections. Intersection of people, data, process, and things. Increase City of Nice’s parking revenue 40-60% without raising taxes through smart parking. They project $19 trillion in value over 10 years from combo of public and private innovations. Smart street lighting: reduces crime, property values increase, free wi-fi from the connected street lights. Barcelona is Exhibit A for benefits. Need: comprehensive strategy (privacy is a contextual issue: depends on the benefits you receive), scalability, apps, data analytics, transparency, powerful network foundation, IoT catalyst for breaking down silos, IoT must address people and process.
- Ron Sege, chair and ceo of Echelon Corp: got started with smart buildings, 25 yrs. old. Why now with IoT: ubiquitous communications, low cost, hyper-competition, cloud. They do outdoor & indoor lighting and building systems. Challenges: move to one infrastructure/multiple use cases, will IT learn about OT & visa-versa?, reliability: critical infrastructure can’t fail & must respond instantly.
- Christopher Wolf, Future of Privacy Forum: flexible, use-based privacy standards. Industry-wide approach to privacy: auto industry last week told NISTA about uniform privacy standards for connected cars (neat: will have to blog that…).
- Peter Marx, chief innovation officer, City of LA: big program to reduce street lights with LEDs: changed whole look of city at night & saves lot of money. 6 rail lines being built there. Adding smart meters for water & power. EV chargers on street lights. Held hackathon for young people to come up with ideas to improve city. Procurement cycles are sooo arcane that he suggests entrepreneurs don’t do business with city — he just tries to enable them.
Outside the City:
- Darrin Mylet, Adaptrum: Using “TV white space spectrum” in non-urban areas. Spectrum access critical:need mix of spectrum types. Where do we need spectrum? Most need in non-line-of-sight areas such as trees, etc. Examples: not only rural, but also some urban areas (San Jose); Singapore; Africa; redwood forests;
- Arturo Kuigami, World Bank: examples in developing nations: (he’s from Peru); most of global migration is to smaller cities; look at cities as ecosystems; “maker movement” is important — different business models: they partnered with Intel and MIT on “FabLabs” in Barcelona this year. MoMo — water access point monitoring in Tanzania. Miroculus: created by a global ad hoc team — cheap way to make cancer diagnosis: have identified 3-4 types of cancers it can diagnose. Spirometer to measure COPD, made by a 15-year old! “IoT can be a global level playing field.”
- Chris Rezendes, INEX Advisors: Profitable sustainability: by instrumenting the physical world, we can create huge opportunities for a wide range of people outside our companies. Focusing on doing a better job of instrumenting and monitoring our groundwater supplies: very little being done in SW US right now (INEX investing in a startup that is starting this monitoring). If we have better data on groundwater, we can do a better job of managing it. “Embrace complexity upfront” to be successful.
- Shudong Chen, Chinese Academy of Sciences: talking about the Chinese food security crisis because of milk production without a food production license. Government launched “Wuxi Food Science & Technology Park.”
- Tobin Richardson, Zigbee Alliance: critical role of open, global standards. Zigbee LCD lights now down to $15.
- Cees Links, GreenPeak Technologies: Leader in Zigbee-based smart home devices. Smart home waay more complex than wi-fi. 1m chips a week, vs. 1 million for whole year of 2011. “Not scratching the surface.” Small data — many small packets.
- Todd Green, CEO PubNub: data stream network.
- no killer app for the smart home.. Controlling by your phone not really that great a method.
- FTC agrees with me: a few adverse stories (TrendNet baby cam example) can be really bad for an industry in its infancy.
- always hole in security. For example, you can tell if no one’s home because volume of wi-fi data drops.W
- FTC: consumer ed critical part of their work. Working now on best practices for home data protection.
- mitigation after a security breach? Always be open, communicate (but most hunker down!).
Beyond Cost Savings: Forging a Path to Revenue Generation
- Eric Openshaw: (had tech problems during his preso: very important one — check the Deloitte The Internet of Things white paper for details) cost savings through IoT not enough for sustainable advantage: need to produce new revenue to do that. Defined ecosystem shaping up, which creates clarity, breaks down silos.
- areas: smart grid, health care, home automation, cars, industrial automation
- study the GE jet model for health care: what if doctors were paid to keep us healthy.
- need comprehensive understanding of the change issues
- be very specific: singular asset class, etc. — so you get early victories
- companies will have overarching, finite roadmap
- security & privacy dichotomy: differentiate between personal health care data and data from your washing machine. Most of us will share all sorts of information if there’s something in return
- get focused on customer and product life cycle — that’s where the money will be. Focus on operating metric level. This is most far-reaching tech change he’s seen.
Managing Spectrum Needs
- Julius Knapp, Chief, FCC Office of Engineering & Technology: new opportunity to combine licensed and unlicensed space. Described a number of FCC actions to reconsider role of various types of spectrum. “Hard to predict I0T’s long-term spectrum needs” because industry is new: they’ll watch developments in the field.
- Prof. H. Nwana, exec. director of Dynamic Spectrum Alliance: most spectrum usually not used in most places at most time. His group working to use changes to spectrum to end digital divide: (used incredible map showing how much of world, including US, China, India, W. Europe, could be fitted into Africa).
- Carla Rath, VP for Wireless Policy, Verizon: “in my world, the network is assumed.” Need for more spectrum — because of growth in mobile demand. Praises US govt. for trying to make more spectrum available. Don’t want to pigeonhole IoT in certain part of spectrum: allow flexibility. Tension between flexibility and desire for global standards when it comes to IoT.
- Philip Marnick, group director of spectrum policy, Ofcom UK: no single solution. Market determines best use. Some applications become critical (public safety, etc.) — must make sure people using those are aware of chance of interference.
- Hazem Moakkit, vp of spectrum development for 03b (UK satellite provider for underserved areas of developing world): “digital divide widened by IoT if all are not on board.” Fair allocation of spectrum vital.
- interesting question: referred to executive of a major farm equipment manufacturer whose products are now sensor-laden (must be John Deere…) and is frustrated because the equipment won’t work in countries such as Germany due to different bands.
Architecting the IoT: Sensing, Networking & Analytics:
- Tom Davenport: IoT highly unpredictable. “Great things about standards is there’s so many to choose from” — LOL. Will IoT revolution be more top down or bottom up?
- Gary Butler, CEO, Camgian: announcing an edge system for IoT. Driven by sensor info. Need new networking architecture to combine sensing and analytics to optimize business processes, manage risk. Systems now built from legacy equipment, not scalable. They’re announcing new platform: Egburt. Applicable to smart cities, retailing, ifrastructure (I’ll blog more about this soon!!). “Intelligence out of chaos.” Anomaly detection. Real-time analysis at the device level. Focus on edge computing. Must strengthen the ROI.
- Xiaolin Lu, Texas Instruments fellow & director of IoT Lab: Working in wearables, smart manufacturing, smart cities, smart manufacturing, health care, automotive. TI claims it has all IoT building blocks: nodes, gateway/bridge or router/cloud. Power needs are really critical, with real emphasis on energy harvesting from your body heat, vibration, etc. Challenges: sensing and data analytics, robust connectivity, power, security, complexity, consolidation of infrastructure and data. Big advocates for standards. They work on smart grid.
- Steve Halliday, president, RAIN RFID: very involved in standards. 4 BILLION RFID tags shipped last year. Don’t always want IP devices. Power not an issue w/ RFID because they get their power from the reader. Think RFID will be underpinning of IoT for long time. Lot of confusion in many areas about IoT, especially in manufacturing.
- Sky Mathews, IBM CTO: IBM was one of earliest in the field, with Smarter Planet. Lot of early ones were RFID. A variety of patterns emerging for where and how data is processed. What APIs do you want to expose to the world? “That’s where the real leaps of magnitude will occur” — so design that in from beginning.
‘People’ Side of the IoT: meeting consumer expectations:
- Mark Eichorn, asst. director, Consumer Protection Bureau, FTC: companies that have made traditional appliances & now web-enable them aren’t always ready to deal with data theft. Security and privacy: a lot don’t have privacy policies at all. At their workshop, talk about people being able to hack your insulin readings.
- Daniel Castro, sr. analyst, Center for Data Innovation: thinks that privacy issue has been misconstrued: what people really care about is keeping data from government intrusion. Can car be designed so a cop could pull it over automatically (wow: that’s a thought!). Chance for more liability with misuse of #IoT data.
- Linda Sherry, director of national priorities, Consumer Action: “convenience, expectations and trust.” “What is the IoT doing beside working?” Connecting everything may disenfranchise those who aren’t connected. Need to register those who collect data – hmm. Hadn’t heard that one before. Even human rights risks, stalking, etc. — these issues must be thought about. Can algorithms really be trusted on issues such as insurance coverage? How do you define particularly sensitive personal data? “Hobbling the unconnected” when most are connected? “Saving consumers from themselves.” “Document the harms.” Make sure groups with less $ can really participate in multi-stakeholder negotiations.
- Stephen Pattison, vp of public affairs, ARM Holdings: disagrees with Linda about slowing things down: we want to speed up IoT as instrument of transformation. We need business model for it. Talks about how smart phone didn’t explode until providers started subsidizing purchase. He suspects that one model might be that a company would provide you whole range of smart appliances in return for your data. “Getting data right matters.” “Freak events” drive concerns about data security & privacy: they generate concern and, sometimes, “heavy-handed” regulation.
Industry must work together on framework for data that creates confidence by public. Concerns about data are holding back investment in the field. They’re working with AMD on a framework: consumers own their own data — must start with that (if they do, people will cooperate); not all data equally sensitive — need chain of custody to keep data anomyzed; security must be right at the edge; simplify terms and conditions.
Sometimes thinks that, in talking about IoT, it’s like talking about cars in 1900, but we managed to create a set of standards that allowed it to grow: “rules of the road,” etc.
Despite my passion for all things Apple and the incredible functionality that comes from Tim Cook’s passion for integrating all parts of the ecosystem seamlessly (and, as I’ve noted in prior disclaimers, my part-time work at the Apple Store ..), I don’t think there’s any doubt when it comes to the Internet of Things that open standards win out.
That’s because they meet the test of my favorite Essential Truth, “who else can use this data?”
It goes back to my Data Dynamite book and my work with Vivek Kundra when he was opening up data in the District of Columbia before becoming the US CIO: when you share data, you empower end users and can go beyond your own developers’ talents and interests, to harvest others’ interests and developments.
Here’s a great example. Opower’s OpenStat API enables the electric industry’s only open thermostat management platform. It allows any smart thermostat provider to participate in existing Opower-managed utility thermostat programs. It combines energy usage, billing, parcel and weather data to engage customers, drive measurable energy efficiency, and deliver reliable demand response. It already has 95 partner utilities, 50 million (really? that sounds high to me…) homes in 35 states sharing data.
By contrast, Nest (which of course was created by Apple alums) had to create a specific API to allow sharing its data.
“This API is Nest’s answer to the Learning Thermostat’s lack of Z-Wave or ZigBee wireless communication. Nest came under fire from the CEDIA crowd when the Learning Thermostat launched since it wouldn’t work within even $100k home automation systems. The thermostat wasn’t friendly with others. It wouldn’t talk to other home automation products using the legacy home automation protocols. This API could change everything.“
The jury’s still out — and it will really be interesting to see how many other companies decide to integrate with Apple’s new Health and Home apps. On one hand, a proliferation of standards just retards more creative API mashups, a la IFTTT (my heros!!). On the other, seamless integration and ease-of-use, the Apple hallmarks, could go a long way to ingraining the IoT into consumers’ daily lives.
What do you think?
Just arrived @ Wearables + Things conference (I’ll speak on “Smart Aging” tomorrow). Hmm: there’s one noteworthy player absent from the conference: those guys from Cupertino. Wonder why they’re not there (perhaps in stealth mode??)
Conference already underway, about to have 2 new product reveals!
- iStrategyLabs, “Dorothy,” connects your shoe to your phone. You’re stuck in a conversation, need way to leave. What if you could click your heels together three times (get it, Dorothy???) and you’d get a bail-out call (or you can trigger an IFTTT recipe or call for a pizza…). “Ruby” goes in shoe. OK, this ain’t as significant as either the Lechal haptic shoe, but who knows how it might evolve…
- Atlas Wearables’ fitness product, Atlas. Their goals is seamless, frictionless experiences. “What if device could recognize specific motions you’re making?” This is really cool: it recognizes and records a wide range of fitness activities, such as push-ups. I really don’t like fact that my Jawbone can’t do that, so this looks good!
Sony Mobile, Kristian Tarnhed. Challenges:
- g data overload. They have a “lifelog” app that tries to make sense of all the data.
- too many devices that want your attention. Make them complement smart phone as much as possible.
- is it really wearable, usable?
Very funny: no one mentions Apple. 10-ton gorilla in the room????
Amazing preso by Jim McKeeth: “Is Thought the Future of Wearable Input?” Guy wearing Google Glass is controlling a drone! Wouldn’t that be an incredible thing for “Smart Aging” to allow a frail elder to control various household things just by thinking them?
Oren Michels, chief strategist, Intel (he was an API pioneer at Mashery):
- APIs make connections. The Epocrates platform from Athena Health is an example: may save $3.5B.
- Also working in travel. Example is Sabre, which has switched to an open API.
- APIs create better customer experiences: Apple Pay! 30% of Starbucks revenue from its phone purchase app.
Quick time to market: Coke was able to restock vending machines instantly during 2012 Olympics through API.
- better healthcare monitoring: give small devices processing power through cloud
- connected car ecosystem (BMW iConnected Services, MyCityWay, TomTom’s WebFleet)
- Snapshot from Progressive
- Inrix — “data for planning smart cities”
This, IMHO, is sooo important: open APIs are great example of my Essential Truth of “who else can use this data?” — you don’t have to develop every kewl use for your device yourself: open the API and others will help!
Peter Li, Atlas Wearables (the company that debuted their new device yesterday):
- iPhone: remember, it was a 3-in-one solution.
- sensors now commoditized: cheap & tiny
- he was a biomedical engineer
- synergistic benefits by combining data streams
- era of augmentation: making you better without you having to think about it.
- frictionless actions
“sensors root of the revolution”
Brad Wilkins, Nike science director:
- he’s exercise physiologist
- they have whole detailed process to understand physiological phenomena. Role of sensor is the describe the phenomena. Then apply that data to enhance athlete potential
Noble Ackerson, Lynxfit, “Hacking Your Way Through Rehab With Wearables”
- they let content publishers (they work with Stanford Health, UnderArmour, etc.) in rehab area to push info to devices. Prescribe workouts. Device agnostic.
- They’ve imported 65 different activities into program.
- Track: heart rate, pace, position, speed, endurance, breathing, sentiment.
Panel: Jim Kohlenberger, JK Strategies; Jose Garcia, Samsung; Mark Hanson, BeClose; Alison Remsen, Mobile Future:
- BeClose is working with seniors!!
- Samsung working with airports to make flying experience more enjoyable.
- BeClose: take some of burden off health care system.
- how government can help: faster networks. “First, do no harm.” — Digital Hypocratic Oath.
DHS (sorry, didn’t get his name):
- In a crisis, “data must inform at the speed of thought” Brilliant
- To be operational, data must be intuitive, instinctive, interoperable, and wearable.
- Creating “Next Generation First Responder”
- Creating fire jackets with sensors built in.
Proximity-aware apps using iBeacon:
- beacons are Bluetooth v4.0 Low Energy transmitters.
- mobiles can identify and determine proximity to beacon: usual range is 25 to 40 m, but you can tune it to much shorter range.
- beacons broadcast unique identifier for the place. Also provide Measured Power Value: what’s signal strength of beacon at specific distance.
- the beacon only sends out a unique identifier, which triggers the app contains all the info that drives the experience.
- app is notified whether you’re in immediate range, near, or far range (might even want to present content when person exits the area).
- beacons protect privacy by being opt-in. They are transmit only: don’t receive or collect signals from mobile devices.
- Apple requires that the app specifically ask user to allow proximity-aware mobile app to access their location.
- non iBeacon versions: AltBeacon (Radius Network’s opsolves en source alternative), and other ones that specific companies will introduce, optimized for their products.
- Radius multi-beacon: solves fragmentation problem or multiple, incompatible beacon ad types. Their RadBeacons handle both types.
- RadBeacon: USB powered, coin-cell battery powered, AA battery powered. Most beacons will only last about a month before battery change.
- Future of beacons: will be split in market: corporate (one of their questions has rolled out more than 16,000 — they won’t powered or long-battery-life versions & remote monitoring) vs. consumers (cheap & disposable). Will be integrated into equipment (wifi access-point hotspots, POS terminals, fuel dispensers, self-service kiosks.
Privacy & Security Panel:
- There is real risk of personal data being intercepted. “No perfect solutions.”
- Data can be stored on smart phone OR uploaded to cloud. What control does user have? What if you have health wearable that sends info on blood pressure, etc., to cloud, where it gets shared with companies, and, for example, it can link data to your Facebook data, could be risk of disclosure.
- HIPPA and variety of other regulations can come into play.
- Things moving very quickly, data captured & used. Example of Jawbone data from people who were sleeping during California quake: users upset because the data was disclosed to news media — even though it was just aggregated, was creepy!
- FTC went after the Android flashlight app that was aggregating data. A no-no.
- have to make it simple to understand in statements about how your data will be collected & used.
- Tiles: if the device is gone from home, will send alert to ALL Tile devices. You might be able to modify the software so you (bad guy) could retrieve it it while the owner would think it was still lost. Stalker might even be able to use this data..
Scott Amyx, Amyx & McKinsey, “The Internet of Things Will Disrupt Everything”:
- Example of McLean, the developer of intermodal shipping container. Hmm: does Amyx know about how Freight Farms has created IoT-enhanced food growing in freight containers???
- future of M2M will allow sensors with embedded processors — smarter than today’s computers.
- memory: over time, memory will only grow.
- wifi: most locked networks are idle most of day. Harness them.
- lifi: 2-way network to turn any light as a network. Higher-speed than wifi.
- mesh networks (long-time fascination of mine, especially in disasters): every node creates more powerful network. Can’t be controlled by a central gov.
- can disrupt telecom (mesh networks)
- shifting consumer data from cloud to you
- they’re testing a system that would tell what a person really feels while they’re in store, film companies can test from pilot whether people will really like it. Creepy??
- working with Element to bring this to fashion show: would gauge reaction.
- IoT won’t be great leap, but gradual trend (like my argument that companies should begin with IoT by using it to optimize current manufacturing).
- incredible vision of how you’ll drive to a biz appt. in driverless car, you’ll get briefing on the meeting from your windshield.
- opportunities at every stage of the IoT development shift.
I’ll admit it: until I began writing the “Managing the Internet of Things Revolution” guide to Internet of Things strategy for SAP, I was pre-occupied with the IoT’s gee-wiz potential for radical transformation: self-driving cars, medical care in which patients would be full partners with their doctors, products that customers would be able to customize after purchase.
Then I came to realize that this potential for revolution might be encouraging executives to hold off until the IoT was fully-developed, and, in the process, ignoring low-hanging fruit: a wide range of ways that the IoT could dramatically increase the efficiency of current operations, giving them a chance to experiment with limited, less-expensive IoT projects that would pay off rapidly and give them the confidence and understanding necessary to launch more dramatic IoT projects in the near future.
This is crucially important for IoT strategies: instead waiting for a radical transformation (which can be scary), view it instead as a continuum, beginning with small, relatively-low cost steps which will feed back into more dramatic steps for the future.
Now, there’s a great new study, “Industrial Internet Insights Report for 2015,” from GE and Accenture, that documents many companies are in the early stages of implementing such an incremental approach, with special emphasis on the necessary first step, launching Big Data analytics — and that they are already realizing tangible benefits. It is drawn from a survey of companies in the US, China, India, France, Germany, the UK, and South Africa.
The report is important, so I’ll review it at length.
Understandably, it was skewed toward the industries where GE applies its flavor of the IoT (the “Industrial Internet”): aviation, health care, transportation, power generation, manufacturing, and mining, but I suspect the findings also apply to other segments of the economy.
The summary underscores a “sense of urgency” to launch IoT initiatives:
“The vast majority (of respondents) believe that Big Data analytics has the power to dramatically alter the competitive landscape of industries just within the next year, and are investing accordingly…” (my emphasis).
84% said Big Data analytics “has the power to shift the competitive landscape for my industry” within just the next year, and 93% said they feared new competitors will enter the field to leverage data. Wow: talk about short-term priorities!
It’s clear the authors believe the transformation will begin with Big Data initiatives, which, IMHO, companies should be starting anyways to better analyze the growing volume of data from conventional sources. 73% of the companies already are investing more than 20% of their overall tech budget on Big Data analytics — and some spend more than 30%! 80 to 90% said Big Data analytics was either the company’s top priority or at least in the top 3.
One eye-opening finding was that 53% of respondents said their board of directors was pushing the IoT initiatives. Probably makes sense, in that boards are expected to provide necessary perspective on the company’s long-term health.
GE and Accenture present a 4-step process to capitalize on the IoT:
- Start with the exponential growth in data volumes
- Add the additional data volume from the IoT
- Add growing analytics capability
- and, to add urgency, factor in “the context of industries where equipment itself or patient outcomes are at the heart of the business” where the ability to monitor equipment or monitor patient services can have significant economic impact and in some cases literally save lives [nothing like throwing the fear of God into the mix to motivate skeptics!].
“All in all, only about one-third of companies (36 percent) have adopted Big Data analytics across the enterprise. More prevalent are initiatives in a single operations area (16 percent) or in multiple but disparate areas (47 percent)…. The lack of an enterprise-wide analytics vision and operating model often results in pockets of unconnected analytics capabilities, redundant initiatives and, perhaps most important, limited returns on analytics investments.”
Most of the companies surveyed are moving toward centralization of data management to break down the silos. 49% plan to appoint a chief analytics officer to run the operation, and most will hire skilled data analysts or partner with outside experts (insert Accenture here, LOL…).
- assess risks and consequences
- develop objectives and goals
- enforce security throughout the supply chain.
- use mitigation devices specifically designed for Industrial Control Systems
- establish strong corporate buy-in and governance.
For the longer term, the report also mentioned a consistent theme of mine, that companies must begin to think about dramatic new business models, such as substituting value-added services instead of traditional sales of products such as jet engines. This is a big emphasis with GE. It also emphasizes another issue I’ve stressed in the “Essential Truths,” i.e. partnering, as the mighty GE has done with startups Quirky and Electric Imp:
“Think of the partnering taking place among farm equipment, fertilizer, and seed companies and weather services, and the suppliers needed to provide IT, telecom, sensors, analytics and other products and services. Ask: ‘Which companies are also trying to reach my customers and my customers’ customers? What other products and services will talk to mine, and who will make, operate and service them? What capabilities and information does my company have that they need? How can we use this ecosystem to extend the reach and scope of our products and services through the Industrial Internet?'”
While the GE/Accenture report dwelt only on large corporations, I suspect that many of the same findings would apply to small-to-medium businesses as well, and that the falling prices of sensors and IoT platforms will mean more smart companies in this category will begin to launch incremental IoT strategies to first optimize their current operations and then make more radical changes.
Read it, or be left in the dust!
PS: as an added bonus, the report includes a link to the GE “Industrial Internet Evaluator,” a neat tool I hadn’t seen before. It invites readers to “see how others in your field are leveraging Big Data analytics for connecting assets, monitoring, analyzing, predicting and optimizing for business success.” Check it out!
I’m currently reading Erik Brynjolfsson (say that one fast three times…) and Andy McAfee’s brilliant The Second Machine Age, which I highly recommend as an overview of the opportunities and pitfalls of what they call “brilliant technologies.”
While they don’t specifically mention the IoT, I was riveted by one section in which they contrasted current digital innovation with past technologies, using economist Paul Romer‘s term “recombinant innovation”:
“Economic growth occurs whenever people take resources and rearrange them in ways that make them more valuable…. Every generation has perceived the limits to growth that finite resources and undesirable side effects would pose if no new … ideas were discovered. And every generation has underestimated the potential for finding new … ideas. We consistently fail to grasp how many ideas remain to be discovered… Possibilitities do not merely add up, they multiply.” (my emphasis)
I felt like Dr. Pangloss, who was surprised to learn he’d been speaking prose all his life: I realized Romer’s term and definition was a more elegant version of what I’ve written before, especially about IFTTT, about an Essential Truth of the IoT — that sharing data is critical to achieving the IoT’s full potential. IFTTT is a great example of Romer’s argument in practice: individuals are “taking resource and rearrang(ing) them in ways that make them more valuable.” As Brynjolfsson and McAfee write:
““.. digital innovation is recombinant innovation in its purest form. Each development becomes a building block for future innovations. Progress doesn’t run out; it accumulates. And the digital world doesn’t respect any boundaries. It extends into the physical one, leading to cars and planes that drive themselves, printers that make parts, and so on….We’ll call this the ‘innovation-as-building-block’ view of the world..” (again, my emphasis)
This is such a powerful concept. Think of Legos — not those silly ones that dominate today, where they are so specialized they can only be used in making a specific kit — but the good ol’ basic ones that could be reused in countless ways. It’s why I happen to believe that all the well-thought-out projections on the IoT’s potential size probably are on the low side: there’s simply no way that we can predict now all the creative, life-saving, money-saving, or quality-of-life-enhancing ways the IoT will manifest itself until people within and outside of organizations take new IoT devices and use them in IFTTT-like “Recipes” that would never have occurred to the devices’ creators. But beware: none of this will happen if companies use proprietary standards or don’t open their APIs and other tools to all those who can benefit.
Wow: glad I put up with all of the tech problems during the Apple product launch today: the Apple Watch was worth it! It really seems as if it will be the killer device/app for the Internet of Things consumer market, and I think it may also be the lynchpin for my vision of “smart aging,” which would link both wearable health devices and smart home devices.
The elegant, versatile displays (it remains to be seen how easy it will be for klutzes like me to use the Digital Crown and some of the other navigation tools) plus the previously announced Health and Home Apps that are part of iOS 8 could really be the glue that brings together Quantified Self and smart home devices, making “smart aging” possible.
- sorry, but I think it could kill the Lechal haptic shoes before they get off the ground: why have to pay extra for shoes that will vibrate to tell you where to go when your watch can do the same thing with its “Taptic Engine”?
- I think I’ll also ditch my Jawbone UP, as much as I love it, for the Apple Watch: the video on how the Activity and Workout apps will work makes it look incredibly simple to view your fitness data instantly, vs. having to open an app on your phone.
- (Just dreaming here): if they can pull off that neat “Milanese Loop” band on one of the versions that clamps to itself, what about not just a heart beat monitor, but a band that converts into a blood-pressure cuff? Guess that wouldn’t be accurate on the wrist, anyway, huh?
I’ve been trying to come up with a layman’s analogy to use in explaining to skeptical executives about how dramatic the Internet of Things’ impact will be on every aspect of business and our lives, and why, if anything, it will be even more dramatic than experts’ predictions so far (see Postscapes‘ roundup of the projections).
See whether you thing “Collective Blindness” does justice to the potential for change?
What if there was a universal malady known as Collective Blindness, whose symptoms were that we humans simply could not see much of what was in the world?
Even worse, because everyone suffered from the condition, we wouldn’t even be aware of it as a problem, so no one would research how to end it. Instead, for millennia we’d just come up with coping mechanisms to work around the problem.
Collective Blindness would be a stupendous obstacle to full realization of a whole range of human activities (but, of course, we couldn’t quantify the problem’s impact because we weren’t even aware that it existed).
Collective Blindness has been a reality, because vast areas of our daily reality have been unknowable in the past, to the extent that we have just accepted it as a condition of reality.
Consider how Collective Blindness has limited our business horizons.
We couldn’t tell when a key piece of machinery was going to fail because of metal fatigue.
We couldn’t tell how efficiently an entire assembly line was operating, or how to fully optimize its performance.
We couldn’t tell whether a delivery truck would be stuck in traffic.
We couldn’t tell exactly when we’d need a parts shipment from a supplier, nor would the supplier know exactly when to do a new production run to be read.
We couldn’t tell how customers actually used our products.
That’s all changing now. Collective Blindness is ending, …. and will be eradified by the Internet of Things.
What do you think? Useful analogy?