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February 26 2014

Hurdles to the Internet of Things prove more social than technical

Last Saturday’s IoT Festival at MIT became a meeting-ground for people connecting the physical world. Embedded systems developers, security experts, data scientists, and artists all joined in this event. Although it was called a festival, it had a typical conference format with speakers, slides, and question periods. Hallway discussions were intense.

However you define the Internet of Things (O’Reilly has its own take on it, in our Solid blog site and conference), a lot stands in the way of its promise. And these hurdles are more social than technical.

Participants eye O'Reilly booksParticipants eye O'Reilly books

Participants eye O’Reilly books (Credit: IoT Festival)

Some of the social discussion we have to have before we get the Internet of Things rolling are:

  • What effects will all this data collection, and the injection of intelligence into devices, have on privacy and personal autonomy? And how much of these precious values are we willing to risk to reap the IoT’s potential for improving life, saving resources, and lowering costs?

  • Another set of trade-offs involve competing technical goals. For instance, power consumption can constrain features, and security measures can interfere with latency and speed. What is the priority for each situation in which we are deploying devices? How do we make choices based on our ultimate goals for these things?

  • How do we persuade manufacturers to build standard communication protocols into everyday objects? For those manufacturers using proprietary protocols and keeping the data generated by the objects on private servers, how can we offer them business models that makes sharing data more appealing than hoarding it?

  • What data do we really want? Some industries are already drowning in data. (Others, such as health care, have huge amounts of potential data locked up in inaccessible silos.) We have to decide what we need from data and collect just what’s useful. Collection and analysis will probably be iterative: we’ll collect some data to see what we need, then go back and instrument things to collect different data.

  • How much can we trust the IoT? We all fly on planes that depend heavily on sensors, feedback, and automated controls. Will we trust similar controls to keep self-driving vehicles from colliding on the highway at 65 miles per hour? How much can we take humans out of the loop?

  • Similarly, because hubs in the IoT are collecting data and influencing outcomes at the edges, they require a trust relationship among the edges, and between the edges and the entity who is collecting and analyzing the data.

  • What do we need from government? Scads of data that is central to the IoT–people always cite the satellite GIS information as an example–comes from government sources. How much do we ask the government for help, how much do we ask it to get out of the way of private innovators, and how much can private innovators feed back to government to aid its own efforts to make our lives better?

  • It’s certain that IoT will displace workers, but likely that it will also create more employment opportunities. How can we retrain workers and move them to the new opportunities without too much disruption to their lives? Will the machine serve the man, or the other way around?

We already have a lot of the technology we need, but it has to be pulled together. It must be commercially feasible at a mass production level, and robust in real-life environments presenting all their unpredictability. Many problems need to be solved at what the Jim Gettys (famous for his work on the X Window System, OLPC, and bufferbloat) called “layer 8 of the Internet”: politics.

Large conference hallLarge conference hall

Large conference hall. I am in striped olive green shirt at right side of photo near rear (Credit: IoT Festival)

The conference’s audience was well-balanced in terms of age and included a good number of women, although still outnumbered by men. Attendance was about 175 and most of the conference was simulcast. Videos should be posted soon at the agenda site. Most impressive to me was the relatively small attrition that occurred during the long day.

Isis3D, a sponsor, set up a booth where their impressive 3D printer ratcheted out large and very finely detailed plastic artifacts. Texas Instruments’ University Program organized a number of demonstrations and presentations, including a large-scale give away of LaunchPads with their partner, Anaren.

Isis3D demos their 3D printerIsis3D demos their 3D printer

Isis3D demos their 3D printer (Credit: IoT Festival)

Does the IoT hold water?

One application of the IoT we could all applaud is reducing the use of water, pesticide, and fertilizer in agriculture. This application also illustrates some of the challenges the IoT faces. AgSmarts installs sensors that can check temperature, water saturation, and other factors to report which fields need more or less of a given resource. The service could be extended in two ways:

  • Pull in more environmental data from available sources besides the AgSmarts devices. For instance, Dr. Shawana Johnson of Global Marketing Insight suggested that satellite photos (we’re back to that oft-cited GIS data) could show which fields are dry.

  • Close the loop by running all the data through software that adjusts the delivery of water or fertilizer with little or no human intervention. This is a big leap in sophistication, reviving my earlier question about trusting the IoT. Closing the loop would require real-time analysis of data from hundreds of locations. It’s worth noting that AgSmarts offers a page about Analytics, but all it says right now is “Coming Soon.”

Lights, camera, action

A couple other interesting aspects of the IoT are responsive luminaires (light fixtures) and unmanned aerial vehicles, which can track things on the ground through cameras and other sensors.

Consumer products to control indoor lights are already available. Lighting expert John Luciani reported that outdoor lights are usually coordinated through the Zigbee wireless protocol. Some applications for control over outdoor lighting include:

  • Allowing police in their cruisers to brighten the lights during an emergency.

  • Increasing power to LEDs gradually over time, to compensate for their natural dimming.

  • Identifying power supplies that are nearing the end of their life, because LEDs can last much longer than power supplies.

Lights don’t suffer from several of the major constraints that developers struggle with when using many IoT devices. Because luminaires need a lot of power to cast their light, they always have a power source that is easily high enough to handle their radio communications and other computing needs. Second, there is plenty of room for a radio antenna. Finally, recent ANSI standards have allowed a light fixture to contain more control wires.

Thomas Almholt of Texas Instruments reported that Texas electric utilities have been installing smart meters. Theoretically, these could help customers and utilities save money and reduce usage, because rates change every 15 minutes and most customers have no window on these changes. But the biggest benefit they discovered from the smart meters was quite unexpected: teams came out to houses when the meters started to act in bizarre ways, and prevented a number of fires from being starting by the rogue meters.

A presentation on UAVs and other drones (not all are air-borne) highlighted uses for journalism, law enforcement, and environmental tracking, along with the risks of putting too much power in the hands of those inside or outside of government who possess drones.

MIT’s SENSEable City Lab, as an example of a positive use, measures water quality in the nearby Charles River through drones, producing data at a much more fine-gained level than what could be measured before, spacially and temporally.

Kade Crockford of the Massachusetts ACLU laid out (through a video simulation as scary as it was amusing) the ways UAVs could invade city life and engage in creepy tracking. Drones can go more places than other surveillance technologies (such as helicopters) and can detect our movements without us detecting the drones. The chilling effects of having these robots virtually breathe down our necks may outweigh the actual abuses perpetrated by governments or other actors. This is an illustration of my earlier point about trust between the center and the edges. (Crockford led a discussion on privacy in the conference, but I can’t report on it because I felt I needed to attend a different concurrent session.)

Protocols such as the 802.15 family and Zigbee permit communication among devices, but few of these networks have the processing power to analyze the data they produce and take action on their own. To store their data, base useful decisions on it, and allow humans to view it, we need to bring their data onto the larger Internet.

One tempting solution is to use the cellular network in which companies have invested so much. But there are several challenges to doing so.

  • Cell phone charges can build up quickly.

  • Because of the shortage of phone numbers, an embedded device must use a special mobile subscriber ISDN number (MSISDN), which comes with limitations.

  • To cross the distance to cell towers, radios on the devices need to use much more power than they need to communicate over local wireless options such as WiFi and Bluetooth.

A better option, if the environment permits, is to place a wireless router near a cluster of devices. The devices can use a low-power local area network to communicate with the router, which is connected to the Internet by cable or fiber.

When a hub needs to contact a device to send it a command, several options allow the device to avoid wasting power keeping its radio on. The device can wake up regularly to poll the router and get the command in the router’s response. Alternatively, the router can wake the device when necessary.

Government and the IoT platform

One theme coming out of State of the Union addresses and other White House communications is the role of innovation in raising living standards. As I’ve mentioned, there was a bit of discussion at the conference about jobs and what IoT might do to them. Job creation is one of the four goals of the SmartAmerica Challenge run by the Presidential Innovation Fellows program. The other three are saving lives, creating new business opportunities, and improving the economy.

I was quite disappointed that climate change and other environmental protections were left off the SmartAmerica list. Although I applaud the four goals, I noticed that each pleases a powerful lobbying constituency (the health industry, chambers of commerce, businesses, and unions). The environment is the world’s most urgent challenge, and one that millions of people care about, but big money isn’t behind the cause.

Two people presenting the SmartAmerica Challenge suggested that most of the technologies enabling IoT have been developed already. What we need are open and easy-to-use architectures, and open standards that turn each layer of the system into a platform on which others are free to innovate. The call for open standards–which can also create open markets–also came from Bill Curtis of ARM.

Another leading developer in the computer field, Bob Frankston, advised us to “look for resources, not solutions.” I take this to mean we can create flexible hardware and software infrastructure that many innovators can use as platforms for small, nimble solutions. Frankston’s philosophy, as he put it to me later, is “removing the barriers to rapid evolution and experimentation, thus removing the need for elaborate scenarios.”

Bob Frankston speakingBob Frankston speaking

Bob Frankston speaking (Credit: IoT Festival)

Dr. Johnson claimed that government agencies can’t share a lot of their applications for their data because of security concerns, and predicted that each time a tier of government data is published, it will be greeted by an explosion of innovation from the private sector.

However, government can play another useful role. One speaker pointed out that it can guide the industry to use standards by requiring those standards in its own procurements.

Standards we should all learn

Both Almholt and Curtis laid out protocol stacks for the IoT, with a lot of overlap. Both agreed that many Internet protocols in widespread use were inappropriate for IoT. For instance, connections on the IoT tend to be too noisy and unreliable for TCP to work well. Another complication is that an 802.15.4 packet has a maximum size of 127 bytes, and IPv6 (the addressing system of choice for mobile devices) takes up at least 40. Clever reuse of data between packets can reduce this overhead.

Curtis said that, because most Internet standards are too complex for the constrained devices in the IoT, these devices tend to run proprietary protocols, creating data silos. He also called for devices that use less than 10 milliwatts of power. Almholt said that devices will start harvesting electricity from light, vibration, and thermal sources, thus doing without batteries altogether and running for long periods without intervention.

Some of the protocols that show promise for the IoT include:

  • 6LoWPAN or successors for network-layer transmission.

  • The Constrained Access Protocol (CoAP) for RESTful message exchange. By running over UDP instead of TCP and using binary headers instead of ASCII, this protocol achieves most of the benefits of HTTP but is more appropriate for small devices.

  • The Time Synchronized Mesh Protocol (TSMP) for coordinating data transmissions in an environment where devices contend for wireless bandwidth, thus letting devices shut down their radios and save power when they are not transmitting.

  • RPL for defining and changing routes among devices. This protocol sacrifices speed for robustness.

  • eDTLS, a replacement for the TLS security standard that runs over UDP.

Adoption of these standards would lead to a communication chasm between the protocol stack used within the LAN and the one used with the larger outside world. Therefore, edge devices would be devoted to translating between the two networks. One speaker suggested that many devices will not be provided with IP addresses, for security reasons.

Challenges that remain

Research with impacts on the IoT is flourishing. I’ll finish this article with a potpourri of problems and how people are addressing them:

  • Gettys reported on the outrageous state of device security. In Brazil, an enormous botnet has been found running just on the consumer hubs that people install in their homes and businesses for Internet access. He recommended that manufacturers adopt OpenWRT firmware to protect devices, and that technically knowledgeable individuals install it themselves where possible.

  • Although talking over the Internet is a big advance for devices, talking to each other over local networks at the radio layer (using for instance the 802.15.4 standards) is more efficient and enables more rapid responses to the events they monitor. Unfortunately, according Almholt, interoperability is a decade away.

  • Mobility can cause us to lose context. A recent day-to-day example involves the 911 emergency call system, which is supposed to report the caller’s location to the responder. When people gave up their landlines and called 911 from cell phones, it became much harder to pinpoint where they were. The same thing happen in a factory or hospital when a staffer logs in from a mobile device.

Whether we want the IoT to turn on devices while we sit on the couch (not necessarily an indulgence for the lazy, but a way to let the elderly and disabled live more independently) or help solve the world’s most pressing problems in energy and water management, we need to take the societal and technological steps to solve these problems. Then let the fun begin.


If you are interested in the collision of hardware and software, and other aspects of the convergence of physical and digital worlds, subscribe to the free Solid Newsletter — and to learn more about the Solid Conference coming to San Francisco in May, visit the Solid website.

Four short links: 26 February 2014

  1. Librarybox 2.0fork of PirateBox for the TP-Link MR 3020, customized for educational, library, and other needs. Wifi hotspot with free and anonymous file sharing. v2 adds mesh networking and more. (via BoingBoing)
  2. Chicago PD’s Using Big Data to Justify Racial Profiling (Cory Doctorow) — The CPD refuses to share the names of the people on its secret watchlist, nor will it disclose the algorithm that put it there. [...] Asserting that you’re doing science but you can’t explain how you’re doing it is a nonsense on its face. Spot on.
  3. Cloudwash (BERG) — very good mockup of how and why your washing machine might be connected to the net and bound to your mobile phone. No face on it, though. They’re losing their touch.
  4. What’s Left of Nokia to Bet on Internet of Things (MIT Technology Review) — With the devices division gone, the Advanced Technologies business will cut licensing deals and perform advanced R&D with partners, with around 600 people around the globe, mainly in Silicon Valley and Finland. Hopefully will not devolve into being a patent troll. [...] “We are now talking about the idea of a programmable world. [...] If you believe in such a vision, as I do, then a lot of our technological assets will help in the future evolution of this world: global connectivity, our expertise in radio connectivity, materials, imaging and sensing technologies.”

February 24 2014

Four short links: 24 February 2014

  1. Understanding Understanding Source Code with Functional Magnetic Resonance Imaging (PDF) — we observed 17 participants inside an fMRI scanner while they were comprehending short source-code snippets, which we contrasted with locating syntax error. We found a clear, distinct activation pattern of five brain regions, which are related to working memory, attention, and language processing. I’m wary of fMRI studies but welcome more studies that try to identify what we do when we code. (Or, in this case, identify syntax errors—if they wanted to observe real programming, they’d watch subjects creating syntax errors) (via Slashdot)
  2. Oobleck Security (O’Reilly Radar) — if you missed or skimmed this, go back and reread it. The future will be defined by the objects that turn on us. 50s scifi was so close but instead of human-shaped positronic robots, it’ll be our cars, HVAC systems, light bulbs, and TVs. Reminds me of the excellent Old Paint by Megan Lindholm.
  3. Google Readying Android Watch — just as Samsung moves away from Android for smart watches and I buy me and my wife a Pebble watch each for our anniversary. Watches are in the same space as Goggles and other wearables: solutions hunting for a problem, a use case, a killer tap. “OK Google, show me offers from brands I love near me” isn’t it (and is a low-lying operating system function anyway, not a userland command).
  4. Most Winning A/B Test Results are Illusory (PDF) — Statisticians have known for almost a hundred years how to ensure that experimenters don’t get misled by their experiments [...] I’ll show how these methods ensure equally robust results when applied to A/B testing.

February 20 2014

Four short links: 20 February 2014

  1. Practical Typography — informative and elegant.
  2. Nokia Treasure Tag — Bluetooth-chatty locators for keyrings, wallets, etc.
  3. Stanford Guidelines for Web Credibility — signals for those looking to identify dodgy content, as well as hygiene factors for those looking to provide it.
  4. App Trains You to See Farther (Popular Mechanics) — UltimEyes exercises the visual cortex, the part of our brain that controls vision. Brain researchers have discovered that the visual cortex breaks down the incoming information from our eyes into fuzzy patterns called Gabor stimuli. The theory behind UltimEyes is that by directly confronting the eyes with Gabor stimuli, you can train your brain to process them more efficiently—which, over time, improves your brain’s ability to create clear vision at farther distances. The app shows you ever fuzzier and fainter Gabor stimuli.

January 08 2014

The emergence of the connected city

Photo: Millertime83Photo: Millertime83

If the modern city is a symbol for randomness — even chaos — the city of the near future is shaping up along opposite metaphorical lines. The urban environment is evolving rapidly, and a model is emerging that is more efficient, more functional, more — connected, in a word.

This will affect how we work, commute, and spend our leisure time. It may well influence how we relate to one another, and how we think about the world. Certainly, our lives will be augmented: better public transportation systems, quicker responses from police and fire services, more efficient energy consumption. But there could also be dystopian impacts: dwindling privacy and imperiled personal data. We could even lose some of the ferment that makes large cities such compelling places to live; chaos is stressful, but it can also be stimulating.

It will come as no surprise that converging digital technologies are driving cities toward connectedness. When conjoined, ISM band transmitters, sensors, and smart phone apps form networks that can make cities pretty darn smart — and maybe more hygienic. This latter possibility, at least, is proposed by Samrat Saha of the DCI Marketing Group in Milwaukee. Saha suggests “crowdsourcing” municipal trash pick-up via BLE modules, proximity sensors and custom mobile device apps.

“My idea is a bit tongue in cheek, but I think it shows how we can gain real efficiencies in urban settings by gathering information and relaying it via the Cloud,” Saha says. “First, you deploy sensors in garbage cans. Each can provides a rough estimate of its fill level and communicates that to a BLE 112 Module.”

BLE112_M_RGB_frontBLE112_M_RGB_front

As pedestrians who have downloaded custom “garbage can” apps on their BLE-capable iPhone or Android devices pass by, continues Saha, the information is collected from the module and relayed to a Cloud-hosted service for action — garbage pick-up for brimming cans, in other words. The process will also allow planners to optimize trash can placement, redeploying receptacles from areas where need is minimal to more garbage-rich environs.

“It should also allow greater efficiency in determining pick-up schedules,” said Saha. “For example, in some areas regular scheduled pick-ups may be best. But managers may find it’s also a good idea to put some trash collectors on a roving basis to service cans when they’re full. That could work well for areas where there’s a great deal of traffic and cans fill up quickly but unpredictably — and conversely, in low-traffic areas, where regular pick-up isn’t necessary. Both situations would benefit from rapid-response flexibility.”

Garbage can connectivity has larger implications than just, well, garbage. Brett Goldstein, the former Chief Data and Information Officer for the City of Chicago and a current lecturer at the University of Chicago, says city officials found clear patterns between damaged or missing garbage cans and rat problems.

“We found areas that showed an abnormal increase in missing or broken receptacles started getting rat outbreaks around seven days later,” Goldstein said. “That’s very valuable information. If you have sensors on enough garbage cans, you could get a temporal leading edge, allowing a response before there’s a problem. In urban planning, you want to emphasize prevention, not reaction.”

Such Cloud-based app-centric systems aren’t suited only for trash receptacles, of course. Companies such as Johnson Controls are now marketing apps for smart buildings — the base component for smart cities. (Johnson’s Metasys management system, for example, feeds data to its app-based Paoptix Platform to maximize energy efficiency in buildings.) In short, instrumented cities already are emerging. Smart nodes — including augmented buildings, utilities and public service systems — are establishing connections with one another, like axon-linked neurons.

But Goldstein, who was best known in Chicago for putting tremendous quantities of the city’s data online for public access, emphasizes instrumented cities are still in their infancy, and that their successful development will depend on how well we “parent” them.

“I hesitate to refer to ‘Big Data,’ because I think it’s a terribly overused term,” Goldstein said. “But the fact remains that we can now capture huge amounts of urban data. So, to me, the biggest challenge is transitioning the fields — merging public policy with computer science into functional networks.”

There are other obstacles to the development of the intelligent city, of course. Among them: how do you incentivize enough people to download apps sufficient to achieve a functional connected system? Indeed, the human element could prove the biggest fly in the ointment. We may resist quantifying ourselves to such a degree, even for the sake of our cities.

On the other hand, the connected city exists to serve people, not the other way around, observes Drew Conway, senior advisor to the New York City Mayor’s Office of Data Analytics and founder of the data community support group DataGotham. People ultimately act in their self-interest, and if the connected city brings boons, people will accept and support it. But attention must be paid to unintended consequences, emphasizes Conway.

“I never forget that humanity is behind all those bits of data I consume,” says Conway. “Who does the data serve, after all? Human beings decided why and where to put out those sensors, so data is inherently biased — and I always keep the human element in mind. And ultimately, we have to look at the true impacts of employing that data.”

As an example, continues Conway, “say the data tells you that an illegal conversion has created a fire hazard in a low-income residential building. You move the residents out, thus avoiding potential loss of life. But now you have poor people out on the street with no place to go. There has to be follow-through. When we talk of connections, we must ensure that some of those connections are between city services and social services.”

Like many technocrats, Conway also is concerned about possible threats to individual rights posed by data collected in the name of the commonwealth.

“One of New York’s most popular programs is expanding free public WiFi,” he says. “It’s a great initiative, and it has a lot of support. But what if an agency decided it wanted access to weblog data from high-crime areas? What are the implications for people not involved in any criminal activity? We haven’t done a good job of articulating where the lines should be, and we need to have that debate. Connected cities are the future, but I’d welcome informed skepticism on their development. I don’t think the real issue is the technical limitations — it’s the quid pro quo involved in getting the data and applying it to services. It’s about the trade-offs.”


For more on the convergence of software and hardware, check out our Solid Conference.

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December 10 2013

Podcast: news that reaches beyond the screen

Reporters, editors and designers are looking for new ways to interact with readers and with the physical world–drawing data in through sensors and expressing it through new immersive formats.

In this episode of the Radar podcast, recorded at News Foo Camp in Phoenix on November 10, Jenn and I talk with three people who are working on new modes of interaction:

Along the way:

For more on the intersection of software and the physical world, be sure to check out Solid, O’Reilly’s new conference program about the collision of real and virtual.

Subscribe to the O’Reilly Radar Podcast through iTunesSoundCloud, or directly through our podcast’s RSS feed.

November 04 2013

Software, hardware, everywhere

Real and virtual are crashing together. On one side is hardware that acts like software: IP-addressable, controllable with JavaScript APIs, able to be stitched into loosely-coupled systems—the mashups of a new era. On the other is software that’s newly capable of dealing with the complex subtleties of the physical world—ingesting huge amounts of data, learning from it, and making decisions in real time.

The result is an entirely new medium that’s just beginning to emerge. We can see it in Ars Electronica Futurelab’s Spaxels, which use drones to render a three-dimensional pixel field; in Baxter, which layers emotive software onto an industrial robot so that anyone can operate it safely and efficiently; in OpenXC, which gives even hobbyist-level programmers access to the software in their cars; in SmartThings, which ties Web services to light switches.

The new medium is something broader than terms like “Internet of Things,” “Industrial Internet,” or “connected devices” suggest. It’s an entirely new discipline that’s being built by software developers, roboticists, manufacturers, hardware engineers, artists, and designers.

Ten years ago, building something as simple as a networked thermometer required some understanding of electrical engineering. Now it’s a Saturday-afternoon project for a beginner. It’s a shift we’ve already seen in programming, where procedural languages have become more powerful and communities have arisen to offer free help with programming problems. As the blending of hardware and software continues, the physical world will become democratized: the ranks of people who can address physical challenges from lots of different backgrounds will swell.

The outcome of all of this combining and broadening, I hope, will be a world that’s safer, cleaner, more efficient, and more accessible. It may also be a world that’s more intrusive, less private, and more vulnerable to ill-intentioned interference. That’s why it’s crucial that we develop a strong community from the new discipline.

Solid, which Joi Ito and I will present on May 21 and 22 next year, will bring members of the new discipline together to discuss this new medium at the blurred line between real and virtual. We’ll talk about design beyond the computer screen; software that understands and controls the physical world; new hardware tools that will become the building blocks of the connected world; frameworks for prototyping and manufacturing that make it possible for anyone to create physical devices; and anything else that touches both the concrete and abstract worlds.

Solid’s call for proposals is open to the public, as is the call for applications to the Solid Fellowships—a new program that comes with a stipend, a free pass to Solid, and help with travel expenses for students and independent innovators.

The business implications of the new discipline are just beginning to play out. Software companies are eyeing hardware as a way to extend their offerings into the physical world—think, for instance, of Google’s acquisition of Motorola and its work on a driverless car—and companies that build physical machines see software as a crucial component of their products. The physical world as a service, a business model that’s something like software as a service, promises to upend the way we buy and use machines, with huge implications for accessibility and efficiency. These types of service frameworks, along with new prototyping tools and open-source models, are making hardware design and manufacturing vastly easier.

A few interrelated concepts that I’ve been thinking about as we’ve sketched out the idea for Solid:

  • APIs for the physical world. Abstraction, modularity, and loosely-coupled services—the characteristics that make the Web accessible and robust—are coming to the physical world. Open-source libraries for sensors and microcontrollers are bringing easy-to-use and easy-to-integrate software interfaces to everything from weather stations to cars. Networked machines are defining a new physical graph, much like the Web’s information graph. These models are starting to completely reorder our physical environment. It’s becoming easier to trade off functionalities between hardware and software; expect the proportion of intelligence residing in software to increase over time.
  • Manufacturing made frictionless. Amazon’s EC2 made it possible to start writing and selling software with practically no capital investment. New manufacturing-as-a-service frameworks bring the same approach to building things, making factory work fast and capital-light. Development costs are plunging, and it’s becoming easier to serve niches with specialized hardware that’s designed for a single purpose. The pace of innovation in hardware is increasing as the field becomes easier for entrepreneurs to work in and financing becomes available through new platforms like Kickstarter. Companies are emerging now that will become the Amazon Web Services of manufacturing.
  • Software intelligence in the physical world. Machine learning and data-driven optimization have revolutionized the way that companies work with the Web, but the kind of sophisticated knowledge that Amazon and Netflix have accumulated has been elusive in the offline world. Hardware lets software reach beyond the computer screen to bring those kinds of intelligence to the concrete world, gathering data through networked sensors and exerting real-time control in order to optimize complicated systems. Many of the machines around us could become more efficient simply through intelligent control: a furnace can save oil when software, knowing that homeowners are away, turns down the thermostat; a car can save gas when Google Maps, polling its users’ smartphones, discovers a traffic jam and suggests an alternative route—the promise of software intelligence that works above the level of a single machine. The Internet stack now reaches all the way down to the phone in your pocket, the watch on your wrist, and the thermostat on your wall.
  • Every company is a software company. Software is becoming an essential component of big machines for both the builders and the users of those machines. Any company that owns big capital machines needs to get as much out of them as possible by optimizing their operation with software, and any company that builds machines must improve and extend them with layers of software in order to be competitive. As a result, a software startup with promising technology might just as easily be bought by a big industrial company as by a Silicon Valley software firm. This has important organizational, cultural, and competency impact.
  • Complex systems democratized. The physical world is becoming accessible to innovators at every level of expertise. Just as it’s possible to build a Web page with only a few hours’ learning, it’s becoming easier for anyone to build things, whether electronic or not. The result: realms like the urban environment that used to be under centralized control by governments and big companies are now open to innovation from anyone. New economic models and communities will emerge in the physical world just as they’ve emerged online in the last twenty years.
  • The physical world as a service. Anything from an Uber car to a railroad locomotive can be sold as a service, provided that it’s adequately instrumented and dispatched by intelligent software. Good data from the physical world brings about efficient markets, makes cheating difficult, and improves quality of service. And it will revolutionize business models in every industry as service guarantees replace straightforward equipment sales. Instead of just selling electricity, a utility could sell heating and cooling—promising to keep a homeowner’s house at 70 degrees year round. That sales model could improve efficiency and quality of life, bringing about incentive for the utility to invest in more efficient equipment and letting it take advantage of economies of scale.
  • Design after the screen. Our interaction with software no longer needs to be mediated through a keyboard and screen. In the connected world, computers gather data through multiple inputs outside of human awareness and intuit our preferences. The software interface is now a dispersed collection of conventional computers, mobile phones, and embedded sensors, and it acts back onto the world through networked microcontrollers. Computing happens everywhere, and it’s aware of physical-world context.
  • Software replaces physical complexity. A home security system is no longer a closed network of motion sensors and door alarms; it’s software connected to generic sensors that decides when something is amiss. In 2009, Alon Halevy, Peter Norvig, and Fernando Pereira wrote that having lots and lots of data can be more valuable than having the most elegant model. In the connected world, having lots and lots of sensors attached to some clever software will start to win out over single-purpose systems.

These are some rough thoughts about an area that we’ll all spend the next few years trying to understand. This is an open discussion, and we welcome thoughts on it from anyone.

August 26 2013

Le service client à l'heure de l'internet des objets - Harvard Business Review

Le service client à l’heure de l’internet des objets - Harvard Business Review
http://blogs.hbr.org/cs/2013/08/customer_service_in_the_age_of.html

Aujourd’hui, un service client innovant demande d’être capable de communiquer sur de multiples plateformes... Demain, il nécessitera aussi d’intégrer l’internet des objets. Pour s’y préparer, estime Duke Chung, il faut dès à présent construire des bases de connaissances plus solides, plus contextualisées, et rendre les #services plus faciles d’accès. Demain, les appareils devront être capables de prédire les problèmes liés à l’utilisation qui est faite d’eux, estime Duke Chung, qui est le cofondateur de (...)

#iot #internetofthings #internetdesobjets

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