"iot" entries

The Internet of Things is really about software

Our new report, "What is the Internet of Things," traces the IoT's transformations and impact.

The Internet of Things (IoT) is everywhere right now. It appeared on the cover of the Harvard Business Review in November, and observers saw it in practically every demo at CES.

One of the reasons that it’s ubiquitous is that it bears on practically everything. A few years ago, many companies might plausibly have argued that they weren’t affected by developments in software. If you dealt in physical goods, it was hard to see how software that existed strictly in the virtual realm might touch your business.

The Internet of Things changes that; the kinds of software intelligence that have already revolutionized industries like finance and advertising are about to revolutionize all the other industries.

Mike Loukides and I have traced out our idea of the Internet of Things and its impacts in a report, “What is the Internet of Things,” that’s available for free here.

As much as we all love the romance and gratification of hardware, the Internet of Things is really about software; the hardware just links the Internet to the rest of the world. If you think of the IoT as a newly developing area in software, it’s easy to draw out some characteristics of it that are analogous to things we’ve seen in web software over the last decade or so. Read more…

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Four short links: 20 January 2015

Four short links: 20 January 2015

Govt IoT, Collective Intelligence, Unknown Excellence, and Questioning Scalability

  1. Matt Webb Joining British Govt Data Service — working on IoT for them.
  2. Reading the Mind in the Eyes or Reading between the Lines? Theory of Mind Predicts Collective Intelligence (PLoS) — theory of mind abilities are a significant determinant of group collective intelligence even when, as in many online groups, the group has extremely limited communication channels. Phone/Skype calls, emails, and chats are all intensely mental activities, trying to picture the person behind the signal.
  3. MIT Faculty Search — two open gigs at MIT, one around climate change and one “undefined.” Great job ad.
  4. Scalability at What Cost?evaluation of these systems, especially in the academic context, is lacking. Folks have gotten all wound-up about scalability, despite the fact that scalability is just a means to an end (performance, capacity). When we actually look at performance, the benefits the scalable systems bring start to look much more sketchy. We’d like that to change.
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Four short links: 14 January 2015

Four short links: 14 January 2015

IoT and Govt, Exactly Once, Random Database Subset, and UX Checking

  1. Internet of Things: Blackett Review — the British Government’s review of Internet of Things opportunities around government. Government and others can use expert commissioning to encourage participants in demonstrator programmes to develop standards that facilitate interoperable and secure systems. Government as a large purchaser of IoT systems is going to have a big impact if it buys wisely. (via Matt Webb)
  2. Exactly Once Semantics with Kafka — designing for failure means it’s easier to ensure that things get done than it is to ensure that things get done exactly once.
  3. rdbms-subsetter — open source tool to generate a random sample of rows from a relational database that preserves referential integrity – so long as constraints are defined, all parent rows will exist for child rows. (via 18F)
  4. UXcheck — a browser extension to help you do a quick UX check against Nielsen’s 10 principles.
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Four short links: 13 January 2015

Four short links: 13 January 2015

Slack Culture, Visualizations of Text Analysis, Wearables and Big Data, and Snooping on Keyboards

  1. Building the Workplace We Want (Slack) — culture is the manifestation of what your company values. What you reward, who you hire, how work is done, how decisions are made — all of these things are representations of the things you value and the culture you’ve wittingly or unwittingly created. Nice (in the sense of small, elegant) explanation of what they value at Slack.
  2. Interpretation and Trust: Designing Model-Driven Visualizations for Text Analysis (PDF) — Based on our experiences and a literature review, we distill a set of design recommendations and describe how they promote interpretable and trustworthy visual analysis tools.
  3. The Internet of Things Has Four Big Data Problems (Alistair Croll) — What the IoT needs is data. Big data and the IoT are two sides of the same coin. The IoT collects data from myriad sensors; that data is classified, organized, and used to make automated decisions; and the IoT, in turn, acts on it. It’s precisely this ever-accelerating feedback loop that makes the coin as a whole so compelling. Nowhere are the IoT’s data problems more obvious than with that darling of the connected tomorrow known as the wearable. Yet, few people seem to want to discuss these problems.
  4. Keysweepera stealthy Arduino-based device, camouflaged as a functioning USB wall charger, that wirelessly and passively sniffs, decrypts, logs, and reports back (over GSM) all keystrokes from any Microsoft wireless keyboard in the vicinity. Designs and demo videos included.
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Four short links: 6 January 2015

Four short links: 6 January 2015

IoT Protocols, Predictive Limits, Machine Learning and Security, and 3D-Printing Electronics

  1. Exploring the Protocols of the Internet of Things (Sparkfun) — Arduino and Arduino-like IoT “things” especially, with their limited flash and SRAM, can benefit from specially crafted IoT protocols.
  2. Complexity Salon: Ebola (willowbl00) — These notes were taken at the 2014.Dec.18 New England Complex Systems Institute Salon focused on Ebola. […] Why don’t we engage in risks in a more serious way? Everyone thinks their prior experience indicates what will happen in the future. Look at past Ebola! It died down before going far, surely it won’t be bad in the future.
  3. Machine Learning Methods for Computer Security (PDF) — papers on topics such as adversarial machine learning, attacking pattern recognition systems, data privacy and machine learning, machine learning in forensics, and deceiving authorship detection.
  4. voxel8Using Voxel8’s 3D printer, you can co-print matrix materials such as thermoplastics and highly conductive silver inks enabling customized electronic devices like quadcopters, electromagnets and fully functional 3D electromechanical assemblies.
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We need an Internet that performs flawlessly, every second of every day

As we increasingly depend on connected devices, primary concerns will narrow to safety, reliability, and survivability.

Editor’s note: this interview with GE’s Bill Ruh is an excerpt from our recent report, When Hardware Meets Software, by Mike Barlow. The report looks into the new hardware movement, telling its story through the people who are building it. For more stories on the evolving relationship between software and hardware, download the free report.

More than one observer has noted that while it’s relatively easy for consumers to communicate directly with their smart devices, it’s still quite difficult for smart devices to communicate directly, or even indirectly, with each other. Bill Ruh, a vice president and corporate officer at GE, drives the company’s efforts to construct an industrial Internet that will enable devices large and small to chat freely amongst themselves, automatically and autonomously. From his perspective, the industrial Internet is a benign platform for helping the world become a quieter, calmer, and less dangerous place.

“In the past, hardware existed without software. You think about the founding of GE and the invention of the light bulb — you turned it on and you turned it off. Zero lines of code. Today, we have street lighting systems with mesh networks and 20 million lines of code,” says Ruh. “Machines used to be completely mechanical. Today, they are part digital. Software is part of the hardware. That opens up huge possibilities.”

A hundred years ago, street lighting was an on-or-off affair. In the future, when a crime is committed at night, a police officer might be able to raise the intensity of the nearby street lights by tapping a smart phone app. This would create near-daylight conditions around a crime scene, and hopefully make it harder for the perpetrators to escape unseen. “Our machines are becoming much more intelligent. With software embedded in them, they’re becoming brilliant,” says Ruh. Read more…

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Biology as the next hardware

Why DNA is on the horizon of the design world.

DNA by John Goode, on Flickr

I’ve spent the last couple of years arguing that the barriers between software and the physical world are falling. The barriers between software and the living world are next.

At our Solid Conference last May, Carl Bass, Autodesk’s CEO, described the coming of generative design. Massive computing power, along with frictionless translation between digital and physical through devices like 3D scanners and CNC machines, will radically change the way we design the world around us. Instead of prototyping five versions of a chair through trial and error, you can use a computer to prototype and test a billion versions in a few hours, then fabricate it immediately. That scenario isn’t far off, Bass suggested, and it arises from a fluid relationship between real and virtual.

Biology is headed down the same path: with tools on both the input and output sides getting easier to use, materials getting easier to make, and plenty of computation in the middle, it’ll become the next way to translate between physical and digital. (Excitement has built to the degree that Solid co-chair Joi Ito suggested we change the name of our conference to “Solid and Squishy.”)

I spoke with Andrew Hessel, a distinguished research scientist in Autodesk’s Bio/Nano/Programmable Matter Group, about the promise of synthetic biology (and why Autodesk is interested in it). Hessel says the next generation of synthetic biology will be brought about by a blend of physical and virtual systems that make experimental iteration faster and processes more reliable. Read more…

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Hardware start-ups now look a lot like software start-ups

Joi Ito on the evolution of manufacturing.

Editor’s note: this interview with Joichi Ito is an excerpt from our recent report, When Hardware Meets Software, by Mike Barlow. The report looks into the new hardware movement, telling its story through the people who are building it. For more stories on the evolving relationship between software and hardware, download the free report.

Joichi Ito is the director of the MIT Media Lab. Ito, who is also co-chair of the O’Reilly Solid Conference, recalls sending a group of MIT students to Shenzhen so they could see for themselves how manufacturing is evolving. “Once they got their heads around the processes in a deep way, they understood the huge differences between prototyping and manufacturing. Design for prototyping and design for manufacturing are fundamentally different,” says Ito. The problem in today’s world, according to Ito, is that “we have abstracted industrial design to the point where we think that we can just throw designs over a wall” and somehow they will magically reappear as finished products.

The trip to Shenzhen helped the students understand the manufacturing process from start to finish. “In Shenzhen, they have a $12 phone. It’s amazing. It has no screws holding it together. It’s clearly designed to be as cheap as possible. It’s also clearly designed by someone who really understands manufacturing and understands what consumers want.”

Ito also sees a significant difference between what’s happening on the factory floors in Shenzhen and the maker movement. “We’re not talking about low-volume, DIY manufacturing,” he says. Instead, Ito’s students are working through the problems and challenges of a real, live paradigm shift — the kind of gut-wrenching upheaval described in Thomas S. Kuhn’s seminal book, The Structure of Scientific Revolutions. From Kuhn’s point of view, a paradigm shift isn’t a cause for celebration or blithe headlines — it’s a sharp and unexpected blow that topples old theories, wrecks careers, and sweeps aside entire fields of knowledge. Read more…

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What you need to know for the hardware-software convergence

Core competencies and essential reading from hardware, software, manufacturing, and the IoT.

As I noted in “Physical and virtual are blurring together,” we now have hardware that acts like software, and software that’s capable of dealing with the complex subtleties of the physical world. So, what must the innovator, the creator, the executive, the researcher, and the artist do to embrace this convergence of hardware and software?

At its core, this is about a shift from discipline toward intent. Individuals and institutions — whether they’re huge enterprises, small start-ups, or nonprofits — must be competent in several disciplines that increasingly overlap, and should be prepared to solve problems by working fluidly across disciplines.

To use Joi Ito’s example, someone who wants to develop a synthetic eye might begin to approach the problem with biology, or electronics, or software, or (most likely) all three together. Many problems can be solved somewhere in a large multidimensional envelope that trades off design, mechanics, electronics, software, biology, and business models. Experts might still do the best work in each discipline, but everyone needs to know enough about all of them to know where to position a project between them.

Below you’ll find the core competencies in the intersection between software and the physical world, and our favorite books and resources for each one.

Electronics for physical-digital applications

  • Practical Electronics, by John M. Hughes: To know what’s possible and where to start, it’s essential to understand both the analog and digital sides of electronics. This is O’Reilly’s authoritative introduction to both analog and digital electronics, with information on circuit design, common parts and techniques, and microcontrollers.
  • Raspberry Pi Cookbook, by Simon Monk: The Raspberry Pi is rapidly becoming the standard embedded computing platform for prototyping and experimentation, with enough computing power to run familiar interpreted programming languages and widely supported operating systems.
  • Arduino Cookbook, by Michael Margolis: The Arduino microcontroller offers a fluid interface between digital and physical; it’s highly extensible and accessible to people with no prior experience in either electronics or code.

Read more…

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Hardware is an elusive constraint on user experience

Andrew “bunnie” Huang on understanding the interplay between software, hardware, and the existing supply chain.

Editor’s note: this interview with Andrew “bunnie” Huang is an excerpt from our recent report, When Hardware Meets Software, by Mike Barlow. The report looks into the new hardware movement, telling its story through the people who are building it. For more stories on the evolving relationship between software and hardware, download the free report.

Andrew “bunnie” Huang has a Ph.D. in electrical engineering from MIT, but he is most famous for reverse engineering the Xbox, establishing his reputation as one of the world’s greatest hardware hackers. He sees an evolving relationship between hardware and software.

“It used to be that products were limited solely by the capability of their hardware. Early radios, for example, had mechanical buttons that acted directly on the physics of the receiver,” says Huang. “As hardware becomes more capable, the user experience of the hardware is more dictated by the software that runs on it. Now that hardware is ridiculously capable — you basically have supercomputers in your pockets that cost next to nothing — pretty much the entire user experience of the product is dictated by the software. The hardware simply serves as an elusive constraint on the user experience.”

Hardware is “a cage,” says Huang, and good software developers learn to work within the constraints of the hardware. “When I work with programmers on new products, I take the first prototype, put it on the desk and I say, ‘Welcome to your new cage.’ That’s the reality. There’s a hard wall. But we try to build the cage big enough so there are options for programmers. A quad core Android phone with a gigabyte of memory is a pretty big cage. Sometimes when programmers feel constrained, they’re just being lazy. There’s always more than one way to skin a cat in the software world.” Read more…

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