- How to Build a Working Digital Computer Out of Paperclips (Evil Mad Scientist) — from a 1967 popular science book showing how to build everything from parts that you might find at a hardware store: items like paper clips, little light bulbs, thread spools, wire, screws, and switches (that can optionally be made from paper clips).
- Moloch (Github) — an open source, large scale IPv4 packet capturing (PCAP), indexing and database system with a simple web GUI.
- Offline Wikipedia Reader (Amazon) — genius, because what Wikipedia needed to be successful was to be read-only. (via BoingBoing)
- Storing and Publishing Sensor Data — rundown of apps and sites for sensor data. (via Pete Warden)
"sensors" entries
Four short links: 8 May 2013
Paperclip Computing, Packet Capture, Offline Wikipedia, and Sensor Databases
Strata Week: Data brokers know more about us than we know
Data brokers, workplace sensor studies, unreported drug side effects revealed in search data, and the dark side of big data.
The lowdown on data brokers, and the use of sensor data in the workplace
ProPublica’s Lois Beckett takes a look this week at data brokers. She says that though Congress is making moves to make such companies give consumers more control over their data and what happens to it, many people not only don’t know these data brokers exist, but they also don’t know the extent of the data gathered and how it’s used.
Defining the industrial Internet
Some broad thoughts on characteristics that define the industrial Internet field.
We’ve been collecting threads on what the industrial Internet means since last fall. More case studies, company profiles and interviews will follow, but here’s how I’m thinking about the framework of the industrial Internet concept. This will undoubtedly continue to evolve as I hear from more people who work in the area and from our brilliant readers.
The crucial feature of the industrial Internet is that it installs intelligence above the level of individual machines — enabling remote control, optimization at the level of the entire system, and sophisticated machine-learning algorithms that can work extremely accurately because they take into account vast quantities of data generated by large systems of machines as well as the external context of every individual machine. Additionally, it can link systems together end-to-end — for instance, integrating railroad routing systems with retailer inventory systems in order to anticipate deliveries accurately.
In other words, it’ll look a lot like the Internet — bringing industry into a new era of what my colleague Roger Magoulas calls “promiscuous connectivity.” Read more…
The inevitability of smart dust
Why general purpose computing will diffuse into our environment.
I’ve put forward my opinion that desktop computing is dead on more than one occasion, and been soundly put in my place as a result almost every time. “Of course desktop computing isn’t dead — look at the analogy you’re drawing between the so called death of the mainframe and the death of the desktop. Mainframes aren’t dead, there are still plenty of them around!”
Well, yes, that’s arguable. But most people, everyday people, don’t know that. It doesn’t matter if the paradigm survives if it’s not culturally acknowledged. Mainframe computing lives on, buried behind the scenes, backstage. As a platform it performs well, in its own niche. No doubt desktop computing is destined to live on, but similarly behind the scenes, and it’s already fading into the background.
The desktop will increasingly belong to niche users. Developers need them, at least for now and for the foreseeable future. But despite the prevalent view in Silicon Valley, the world does not consist of developers. Designers need screen real estate, but buttons and the entire desktop paradigm are a hack; I can foresee the day when the computing designers use will not even vaguely resemble today’s desktop machines.
For the rest of the world? Computing will almost inevitably diffuse out into our environment. Today’s mobile devices are transition devices, artifacts of our stage of technology progress. They too will eventually fade into their own niche. Replacement technologies, or rather user interfaces, like Google’s Project Glass are already on the horizon, and that’s just the beginning.
People never wanted computers; they wanted what computers could do for them. Almost inevitably the amount computers can do for us on their own, behind our backs, is increasing. But to do that, they need data, and to get data they need sensors. So the diffusion of general purpose computing out into our environment is inevitable. Read more…
Driven to distraction: How Veterans Affairs uses monitoring technology to help returning veterans
Fujitsu provides the Sprout device to collect and analyze sensor data in real time
Veterans Affairs is collaborating with Fujitsu on a complex and interesting use of sensor data to help rehabilitate veterans suffering from Post Traumatic Stress Disorder (PTSD). I recently talked about this initiative with Dr. Steven Woodward, Principal Investigator of the study at the VA Palo Alto Health Care System, and with Dr. Ajay Chander, Senior Researcher in Data Driven Health Care at Fujitsu Laboratories of America (FLA).
The study is focused on evaluating strategies for driving rehabilitation. During deployments, veterans adapt their driving behavior to survive in dangerous war zones that are laced with combat fire, ambushes, and the threat of improvised explosive devices. Among veterans suffering from PTSD, these behaviors are hard to unlearn upon their return from such deployments. For example, some veterans veer instinctively into the middle of the road, reacting to deep-seated fears of improvised explosive devices. Others refuse to stop at stop signs for fear of attack. Other risky behaviors range from road rage to scanning the sides of the road instead of focusing on the road ahead. At-fault accident rates are significantly higher for veterans upon return from a deployment than before it.
The VA’s research objective is to understand the triggers for PTSD and discover remedies that will enable veterans to return to normal life. For the study, the VA instrumented a car as well as its veteran driver with a variety of sensors that collect data on how the car is being driven and the driver’s physiology while driving it. These sensors included wireless accelerometers on the brake and accelerator pedals and on the steering wheel, a GPS system, and an EKG monitor placed on the driver and wired to an in-car laptop for real-time viewing of cardiological signals, as well as manual recording of the driver’s state and environmental cues by an in-car psychotherapist. With such a system, the VA’s goal was to record and analyze driving trails of veterans and assess the efficacy of driving rehabilitation techniques.
As Dr. Woodward explained, the VA had been assessing veterans’ driving habits for quite a while before getting introduced to Fujitsu’s real-time monitoring technology. ASsessments had been a significant challenge for multiple reasons. On the data collection and visualization front, the disparate sensors, the laptop, and the power supplies added up to a significant in-car IT footprint. More importantly, since all sensor systems were manufactured by different vendors and didn’t share data with each other, the data streams were not synchronized. This made it difficult for the VA researchers to get an accurate understanding of how the driver’s physiology coupled with the car’s drive and location data. Read more…
Listening for tired machinery
Cheap sensors and sophisticated software keep expensive machines running smoothly
Software is making its way into places where it hasn’t usually been before, like the cutting surfaces of very fast, ultra-precise machine tools.
A high-speed milling machine can run at 42,000 RPM as it fabricates high-quality machine components within tolerances of a few microns. Excessive wear in that environment can lead to a failure that ruins an expensive part, but it’s difficult to use physical means to detect wear on cutting surfaces: human operators can’t see it and detailed microscopic inspections are costly. The result is that many operators simply replace parts on a pre-determined schedule — every two months, perhaps — that ends up being overly conservative.
The researchers’ milling machine, shown with sensors near the cutting device. (Source: X. Li, M.J. Er, H. Ge, O. P. Gan, S. Huang, L.Y. Zhai, S. Linn, Amin J. Torabi, “Adaptive Network Fuzzy Inference System and Support Vector Machine Learning for Tool Wear Estimation in High Speed Milling Processes,” Proceedings of the 38th Annual Conference of the IEEE Industrial Electronics Society, pp. 2809-2814, 2012.)
Enter software: in a paper delivered to the IEEE’s Industrial Electronics Society in Montreal last Thursday*, a group of researchers from Singapore propose a way to use low-cost sensors along with machine learning algorithms to accurately predict wear on machine parts — a technique that could cut costs for manufacturers by lengthening the lifespan of machine parts while avoiding failures.
The group’s demonstration is a promising illustration of the industrial Internet, which promises to bring more intelligence to machines by linking them to networks and integrating them with sophisticated software. Techniques from areas like machine learning, which can be computationally intensive, can thus be available in monitoring parts as small and common as cutting surfaces in milling machines.
Sensor-laden glove brings medical examination to the masses
How a sensor glove can benefit the patient-doctor relationship.
Recently a group of three young entrepreneurs showed off a prototype of a glove that contained sensors useful for medical examinations. Their goals were not merely to make diagnosis easier, but to save the doctor/patient relationship from the alienation of modern technology. Medical student Andrew Bishara came into O’Reilly’s Cambridge studio to discuss the glove’s capabilities, how the creators were inspired to design it, and how they plan to productize it.
Here’s the full video from our discussion:
Highlights from the conversation include:
- Introduction to the glove and its purpose in bringing touch back into medicine. [Discussed at the 0:31 mark]
- Some of the purposes of the sensors. [Discussed at the 2:00 mark]
- Software on the device and in the cloud. [Discussed at the 7:58 mark]
- Creating a marketable product from the glove. [Discussed at the 9:54 mark]
- Open hardware. [Discussed at the 13:39 mark]
- How the developers were inspired by Singularity University. [Discussed at the 15:03 mark]
Four short links: 4 October 2012
Vannevar Bush, Topic Transparency, Ancient Maps, and Concussion Sensors
- As We May Think (Vannevar Bush) — incredibly prescient piece he wrote for The Atlantic in 1945.
- Transparency and Topic Models (YouTube) — a talk from DataGotham 2012, by Hanna Wallach. She uses latent Dirichlet allocation topic models to mine text data in declassified documents where the metadata are useless. She’s working on predicting classification durations (AWESOME!). (via Matt Biddulph)
- Slippy Map of the Ancient World — this. is. so. cool!
- Technology in the NFL — X2IMPACT’s Concussion Management System (CMS) is a great example of this trend. CMS, when combined with a digital mouth guard, also made by X2, enables coaches to see head impact data in real-time and asses concussions through monitoring the accelerometers in a players mouth guard. That data helps teams to decide whether to keep a player on the field or take them off for their own safety. Insert referee joke here.
The complexity of designing for everywhere
Author Rachel Hinman on the future of mobile design and UX.
In her new book The Mobile Frontier, author Rachel Hinman (@Hinman) says the mobile design space is a wide-open frontier, much like space exploration or the Wild West, where people have room to “explore and invent new and more human ways for people to interact with information.”
In the following interview, Hinman talks about the changing landscape of computing — GUIs becoming NUIs — and delves into the future of mobile and how designers and users alike will make the journey.
What is mobile’s biggest strength? What about it is creating a new frontier?
Rachel Hinman: Humans have two legs, making us inherently mobile beings. Yet for the last 50 years, we’ve all settled into a computing landscape that assumes a static context of use. Mobile’s biggest strength is that it maps to this inherent human characteristic to be mobile.
The static, PC computing landscape is known and understood. Mobile is a frontier because there’s still much we don’t understand and much yet to be discovered. There are lots of breakthroughs in mobile yet to come, making it an exciting place for those who can stomach the uncertainty and ambiguity to be. Read more…
Four short links: 9 August 2012
Economics of Innovation, Bio Imagery, Open Source EEG for Smartphone, and Feynman Bio
- Doing Capitalism in the Innovation Economy (Amazon) — soon-to-be-released book by Bill Janeway, of Warburg-Pincus (and the O’Reilly board). People raved about his session at scifoo. I’m bummed I missed it, but I’ll console myself with his book.
- Cell Image Library — a freely accessible, easy-to-search, public repository of reviewed and annotated images, videos, and animations of cells from a variety of organisms, showcasing cell architecture, intracellular functionalities, and both normal and abnormal processes. The purpose of this database is to advance research, education, and training, with the ultimate goal of improving human health. And an excellent source of desktop images.
- Smartphone EEG Scanner — unusually, there’s no Kickstarter project for an iPhone version. (Designs and software are open source)
- Feynman — excellent graphic novel bio of Feynman, covering the science as well as the personality. Easy to read and very enjoyable.