A few interesting products are on the horizon, though. A forthcoming “smart” helmet from the sports-gear maker Riddell can send alerts to a coach on the sidelines using a device when one of his football players gets hit in the head with a certain degree of severity. The system can keep track of each player’s hits over time for review on a laptop.

A sensor from startup Brain Sentry can be applied to a helmet and cause an LED to flash red on the helmet whenever there’s it detects sudden acceleration. Reebok and MC10 have come up with the CheckLight skullcap with sensing technology and LEDs for use under a helmet in any sport.

The National Football League has been putting up money for research to better diagnose brain injuries, so devices like these could get beyond amateur use and go pro in the near future.

Big data could be coming to soccer soon, too. A German company has deployed sensors to track player and ball movement on a soccer field in Nuremberg, and data scientists got to work on the data at a Cloudera event in February. The winners, from Pythian, used Cloudera Impala to make a neat heat map showing where players and the ball were on the field during the game.

Source: Flickr user markusunger

Quantifying the slam dunk

Look to basketball and baseball for a couple of other applications in sensors that aren’t so far off. Think of a slam dunk, and then think about seeing just how hard a basketball player is slamming the ball through the hoop. Researchers at MIT removed the nylon core from a basketball net, dropped conductive silicone with sensors in its place and came up with a way to measure force, quantify it on a connected circuit board and transmit it to a computer. Working with TNT, the researchers deployed the Slam Force Net system at the 2012 All-Star Game’s slam-dunk contest, said Michael Bove, a professor at the MIT Media Lab. Readings were displayed on for everyone watching the contest on television.

Source: Flickr user terren in Virginia

The system doesn’t generate a ton of data, and it costs within the “tens of dollars” to build, Bove said. But that’s not the problem in getting the system to be used.

“The business model is more, ‘Does it make sense to show it (the data on screen)?’ And, if you’re going to show it, how graphically sophisticated do you want it to be?” Bove said.

But that’s not the only possible application of the sensor-laden net. It could also stop the clock when the ball goes through the net. The system would be more reliable than controlling the clock by hand, Bove said.

The connected baseball

Meanwhile, he can see the same material deployed in a net for training pitchers to throw at a certain speed inside a strike zone. “It would be tens of dollars, and it wouldn’t require the amount of setup you would need with a radar gun,” Bove said.

Source: Flickr user lmbaker3

The curveball of monetization

The common theme here is that we’re still in the early innings for commercializing professional uses of sensors in sports. Researchers at the CambridgeSens group at the University of Cambridge, the Centre for Pervasive Sensing at Imperial College in London and many other academic institutions are experimenting with materials, transmitters and data-analysis methods. Surely athletes will end up using some of this technology. The bottleneck at the moment seems to be the creation of systems that can deliver value to players, teams, leagues and fans on an ongoing basis.

A good example comes from the world of running. Research into sensor-rich insoles focused on clocking how long shoes touched the ground during a sprint. That data could be processed right after a run and displayed to runners, so they can adjust their performance based on muscle memory.

“The big decision is what sort of information you want to give to people and what sort of processing algorithms you would use to do this in real time,” said one of the researchers, Marcelo Pias. “That’s what we spent quite a lot of time developing.”

But the technology might be years away from commercialization. Pias’ group did market research and came to the conclusion that it would address “a niche market — very, very small compared to what you would achieve with something like Fitbit,” said Pias, who is now running Globosense, a startup focusing on the connected home.

Dealing with data

The dearth of sensible go-to-market strategies right now might be all right, because IT executives are still scrambling to figure out what to do as more data sets become available for analysis. The topic will certainly be up for discussion when my colleague Barb Darrow talks with the CIOs of the Pabst Brewing Co. and the Clorox Co. at GigaOM’s Structure conference in San Francisco on June 19.

So as companies and organizations go forward with new ways to compute and store increasing amounts of data, entrepreneurs have some time to pencil out business models that could make money off sensor technology that many people in sports would be willing to pay for.

Until that happens, good old processed film will remain a viable option for analyzing player performance. There’s nothing wrong with that, but it sure would be nice to go a few steps further.

Feature image courtesy of Flickr user khawkins04.

Disclosure: Fitbit is backed by True Ventures, a venture capital firm that is an investor in the parent company of this blog, Giga Omni Media. Om Malik, founder of Giga Omni Media, is also a venture partner at True.

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The startups are focusing on all kinds of issues – from using big data to accelerate cancer care to creating an online community for patients and caregivers to using sensors to lower stress and boost productivity.  But a few of the companies have already attracted a bit of attention.

Augmedix, for example, is building a service for doctors powered by the ever-buzzy Google Glass. The company, which is led by a former employee of sensor company MC10, has only said that it’s creating an app for medical doctors. But it’s already raised $55,000 in seed funding on Upstart, including from SoftTech venture capitalist Jeff Clavier.

Another startup worth watching is Smart Patients, founded by Google’s former Chief Health Strategist Roni Zeiger. The startup, which we covered back in April when it launched at TEDMED, is creating an online community for cancer patients and caregivers that incorporates social networking and search technology.

Given booming interest in sensor technology, it’s also little surprise that Rock Health tapped wearable sensor startup Spire to be a part of its newest class. A recent graduate from StartX, the accelerator for startups founded by Stanford students, Spire tracks breathing patterns as an indicator of stress.

In addition to revealing the members of its newest class, Rock Health said that its roster of corporate supporters had grown with partnerships with life sciences real estate and venture firm Alexandria Real Estate Equities, pharmaceutical company Boehringer Ingelheim, and Ogilvy Public Relations. The accelerator also said that later this year it will move out of its digs in San Francisco’s Chinatown to a new space closer to UCSF’s new Center for Digital Health Innovation and SoMa.

Here’s a full list of the startups in the accelerator’s new class:

Amplify Health – As the health care system shifts from “fee for service” to “fee for value,” Amplify Health wants to offer physicians software for managing their patient populations and improving outcomes.

Anapsis – The young (or very stealthy startup) doesn’t appear to have a website up but Rock Health says it’s building a “research platform and marketplace for scientific and statistical computing.”

Augmedix – Augmedix is one of the first startups creating a Google Glass-powered application for medical doctors.

CancerIQ – With a goal of bringing better intelligence and big data to cancer care, CancerIQ is a web-based application that helps researchers and physicians access and understand a wide range of relevant data.

CRIXlabs – Using predictive software, the startup aims to help pharmaceutical companies in their research process to develop safer and more effective drugs.

Fluid – The startup enables patients to diagnose themselves with the flu in minutes, without taking a trip to the doctor.

Lift Labs – For people with Parkinson’s disease or other conditions that cause tremor, Lift Labs is developing a range of tools, including a spoon that makes eating more comfortable.

Sensentia – The company is developing tools for healthcare administration and operations, including a product that enables health insurers to more efficiently handle the volume of real-time inquiries from care providers.

Smart Patients – Launched in April, Smart Patients is creating an online community for cancer patients and caregivers.  

Spire – The wearable sensor tracks breathing patterns to help people monitor and control stress.

ThriveOn – A mental health-focused startup, ThriveOn offers customized care programs for individuals.

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Some day our bodies — or at least the clothing or accessories that adorn them — could become key network nodes in the internet of things. European researchers think that sensors and transmitters on our bodies can be used to form cooperative ad hoc networks that could be used for group indoor navigation, crowd-motion capture, health monitoring on a massive scale and especially collaborative communications. Last week, French institute CEA-Leti and three French universities have launched the Cormoran project, which aims to explore the use of such cooperative interpersonal networks.

The concept of wireless body area networks (WBANs) isn’t a new one. WBANs could be used to sever the cord between patients and their monitoring equipment. Companies like Apple and Heapslylon are exploring the possibility of connected clothes with embedded sensors. We’ve already begun embracing a new era of wearables, such as Google Glass to Fitbit (see disclosure), designed to become extensions of our senses and movements.

All of these devices will become key end-points in the internet of things, but what Cormoran proposes to make them pull double duty. Rather than just remain terminuses, they could route bits to and relay data from each other, becoming a distributed ad hoc network that constantly morphs as we move through physical space.

Better living through distributed networking

Why would you want this kind of network? For one, there is an inherent inefficiency in the point-to-multipoint transmissions that dominate mobile data communications today. Wearable tech usually connects via Bluetooth to a smartphone, which then transmits its info to some distant cell tower. Many medical and connected home devices use proprietary technologies requiring their own dedicated wireless gateways.

Assuming your device can even get a connection to the internet, it’s often using an expensive, power-hungry and highly suboptimal means to transmit tiny specs of data. A distributed wireless network, however, could aggregate data from hundreds if not thousands of nearby devices and then find the most efficient link to offload that collective data to the internet at large. This kind of collaboration is the same principle proposed by mesh-networking outfits Open Garden and the Open Technology Institute as a means of optimizing wireless systems – if everyone shares their connections and relays each others’ data, then everyone benefits.

But there’s an additional benefit to this kind of collaborative communication: by linking to one another, body area networks could create new useful data about users’ surroundings and location. By measuring the signal strength of nearby connections, the network could determine the precise location of every node, or person, within it.

You can imagine some of the possible applications for such technology. In a busy airport or train station, proximal location-based services could route departing passengers en masse to their proper gates or trains or arriving passengers to the proper baggage claim. City planners could use the technology to track and manage the flow of pedestrian traffic, and emergency agencies could use it to coordinate the evacuation of a building. Sociologists could use it to study group behavior, and game designers and movie CGI could use it to digital map crowd movement.

The big “what if?”

On the flip side, though, creating such collaborative networks has ominous security implications. Our own notions of individual privacy suffer if we know every transmitter in a hundred-foot radius is talking to our devices and even helping to carry our personal data back to the cloud.

There are a lot of similarities between collaborative body area networks and the vehicle-to-vehicle connected car technologies pursued by the automotive. If all cars on the highway could talk to one another, they could coordinate their activities, preventing accidents and getting drivers to their destinations faster. But the danger is that these networks would get hacked. Personal information about a car’s driver could get in malicious hands, or data intended to prevent accidents could be falsified to actually cause them.

It’s an exiting project, but Cormoran is going to have deal with similar questions. It will have to not only create the protocols that will allow our body area networks to coordinate, but ensure that the data they relay remains secure and most of the information they share remains anonymous.

Disclosure: Fitbit is backed by True Ventures, a venture capital firm that is an investor in the parent company of this blog, Giga Omni Media. Om Malik, founder of Giga Omni Media, is also a venture partner at True.

Networking diagram courtesy of Cormoran. Privacy image courtesy of Shutterstock user Johan Swanepoel.

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Yet that’s exactly what a group of researchers at the University of Illinois have created — a cradle that wraps around an iPhone and turns it into a biosensor that can detect, according to a university press release, “toxins, proteins, bacteria, viruses and other molecules.” Inside that cradle are about $200 worth of mirrors, lenses and a photonic crystal that the researchers claim can identify these substances as accurately as a $50,000 spectrophotometer in the lab.

The cradle is essentially there for support, though, while the phone’s camera and processor do the real work. With everything firmly aligned in front of the camera, a scientist would simply snaps a photo and the CPU processes the result. What it’s processing is the difference in wavelength that the photonic crystal, primed to react to a specific molecule, reflects. The team demonstrates the device and app in the video embedded below.

And if you’re into this type of mobile data collection, another group of University of Illinois researchers actually created a smartphone-powered water-pollution device called MoboSens

Like all things mobile or sensor, though — from SkinScan (now SkinVision) to health care apps like Ginger.io — the biggest value might come from data that has nothing to do with what the app is primarily measuring. Rather, when data about a certain condition, air quality or what have you is tagged with time and geodata, for example, it becomes the basis for mapping how situations are spreading or where there might be safe haven.

Imagine a team of scientists with iPhones dispersed throughout a city after a disaster, painting a real-time picture of what areas are most affected by a particular toxin (or maybe radiation). Taking a longer term approach, researchers could track how situations are evolving over time. Throw in even more data that smartphones are capable of detecting — temperature, ambient noise, vibration, etc. — and we might unlock entirely new ways to think about how diseases spread through the air or what conditions tend to favor the spread of foodborne bacteria.

In some ways, though, this is more than another cool thing you can do with a smartphone. It’s the furtherance of something we’ll discussing in depth at our Structure conference next month, which is how we rethink IT when computation and data are no longer bound within a single server or even the corporate network somewhere. The biological data this app will collect isn’t much use locked inside the phone; it needs a way to reliably and securely connect with other datasets and other services, likely distributed across the country or even the world. That’s where the real opportunity lies.

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The news of the new EU industrial strategy came just a couple of days after the Geneva-headquartered, French-Italian manufacturer STMicroelectronics launched its own three-year project, worth €360 million ($463 million), aimed at creating a European microelectronics design ecosystem based around its fully-depleted silicon-on-insulator (FD-SOI) manufacturing process.

Some in the industry, such as chipmaker GlobalFoundries, have previously urged European authorities to back electronics manufacturing on the continent in order to counteract the vast influence of Asia and (to a lesser extent) the U.S. in this field.

Cheaper, faster, smarter

The European Commission’s strategy, announced on Thursday, is intended to make chips cheaper, faster and smarter. It will concentrate on shoring up three existing electronics clusters, namely those in Dresden (Germany), Eindhoven (Netherlands) and Leuven (Belgium), and Grenoble (France). Connections will also be made with other clusters such as that in Cambridge (UK), which is big in the wireless sector.

“I want to double our chip production to around 20 percent of global production,” Digital Agenda Commissioner Neelie Kroes said in a statement. “I want Europe to produce more chips in Europe than the United States produces domestically. It’s a realistic goal if we channel our investments properly.”

As per usual, this isn’t a simple public cash splurge. €5 billion in public funds – 30 percent from the EU with the rest coming from national and regional funds – will go to R&D, in order to help stimulate the sector. Overall, the Commission says, industry has indicated it will stump up €100 billion over the seven years: €15 billion in capital expenditure and €85 billion in operational costs.

The kind of electronics we’re talking about could be used in desktop and handheld computers, but the main thrust is for embedded systems and “internet of things” devices, from sensors and smart grids to new healthcare technologies. As Kroes said in a speech, “this isn’t about computers.”

Targeting these areas plays to Europe’s strengths. According to the Commission, Europe already pumps out half of global automotive electronics, 40 percent of electronics used in energy applications, and 35 percent of those used for industrial automation – this will be a reference to the output of companies such as Bosch, which are hugely active despite often being somewhat under-the-radar. Then we also have smaller manufacturers working in high-growth niches, such as health implants and sensors.

And jobs?

The purpose of all this is to make Europe less reliant on manufacturers outside the continent, but job creation is also a major factor. The Commission reckons the European electronics industry already employs 200,000 people directly and supports a further million jobs indirectly.

That said, the Commission also pointed out in its statement that demand for skilled workers in these fields is higher than supply – if this whole strategy is to work, the implication runs, Europe will need to attract more skilled workers. The statement talks of coordinating public efforts across Europe. Perhaps that will mean tweaking immigration rules: something the U.S. tech sector is also heavily vocal about these days.

Meanwhile, STMicro’s push – called, incredibly, “Pilot Lines for Advanced CMOS Enhanced by SOI in 2x nodes, Built in Europe” (Places2Be) – also takes place in the context of a wider European project, the nanoelectronics-focused ENIAC. In a briefing note accompanying Thursday’s announcement, the Commission insisted that ENIAC and ARTEMIS (another project focusing on embedded computing) had been a success, and that the new drive did not denote failure of those two schemes.

The Commission said the new joint undertaking would build on “lessons learnt” from ENIAC and ARTEMIS while providing a “simplified funding structure”.

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That first RE.WORK summit will take place on 19 September, which is also the second day of GigaOM’s Structure:Europe conference in London. The RE.WORK program will kick off with a focus on the areas of: the internet of things, 3D printing, nanotech, artificial intelligence, robotics, computing systems and sensors.

“We’re trying to showcase emerging technologies and breakthrough ideas,” summit founder Nikita Johnson told me. “It’s all about reworking big challenges that we’re facing in the future. We want to bring the technology and science aspect, but with mission of positive impact.”

While the first of these summits will focus on technology, others will have different themes: one in December will deal with urbanization, RE.WORK Health will take place next year, and still others will handle energy, education and the environment. The first three meetings will take place in London, with others set for Dublin, Berlin and other European cities. Events will also be followed up with smaller meet-ups, Johnson added.

Apart from Solve For X, other initiatives in this space include TED, to a certain extent (RE.WORK looks to be a bit more collaborative and interactive) and the engineering-led Global Grand Challenges Summit.

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According to a Monday blog post from Michael Manoochehri, a Google developer program engineer, Google will take the data coming in from the Arduino boards and visualize it all in real time with Google Cloud Platform services such as Google Compute Engine and BigQuery. And it’s no teensy-weensy data set:

“Altogether, the sensors network will provide over 4,000 continuous data streams over a ZigBee mesh network managed by Device Cloud by Etherios.”

The visualizations will be on display on screens during the conference. And Google said it will make the Cloud Platform code and the resulting data available in open source.

O’Reilly Media has used Arduinos at events for similar purposes before, as I reported in February. How are the deployments different? For one thing, Google uses the Google cloud — surprise, surprise — while O’Reilly has used Amazon Web Services. The question is whether the project will persuade non-Google developers to try using the Google Cloud Platform for their own programs to crunch data generated by sensors.

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“I like the word autopilot more than I like the word self-driving,” Musk said in the interview. “Self-driving sounds like it’s going to do something you don’t want it to do. Autopilot is a good thing to have in planes, and we should have it in cars.”

Musk told Bloomberg that he’s discussed the autopilot concept with Google’s engineers and even mentioned the possibility of Tesla and Google jointly developing such a system. But Musk later tweeted from his Twitter account that his comments to Bloomberg were meant to be off the cuff, and that Tesla and Google weren’t announcing any big new initiative.

“Creating an autopilot for cars at Tesla is an important, but not yet top priority,” Musk tweeted. “Still a few years from production.”

Musk’s notion of an inexpensive autonomous driving system is an interesting one as it does away with the complex light detection and ranging — or Lidar — sensors that use 360-degree scanning lasers to render a 3D construct of the world around the vehicle. You’ve seen such funky laser arrays on top of mapping vehicles before, so the technology is readily available, but even a scaled down version of such systems would add enormous cost to car. According to Ford engineers, those costs are among the principal reasons why fully autonomous cars are still many years away from becoming reality.

But Musk posited that a car could simply use cameras to collect the data the car needs from its surroundings. The approach has its limitations compared to lasers. Cameras take pictures, while Lidar is registering physical objects, tracking their distance and relative speed to your car. Cameras would extrapolate that data from images. Stereoscopic lenses could allow for better depth perception on the road, but ultimately a camera-based system would depend on a lot of image-processing muscle to cull critical life-saving information from a massive pool of pixels.

Luckily for Musk, he’s not the only one thinking this way. Many of the new advanced driver assistance systems (ADAS) systems that warn drivers of impending accidents or alert them to lane drifting are camera based. It’s also no coincidence that graphics card giant Nvidia is making a big play in the connected car space. The silicon vendor believes that its years of crunching real-time image and spatial data in PCs and game consoles make it the ideal company to power future car sensor systems.

Eventually cars won’t just sense the other vehicles and objects in their vicinity. Those vehicles will actively communicate with one another and those objects. Using a secure form of long-range Wi-Fi, a car will tell all the vehicles behind its about brake or change lanes. Transmitters on the highway will tell you a big curve is coming up. (For more info on the connected car see our infographic.)

Such vehicle-to-vehicle and vehicle-to-infrastructure communications could never replace sensors entirely since it would take decades for every vehicle on the road and every stretch of asphalt to become connected. But those technologies would allow cars to evolve cars beyond autonomy into a kind of ad hoc network, in which they would collectively make decisions instead of merely reacting to each other’s actions.

Returning to Musk’s remarks, though, I find it particularly interesting how he’s positioning the concept of the driverless car. He’s calling it a form of autopilot not too far off from the adaptive cruise control we use in our vehicles. Musk is downplaying the idea of car usurping control from the driver. He’s keyed in on the biggest obstacle facing the autonomous vehicle today: consumer perception. Few people are ready to cede act of driving to computer.

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That the bees, which are described as being half the size of a paperclip and weighing less than a tenth of a gram, can fly at all is an engineering marvel in its own right given their minute size. However, the next parts of the project could actually prove to be even bigger challenges.

According to a Harvard University press release:

[T]he next steps will involve integrating the parallel work of many different research teams that are working on the brain, the colony coordination behavior, the power source, and so on, until the robotic insects are fully autonomous and wireless.

Source: Kevin Ma and Pakpong Chirarattananon, Harvard University.

The problems are that building AI-powered brains won’t be easy and that there’s not yet an energy source small enough and dense enough to power a wireless bee.

On the brain side, though, the RoboBees team might have some help. As we explained in October, there’s a team from the Universities of Sussex and Sheffield in the U.K. working on a project called Green Brain that aims to develop a brain that could let robotic bees like those RoboBees is building act autonomously and respond to sensory stimuli.

Again, though, the small scale of the Harvard project could pose some initial challenges depending on how advanced it wants the brain to be. The plan is for the Green Brain project to run on a GPU-powered supercomputer and, presumably, communicate with sensors on the robot. Even if it were possible for a single GPU processor to run the Green Brain at operational speed, that could still prove too big for the tiny RoboBees, which need to do their own processing.

The key to success, however, might lie in RoboBees’ focus on colony behavior, which is somewhat akin to the concepts underlying distributed computing systems. Because the team expects the robotic bees to function like real honeybee colonies, individual bees can get by with less computer power.

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Overall, health technology startups received $120 million from investors in March, a 12 percent increase from the same period last year. Deal volume nearly tripled, from 13 deals last March to 36 this year.

Here’s an at-a-glance look at activity last month:

• Although practice management was the dominant sector by funding amount last month (largely because of One Medical Group’s Series F round), sensor technology was a bigger winner in terms of deal volume.  In addition to the nearly $12 million raised by health-tracking wristwatch startup Basis, companies including Rock Health-backed Podimetrics, which makes an intelligent floor mat for helping diabetic patients detect foot ulcers, and Sensiotec, which develops technology that monitors heart and respiration rates without any direct patient contact, added new funding.
• Personalized medicine got a boost last month. Five startups – from those that speed up the analysis of DNA sequence data to those that give chronic disease patients in-depth reports and analysis on their personal condition – raised funding, including Spiral Genetics, Bina Technologies and MetaMed.
• Last month, Nike announced the 10 companies participating in the first class of its TechStars-powered accelerator for fitness-related startups. This points to a growing trend of strategic investors attempting to drive innovation around specific themes. Earlier this year, GE announced a partnership with Startup Health to invest in consumer health startups. “I think we’re going to start to see strategic partners do more of these types of programs in the future,” said Unity Stoakes, president of Startup Health.

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