How do participatory sensors work?

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>> It's about allowing everyday people to not just provide data to important things such as traffic and mall traffic and such but also to offer their own data campaigns for issues that are important to them and to their community. And as we've been hearing all afternoon smartphones and web services really provide that phenomenally scalable make a case technology and they do this both through explicitly captured information as well as automatically captured information and let me just give you an example of both of these because examples clearly help. So my favorite example today is an application we built with The National Parks Service and it's called Whatsinvasive.com, it's live and it's basically an application where the Park Service employees and visitors can download an app to their iPhone or their Android phone and they can use it to tag the location of invasive plant species that are threatening the native ecosystem, particularly an interest in contacts of climate change and these other destabilizing factors. So you can participate in whatsinvasive.com by providing data for your favorite wilderness area on your next hike. You can also participate in it by uploading the top 10 most wanted weeds for your neighborhood wilderness area that might not yet be represented with a site but you can also use the same system to document some spatial temporal phenomenon that's of importance to you and your community. So the general technology of participatory sensing is really a story of mobile to web and making it very easy to create your own data campaigns as well as to contribute to other peoples. And so as Diane described and as we heard from Nokia you can also use your smartphone not just for tagging and geo coding and uploading images but to automatically capture data from the other centers on the phone such as location and motion but you don't you can use that information for yourself as well as for contributing to an aggregator service or you can just use it for yourself. So again examples help biketastic is a little example that we've launched and it's a tool for cycle commuters to create and share information about bicycle commuting and when they do that it's not just as you would in a web interface you would go up and draw your start and stop and show the route that you take this is automatically captured information. It's an app you start. You place it in your pouch or on your bike. The information from the GPS and accelerometer is captured activity classified and uploaded and displayed on a map and there you get duration of the ride at start and stop and such but you also get things like how long you spent at noisy, polluted, dangerous traffic intersections by definition because you get to see how smooth is your ride versus how much time you're spending stopped with 0 acceleration versus otherwise. So it's an example of a way in which the same technology that is contributing to wayziz assumed spelling maps and they're very important information sources can contribute to the information that you want to create for your community. And so just to then finish these traces are a very powerful tool for both personal and community behavior change and sort of like that Prius dashboard that we all refer to as a model for providing real time feedback to create behavior change to be able to see your measured behavior and so we can use our location traces like the ones that the cycle commuters are using. We can use our own location traces to understand the implications of where we spend our time and what we spend our time doing. So what is the aggregate air pollution I'm exposed to on days when I can commute during heavy traffic hour versus when I commute at off hours or thinking about personal health applications using these same kinds of traces to look for feedback when I'm trying to do some kind of drug titration or other kind of care plan adaptation. So these personal applications built off of our personal traces are a form of participatory sensing where participating is sensors in the capture the data and we're participating as users of that sensing data. And this is really a common framework that's going to support everything from the invasive plant species to your personal health management. And one of the nice things about a lot of these applications is that they scale down not only up so you don't need to have high market share or high penetration to gain the benefit of these applications you just have to have value to the individual who's collecting their data and using it to understand something about themselves or about their environment.

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