A Taxonomy of Sensors
In spite of my wariness with QS sensors, a sweet spot for large-scale sensors use is possible with large geographic scale, short temporal cycles, non-personally identifiable, public health, group behavior as shown below.
The regional-scale sensors such as airborne or satellites (I recently gave a talk at Planet Labs; they are doing exhilarating work) will continue to be important, but they are too far away from the humans to provide local detail. Implanted or worn sensors, or even smart-home devices such as Nest, provide great local detail, but are so fraught with privacy issues that getting that data into a single, global pool is possibly a fool's errand unless we change the conversation around privacy and sharing.
"Local" sensors, on the other hand, have a better chance to not just scale, but also change the way we collect data about ourselves and our local environments with high temporal and spatial resolutions. By not collecting individual info, we sidestep the issues of privacy and security. These "local" sensors occupy a sweet spot providing useful local detail without getting tied up in privacy issues. Additionally, we can power them however we want, and we already know their position because they are static, so there is no need for battery-consumptive GPS. They well might be the basis for smart-cities—canopies of PV leaves that generate enough power for local lighting, traffic lights that adjust to traffic volumes reducing idling, pollution monitors that indicate problem spots, drains that phone the PW dept. when they get clogged, cars that sense potholes and phone the roads dept. with location and depth of the hole, parking meters and spaces that signal availability to a parking map app, windows that become darker like sunglasses when the sun is shining really bright, conductive paint that can embed circuits in the wall (yes, there is such a thing), even crowdsourced mapping of stagnant pools of water that are malaria breeding grounds, and so on.