>>SlowRo+(OP)
When you move through any environment, it leaves a discernible trace in a (to most people) surprisingly large swath of sensor platforms that exist solely for boring industrial purposes like building management, measuring the operating environment of equipment to improve efficiency, etc, never mind systems actually designed to indirectly capture people (like cameras). Your existence perturbs the environment and leaves a faint footprint in the data. As a trivial example, transient proximity of people creates small fluctuations in measured temperatures. There are analytical techniques that reliably and systematically isolate and amplify those traces so that you can fingerprint and track a person using them. The typical urbanized environment is
littered with these sensors and it has been repeatedly demonstrated that the measurements coming off these sensors can be used to constructively identify specific individuals in the environment.
I think the gap for most people is not the existence of these sensors, which capture nothing about a person in any kind of direct way, or that people perturb their environment in some abstract way, but the existence of analytic techniques that allow someone to reconstruct detailed personal information from large collections of extremely oblique measurements of the broader environment.
The analytic methods for doing this type of reconstruction are quite clever and non-obvious, which I guess would need to be the case for it to be surprising. It is nothing at all like typical web or enterprise analytics -- you are using measured physics and constraints on that physics to infer environmental dynamics that you can't measure directly.