SatProbe: Low-energy and fast indoor/outdoor detection based on raw GPS processing

Abstract

Indoor-outdoor (IO) detection provides very useful hints for a mobile device to perform context-aware services. To that end, GPS presents a viable solution by relating a device's IO status with its positioning performance, which depends on the device's exposure to the open sky. This approach, however, is prohibitively expensive in terms of energy consumption and response time. Recent work has thus been focused on exploiting low-energy sensors such as light, cellular, and magnetic sensors to infer the IO status indirectly, at the cost of reduced adaptability or explicit user involvement. In this paper, we propose an improving solution to this problem. Our method, called SatProbe, reverts to the GPS approach for its directness and robustness, but avoids its drawback by extracting only the number of visible satellites from the raw GPS data, instead of going through extensive computation to obtain a final position. This metric provides a clear indicator of the IO status, yet can be obtained with great efficiency. Experiments on 79 raw GPS traces with 2595 detection points across a variety of environments show that SatProbe produces higher detection accuracy than previous solutions, with more than an order of magnitude reductions in energy consumption and detection time.