The environmental context of a mobile device determines where/how it is used, which can be exploited for efficient operation and better usability. In this work we describe a general method using only the lightweight sensors on a smartphone to detect if a device is indoor or outdoor. Using semi-supervised machine learning techniques, our method automatically learns characteristics of new environments and devices, thereby achieves detection accuracy of over 90% even in unfamiliar circumstances. Therefore, it easily outperforms existing indoor-outdoor detection techniques based on static algorithms, or relying on energy hungry and unreliable GPS.
|Title of host publication||The 20th Annual International Conference on Mobile Computing and Networking, MobiCom'14, Maui, HI, USA, September 7-11, 2014|
|Number of pages||4|
|Publication status||Published - 2014|