Battery-Aware Mobile Solution for Online Activity Recognition from Users' Movements

One of the unique features of mobile applications is location awareness. Mobile users take their devices with them everywhere which increases the availability of persons' traces. Extracting and analyzing knowledge from these traces represent a strong support for several application domains, ranging from traffic management to advertisement and social studies. We present a novel approach to online recognition of users' outdoor activities without depleting mobile resources. We associate the places visited by individuals during their movements to meaningful human activities using a novel algorithm that incrementally clusters a user's moves into different types of activities. To optimize battery consumption, the algorithm behaves variably according to users' behaviours and the remaining battery level. Studies using real GPS records from a spatio-temporal region demonstrate that the proposal is effective and is capable of inferring human activities without draining the phone resources.