Tiered approach to infer the behaviour of low entropy mobile people

Being able to understand human behaviour and monitoring daily life activities is seen as a significant approach for alleviating functional decline among elderly people. The aim of the research work presented in this paper is to investigate a mechanism that can recognise high level activities and behaviour of low entropy people in order to help them improve their health related daily life activities by using wireless proximity data (e.g. Bluetooth, Wi-Fi). A number of scenarios and experiments are designed to prove the validity of the proposed methodology. Using wireless proximity data for activity recognition enhances the intrusion into personal privacy and helps exploiting important structures in human behaviour.