Human Behaviour Detection Using GSM Location Patterns and Bluetooth Proximity Data
Human behaviours are multifarious in nature and it is a challenging task to predict and learn from daily life activities. The profusion of Bluetooth enabled devices used in daily life has created new ways to analyze and model the behaviour of individuals. Bluetooth integrated into mobile handsets can be used as an efficient short range sensor. The aim of this paper is the detection of unusual human behaviours from cell tower and Bluetooth proximity data using neural networks. The primary purpose is to find anomalies in individual's daily life routines that will further help one to detect and predict unusual behaviour of elderly people and patients such as dementia patients.