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The risk of falling is designed much more to the aging population. Due to this risk, many researchers have focused their work to the fall detection to improve the daily life of this category of population. The objective of this paper is to propose a multimodal system for fall detection in an Intelligent Habitat. Our system is based on two Ambient Assistance services (Fall Detection service and Location service) and an Emergency service. The ambient assistance services use sensors installed in the home (Photoelectric sensors) and on the persons (accelerometer), to collect information at any time about location and state of the person. The Emergency service result from the fusion of data collected by these services and sends a code number to the doctor. Depending to this code number, he can know the situation of followed person. This multimodal system is modeled by Colored Timed and Stochastic Petri nets (CTSPN) simulated in CPNTools.

Multimodal System for Fall Detection and Location of person in an Intelligent Habitat