Fall Detection and Intervention based on Wireless Sensor Network Technologies

The present paper details the development of a cost-effective Fall-Detection and -Intervention System (FaDIS) based on Wireless Sensor Network technologies. The system is designed to integrate into existing low-tech homes, to enable Ambient Assisted Living environments, where software and hardware devices attempt to facilitate a safe and proactive independent living. FaDIS is designed to operate both as an add-on component to existing centralized solutions (complete or otherwise) and as an integral yet independent component of decentralized, scalable, and expandable solutions. Accordingly, FaDIS was implemented in two parts. Part 1 was developed as a scaled proof-of-concept that served as the foundation for Part 2, which is the principal focus of the paper. In Part 2, FaDIS is developed as a fully operational, real-scale system that uses a self-healing mesh network protocol, where its own BeagleBone Black development platform serves as the sink node, and where two Class 2M 10° line lasers are used in conjunction with light dependent resistors to gauge the probabilities of an emergency event based on the estimated dimensions of the collapsed object. In both parts, if FaDIS construes the probabilities of an emergency event as high, the same series of corresponding robotic response-actions intervene locally while automated notifications are sent to emergency-personnel, care-takers, and/or family members via both wireless and cellular technologies. A series of sample runs are detailed and described in the present work in order to demonstrate and to argue for the feasibility and functionality of FaDIS as both a Fall-Detection and -Intervention System in particular and as a WSN-based system in general.