Real-Time Audio Event Detection over a Low-Cost GPU Platform for Surveillance in Remote Elderly Monitoring

Abstract

The average of life expectancy of the population and the prioritization of authorities in active and home aging has increased recently. This has led governments and private organizations to increase efforts in caring the elder and dependant segment of the population. The latest advances in technology and communications point out new ways to monitor those people with special needs at their own home, increasing their quality of life of the elderly or the dependant in a cost-affordable way. This same proposal can improve the quality of caring in retirement homes, giving support to the caring services. The purpose of this paper is to present an Ambient Assisted Living (AAL) able to identify, analyze and detect specific events in the daily life environment—mostly, at home or in a residence—defined by medical and assistant staff that can be considered as an emergency situation. It is designed to be deployed in controlled environments, where social services or medical staff are thought to be nearby. This hybrid network service is intended activate several alarms in the central services when certain situations occur in the monitored place. This tele-care proposal for certain predefined risk situations is validated through a proof of concept that takes benefit of the high performance computing capabilities of a NVIDIA Graphical Processing Unit on an embedded system named Jetson TK1 to be able to process and detect the events locally, even the situations that last in time. This platform holds the basic implementation of the acoustic event detection system, for both in-home or residence-based caring service. The system is nowadays designed to identify eight different situations along time, and set the correspondent alarm when one of the situations is detected.