A new system for assistance and guidance in smart homes based on electrical devices identification

The increasing needs for support services offered to cognitively-impaired people have serious social and economic impact on our societies. Assistive technology is often see as a potential answer to this issue that may help giving more autonomy to these people. This paper presents a new assistive system for smart homes, which is based on the analysis of electrical load signatures at the steady-state, in order to provide supervision and assistance in carrying out activities of daily living for people with cognitive impairment. The proposed system exploits a new algorithmic approach to determine the erroneous behavior related to cognitive deficits and to guide the person through the completion of his ongoing task. We implemented and deployed our system in a real size smart home prototype where we used only a single power analyzer at the main electric panel which is invisible to end-users. Then, a complete experiment has been conducted on this new assistive system using breakfast sequences reproduced with electrical appliances. The simulated sequences included some cognitive errors modeled from real case scenarios coming from previous experiments with Alzheimer patients. The system showed very promising and robust results, both for activity recognition and guidance. It demonstrated that it is possible, using nonintrusive hardware like a simple power analyser, to compete with other assistive systems presented in the literature, which require intrusive equipment to properly monitor and guide.