A data fusion model for ambient assisted living

Abstract

Ambient Assisted Living (AAL) is an emergent area that provides useful mechanisms that allows tracking elders through sensoring. For AAL systems, it is very important to provide information fusion techniques, which merge the information available in sensors available in different devices like the smartphones to infer possible risk situations for elders in outdoor environments. The Data Fusion Model is the most widely used method for categorizing data fusion-related functions. In previous works we have developed SafeRoute, an AAL system that pretends monitoring elders in their day-to-day daily living activities in outdoor environments. In this context, this paper presents a specific proposal of application of the JDL Data Fusion Model to tracking old persons in outdoor environments. We additionally present the social interaction model in the context of the SafeRoute system, showing the interactions between caregivers and elders and including new contextual elements to make more efficient the tracking process.