Abstract
The success of providing smart healthcare services in ambient assisted living (AAL) largely depends on an effective prediction of situations in the environment. Situation awareness in AAL is to determine the environment smartness by perceiving information related to the surroundings and human behavioral changes. In AAL environment, there are plenty of ways to collect data about its inhabitants, such as through cameras, microphones, and other sensors. The collected data are complicated enough to go for an efficient processing in perceiving the situation. This paper gives an overview of the existing research results in multimodal data analysis in AAL environment to improve the living environment of the seniors, and it attempts to bring efficiency in complex event processing for real-time situational awareness. This paper thus considers multimodal sensing for detection of current situations as well as to predict future situations using decision-tree and association analysis algorithms. To illustrate the proposed approach, we consider elderly activity recognition in the AAL environment.