Meta-Monitoring Using an Adaptive Agent-Based System to Support Dependent People in Place

In this paper, the authors propose software architecture to monitor elderly or dependent people in their own house. Many studies have been done on hardware aspects resulting in operational products, but there is a lack of adaptive algorithms to handle all the data generated by these products due to data being distributed and heterogeneous in a large scale environment. The authors propose a multi-agent classification method to collect and to aggregate data about activity, movements, and physiological information of the monitored people. Data generated at this local level are communicated and adjusted between agents to obtain a set of patterns. This data is dynamic; the system has to store the built patterns and has to create new patterns when new data is available. Therefore, the system is adaptive and can be spread on a large scale. Generated data is used at a local level, for example to raise an alert, but also to evaluate global risks. This paper presents specification choices and the massively multi-agent architecture that was developed; an example with a sample of ten dependant people gives an illustration.