Structuring reasoning for interpretation of sensor data in home-based health and well-being monitoring applications

This paper presents an approach to structuring knowledge and reasoning for high-level interpretation of sensor data in e.g. independent living applications. The main contribution is to use generalized events, described in terms of 'space-time chunks', as a unifying and simplifying structuring principle. We use reasoning with ontologies and rules in combination with a database system, and also incorporate numerical computation. We show that an easy to use modeling formalism is obtained, and that reasoning is feasible at the time of service request, by using R-entailment, which enables efficient exploitation of ontologies and rules in the presence of RDF data. Two applications were built and evaluated using the approach described in this paper, both of which are related to monitoring well-being of elderly people, and both of which use simple, low-cost sensors.