An integrated inferencing framework for context sensing

This paper presents the use of distributed inferencing with resource optimisation and Spatio-Temporal Self-Organising Map (STSOM) for effectively combining the wearable and ambient sensors. STSOM is an efficient local processing technique which is also suitable for enhancing the temporal behaviour of the distributed inferencing model. To reduce the complexity of the distributed model, a multi-objective Bayesian framework for feature selection has been proposed for model learning. The validation of the techniques has been conducted with activity recognition with both wearable and ambient sensors in a lab-based home monitoring setting.