A Framework for Multisensory Intelligent Monitoring and Interpretation of Behaviors through Information Fusion

Abstract

Modern intelligent monitoring and interpretation systems manage several kinds of heterogeneous sensor networks and use outstanding segmentation and tracking algorithms. Monitoring has evolved from initial systems based on low resolution cameras, directly connected to a monitor, up to distributed systems where several sensors cooperate not only to track objects of interest but also to detect suspicious behaviors based on artificial intelligence techniques. In our opinion, frameworks are essential to provide design and implementation patterns for generating a widespread variety of monitoring and interpretation applications, allowing the interaction of different modules and the reuse of code. In this sense, this paper proposes the implementation of a multi sensory monitoring and interpretation framework based on the model-view-controller paradigm but extended to distributed intelligent systems.