Abstract-This paper presents a novel structure learning algorithm for the creation of distributed Bayesian networks over static and mobile Vision Sensor Network (VSN) nodes. These compose an assistive, intelligent environment for activity recognition. We provide results demonstrating a higher level of accuracy in the recognition of fine motor tasks when the environment is augmented with a mobile robot and show the ability of our learning algorithm to reduce VSN communication compared to a naïve, greedy structure learning technique. I. INTRODUCTION UE to recent advances in medical care and the adoption of increasingly healthy lifestyles, we are witnessing a demographic shift towards an increasingly aged population Where environments are to contain multiple ambient sensors, installation may be performed by a visiting carer or those living within the domicile. Consequently, it is unreasonable to expect these to be located at optimal locations for the determination of individual activities. Furthermore, since each dwelling is unique, their relative positioning can not be assumed prior to installation thus there is a strong requirement for such networks to be self configuring. To this end, we provide a structure learning algorithm for Bayesian networks which is considerate of both inference and communication cost within ambient Vision Sensor Networks (VSNs). Using Pearl's message propagation algorithm, activity inference can be implemented in a distributed manner over the VSNs, without the requirement for a centralized data repository. Where assistive robots are present, our algorithm can seamlessly incorporate such data to augment recognition accuracy. We demonstrate the efficacy of this algorithm in a home healthcare scenario for fine motor tasks occurring at several locations within the environment. II. RELATED RESEARCH For detecting Activities of Daily Living (ADLs), omnidirectional cameras [6] have previously been employed to capture behavioral patterns in a household environment. For example, a system operating at multiple resolutions has been defined, with a wide angle camera directing the pan, tilt and zoom of other camera
