Wireless Visual Sensor Network Platform for Indoor Localization and Tracking of a Patient for Rehabilitation Task

Wireless visual sensor networks (WVSNs) are commonly using information technologies of modern networking and computing platforms. Today, visual network computing applications are faced with high demand of powerful network functionalities and performances. This paper proposes the specific WVSN nodes that are able to sense surrounding signals coming from the patient in the rehabilitation room and perform as local computations wirelessly communicated within the considered WVSNs. Assuming the WVSN platform for the rehabilitation supervision of patients, this paper discusses the specifications of the concept and the development of the WVSN nodes relying on KINECT and Raspberry Pi 3 (RPi 3) boards. Several technologies, such as RPi 3, Kinect, and ID sensor, are utilized in the proposed platform to realize sensors, image-capturing units, and processing cores. This collaborative platform consists of three nodes that are designed in three processing cores using the entire workflow to support the development steps. The communication of the elements between one to another and between the components takes place via Wi-Fi. The implementation of a preprocessing stage for component integration and the development of software development kit tools are necessary. In its final part, this paper summarizes the outlines of the proposed platform in different scenarios which run on nodes and also provides evaluation results that prove the feasibility of the approach.