Communication and computation inter-effects in people counting using intelligence partitioning

The rapid development of the Internet of Things is affecting the requirements towards wireless vision sensor networks (WVSN). Future smart camera architectures require battery-operated devices to facilitate deployment for scenarios such as industrial monitoring, environmental monitoring and smart city, consequently imposing constraints on the node energy consumption. This paper provides an analysis of the inter-effects between computation and communication energy for a smart camera node. Based on a people counting scenario, we evaluate the trade-off for the node energy consumption with different processing configurations of the image processing tasks, and several communication technologies. The results indicate that the optimal partition between the smart camera node and remote processing is with background modelling, segmentation, morphology and binary compression implemented in the smart camera, supported by Bluetooth Low Energy (BLE) version 5 technologies. The comparative assessment of these results with other implementation scenarios underlines the energy efficiency of this approach. This work changes pre-conceptions regarding design space exploration in WVSN, motivating further investigation regarding the inclusion of intermediate processing layers between the node and the cloud to interlace low-power configurations of communication and processing architectures.