Implementation of Wireless Vision Sensor Node With a Lightweight Bi-Level Video Coding

Abstract

Wireless vision sensor networks (WVSNs) consist of a number of wireless vision sensor nodes (VSNs) which have limited resources i.e., energy, memory, processing, and wireless bandwidth. The processing and communication energy requirements of individual VSN have been a challenge because of limited energy availability. To meet this challenge, we have proposed and implemented a programmable and energy efficient VSN architecture which has lower energy requirements and has a reduced design complexity. In the proposed system, vision tasks are partitioned between the hardware implemented VSN and a server. The initial data dominated tasks are implemented on the VSN while the control dominated complex tasks are processed on a server. This strategy will reduce both the processing energy consumption and the design complexity. The communication energy consumption is reduced by implementing a lightweight bi-level video coding on the VSN. The energy consumption is measured on real hardware for different applications and proposed VSN is compared against published systems. The results show that, depending on the application, the energy consumption can be reduced by a factor of approximately 1.5 up to 376 as compared to VSN without the bi-level video coding. The proposed VSN offers energy efficient, generic architecture with smaller design complexity on hardware reconfigurable platform and offers easy adaptation for a number of applications as compared to published systems.