Energy efficiency for wireless smart camera networks is one of the major efforts in the distributed monitoring and surveillance community. If video cameras are equipped with circuits that receive and convert energy from regenerative sources such as solar cells, an effective power management becomes essential for the design of small sized and perpetually powered devices, which can be deployed unattended for years and feature smart vision applications. In this paper we present a simple but optimal power management tailored for multi-modal video sensor nodes and based on model predictive controller (MPC) principles. The system is designed for low-power and low-cost video surveillance and exploits small solar cells for battery recharging and Pyroelectric InfraRed (PIR) sensors to provide low-power monitoring when the camera is not needed. The aim of this work is to show how an adaptive controller helps the system to improve its performance while outperforming naive power management policies. Simulation results and measurements on the video sensor node demonstrate the efficiency of our approach.
['Michele Magno', 'Davide Brunelli', 'Lothar Thiele', 'Luca Benini']
Adaptive power control for solar harvesting multimodal wireless smart camera