A WSN and vision based energy efficient and smart surveillance system using computer vision and ai at edge

Abstract

The current traditional surveillance systems frequently fall short in delivering satisfactory quality of service, leading to frustrated user experiences. Consequently, there is a growing demand for more efficient and intelligent surveillance solutions. This paper addresses this need by introducing a wireless sensor networking (WSN) and vision based approach that employs optical verification through computer vision and AI at the edge, specifically designed for resource constrained IoT nodes. To support the feasibility and effectiveness of the proposed system, the authors conducted experimental analyses using both simulation and a case study. The results of the study demonstrate that the suggested surveillance system is energy conservative and provides real time information, offering a promising solution to the limitations of traditional surveillance setups.