Surveillance Rover Based on Real Time Object Recognition


  • Ashish Daga,


Surveillance. Raspberry Pi 3 B , YOLO.V3, deep learning, Raspbian OS.


In the past few years there have been plenty of technical advancements in surveillance, by the introduction of types of closed loop cameras. These have assisted in solving crime scenes and yet, the rate has not reduced due to the immovability of the surveillance equipment. In any hostage situations security cameras are the first to be targeted by the outlaws to protect their identity. therefore, the need for the development of mobile surveillance equipment is high. Residential areas, government organizations, commercial spaces, schools and hospitals, industries, banking and other challenging indoor and outdoor environments require surveillance systems. This project proposes a rover which can be controlled through the internet and can be used for surveillance applications. Raspberry Pi 3 B+ is used as the brain of the system and the module is also capable of performing Object Recognition using the YOLO.V3 algorithm which is based on deep learning. The rover can be controlled through an android application which communicates with the Raspberry Pi on the Rover and gets the job done. VNC viewer is used to have an access to the Raspbian OS of Raspberry Pi to make changes in its functioning.




How to Cite

Ashish Daga,. (2021). Surveillance Rover Based on Real Time Object Recognition. Journal of Research Proceedings, 1(2), 113–122. Retrieved from