DESIGN OF AN AUTONOMOUS ROBOT SECURITY SYSTEM USING NEURAL NETWORKS

In the future, intelligent machines will replace or enhance human capabilities. Artificial intelligence is the intelligence exhibited by robots and it is having a huge impact on various fields as expert systems are widely used these days to solve the complex problems in various areas as engineering, science, medicine, business, manufacturing, transport, gaming. This paper focuses on an application of Artificial intelligence in the field of security. It is based on a project that was implemented to enhance the security of a Datacenter. Security is the primary concern of modern day. Datacenters are prone to problems like fire, cyber theft, water leakage from cooling systems or presence of rodents. The system consists of a robot, periodically patrolling the datacenter and continuously looking out for these identified problems via an onboard camera module, the problems are further classified using a trained neural net. A map of the workspace in the form of a binary occupancy grid is given to the robot so that it can position and maneuver itself in the datacenter autonomously using mobile robot algorithm: Monte Carlo Localization with particle filters. Also a variety of patrolling paths can be defined by the operator. If anything is detected a vocal message is given to alert the staff and after every patrolling cycle is complete, a summary report is generated. The operator can simply examine the report and know the situation without having to monitor the video feed.