A Remote Surveillance System Based on Artificial Intelligence for Animal Tracking Near Railway Track

In this paper, a Pi camera is properly positioned to record an animal completely crossing a railway track is proposed. In addition, the camera sends information to the central server, where it is evaluated before being used to notify interest groups of an alert. Because of the dramatic growth in human occupancy, studying wildlife in its natural environment is an essential responsibility for ecosystems. Due to the extensive train infrastructure built along woodland areas, animals living there encounter hazardous conditions when attempting to cross. Artificial intelligence (AI) based approaches that increase safety and the effectiveness of the Intelligent Transportation System (ITS) have been created to prevent such hurdles. The Deep Learning (DL) technique is used in the proposed study to boost security and safety in various ITS services at railway crossings. The Artificial Intelligence based Surveillance System for Railway Crossing combines input detection and classification techniques. The MKR1300 LoRaWAN, which is a combination hardware-based timer, is used for data transmission. By using a neural network and an image processing technique, real-time danger and unsafe scenarios can be independently identified. This is made possible by the graphics processing unit (GPU) that is being used.