Early Warning System to Prevent Animal-Train Collision

Abstract

The project aims to prevent animal-train collisions by using an image processing system that can identify obstacles on the train tracks, particularly animals. The project utilizes machine learning algorithms to identify the obstacles and send a notification to the train if an obstacle is detected. The system uses an IoT application and Bluetooth transmitter to send a message to the train and trigger a buzzer notification. By utilizing technology, the project hopes to reduce the number of animal-train collisions and improve safety for both humans and animals. The system utilizes machine learning algorithms to identify the obstacles in real-time and send a notification to the train via an IoT application and Bluetooth transmitter. If an obstacle is detected, a buzzer notification will be triggered on the train, alerting the driver to slow down or stop. The image processing system is designed to be highly accurate and efficient in identifying animals on the tracks, even in challenging lighting or weather conditions. The system is trained using a large dataset of images of animals and non- animal objects on train tracks, enabling it to recognize animals of various sizes, shapes, and colors. Overall, the goal of this project is to reduce the number of animal-train collisions and improve the safety of train travel. By leveraging the power of machine learning and IoT technology, this system can provide an effective solution to a pressing safety issue." To accomplish this, the project utilizes an image processing system that is highly accurate and efficient in identifying animals on the tracks, even in challenging lighting or weather conditions. The system is trained using a large dataset of images of animals and non-animal objects on train tracks, enabling it to recognize animals of various sizes, shapes, and colors. The goal of this project is to reduce the number of animal- train collisions and improve the safety of train travel. By leveraging the power of machine learning and IoT technology, this system can provide an effective solution to a pressing safety issue.