JJEM: Special Edition 2 (December 2024)
JJEM: Special Edition 2 (December 2024)
2024-12-08
Enhancing Road Safety in Remote Areas Through Machine Learning.
Srushti M S, Adarsh M J
Road accident in remote location presents a substantial challenge, delayed accident detection and emergency response exacerbate the severity of road accidents, this work seeks to develop a resilient system for accident detection by employing modern machine learning models techniques. precisely convolutional neural network (CNN) and residual networks (ResNet), by deploying GPS statistics and comprising images and videos from traffic cameras representing both accident and non-accident scenarios the device precisely identify accidents in real time. The fundamental challenge is the delayed emergency response is isolated regions due to the lack of effective monitoring infrastructure, the strategy involves leveraging CNN and ResNet models, with a varied dataset to increase the system ability to accurately differentiate between accident and non-accident situations. this situation expedite emergency services can be alerted more swiftly, which has the potential to save lives and decrease the severity of injuries, advanced techniques in image processing and machine learning support highly accurate and reliable accident detection capabilities.
Encompass accident detection, minimizing human fatalities, real-time location tracking, emergency notifications and leveraging CNN for image classification tasks, ResNet, GPS.