SafeTrax: Smart Collision Prediction and Alert System Using IoT for Sustainable Traffic Safety

• Published in: IEEE access 2025, Vol.13, p.6667-6684
• Main Authors: Amin, Md. Fahim Bin, Khan, Israt Jahan, Akter, Faria, Ahmed, Adib, Islam, Md. Motaharul
• Format: Article
• Language: English
• Subjects: Accidents; Accuracy; AWS IoT Greengrass; Cloud computing; collision; Crashes; Data models; Deep learning; Hidden Markov models; Internet of Things; IoT; Learning programs; pedestrian; Predictive models; Real time; Real-time systems; Road safety; Roads; SafeTrax; Safety; Sensors; Traffic; Traffic accidents; Traffic accidents & safety; Traffic safety; Vehicles
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3524676

With the rise in traffic accidents worldwide, it has become very important to have a more effective way to ensure road safety. To address this issue, we have made a system called SafeTrax. SafeTrax uses deep learning to predict traffic accidents and car crashes. Additionally, it has been implemented with the Internet of Things (IoT) to gather real-time data from sensors, and AWS Greengrass to process that data quickly and give drivers timely warnings. Unlike old safety systems, SafeTrax can predict if an accident might happen. It warns drivers beforehand to make roads safer for cars, people, and other animals. SafeTrax uses video frames from camera sensors in cars to look for dangers. It then uses a special deep-learning program to figure out if a crash might happen. One important part of SafeTrax is the integration of AWS IoT Greengrass. It helps the system work faster by using cloud services on devices like the Raspberry Pi. This means the system can quickly check the data and send warnings in time. SafeTrax can ensure safer roads, and it can help save lives.