Design & Development of a Road Safety Device

Ahmed Tamim Zabir Prince, Dipta Paul, Zahid Hasan Khoka, Mahabub Alam Khan, Md. Mehedi Hasan, Arafat Matubbar Earik, Md Fahim Khan, Sayed Afridi

Image processing, neural network, sensor, road safety.

Traffic accidents represent a serious threat to public safety because they cause a sizable number of fatalities and injuries each year. The primary causes of these collisions include driver fatigue, high vehicle speed, inattentiveness, and difficulty navigating turns on the road. This study suggests the development and application of a sophisticated road safety device to greatly improve driving safety and lower accident rates to address these problems. The proposed system can recognize traffic signs and promptly notify motorists of impending speed bumps and curves in the route. In addition, it has a function that tracks driver fatigue, reducing one of the major factors contributing to auto accidents. Additionally, the device has accident probability detection built in, which enables preventative actions to be conducted in high-risk scenarios. In addition to providing real-time position tracking, the system automatically notifies neighboring police stations and hospitals in the event of an accident, facilitating emergency response. Neural network-based image processing and an embedded sensor system are the two main technologies used in this system. A system block diagram has been proposed and expected to have low mistake rates in all major features and confirming the system's potential as an affordable way to increase traffic safety.

Received: 10 Nov 2024, Receive in revised form: 13 Dec 2024, Accepted: 16 Dec 2024, Available online: 24 Dec 2024

10.22161/ijaers.1112.8