A Novel Approach to Vehicular Safety: Raspberry Pi-based Collision Avoidance and Connectivity in Smart Automobiles Leveraging AI-driven Sensor Fusion

The introduction of smart and connected vehicles has had a dramatic impact on the automobile sector. Given the continuously evolving context, ensuring vehicular safety is important. The present research describes a novel way to improve vehicle safety by combining a Raspberry Pi-based collision avoidance system with complex networking features in smart cars. The implementation of artificial intelligence-driven sensor fusion, which integrates data from various onboard sensors to enhance collision prediction and prevention, is the fundamental element of the invention. The paper describes an extensive technique that includes hardware setup, data collecting, sensor fusion, AI-driven collision prediction, enhanced networking, and real-world testing. The results of simulated and real-world scenarios show that the technology has the potential to greatly improve road safety. It was able to achieve high collision prediction accuracy, quick response times, and excellent communication with other cars and infrastructure. Furthermore, a comparison with the existing method demonstrates the unique approach’s improved performance and benefits. The proposed research is an important step toward establishing total vehicular safety in smart automobiles and opens the path for future automotive technology advances.