Object Detection using Infrared Systems During Fog and Rain

Abstract

This research study focuses on the utilization of infrared systems for object detection during fog and rain, aiming to improve detection accuracy in adverse weather conditions. Road accidents caused by foggy and misty weather conditions claimed 13,372 lives in 2021 in India, and another 25,360 were left injured — more than half were grievously injured. The current research has highlighted the challenges posed by fog and rain on traditional sensors and the potential of infrared technology to overcome these limitations. The rationale for this new research lies in the need for robust and reliable object detection in adverse weather scenarios, particularly for autonomous driving systems. The research methods involve designing and implementing an infrared-based object detection system, incorporating preprocessing techniques, and employing object detection algorithms and frameworks. The study's major findings demonstrate the potential of infrared systems in enhancing object detection reliability in foggy and rainy conditions, as evaluated using real-world datasets. The significance of this study lies in its contribution to improving road safety by providing valuable insights into the utilization of infrared technology for object detection in adverse weather scenarios.