Published Paper Details:

The recent decline in road infrastructure, especially the existence of potholes and speed bumps, has presented serious obstacles to the effectiveness and safety of transportation. Many creative solutions based on the fusion of cutting-edge detection techniques with Internet of Things (IoT) technology have been put forth to deal with this problem. This review examines and summarizes a number of research studies on Internet of Things-based pothole and hump detection devices. To accomplish precise identification, prompt alerting, and efficient road repair, these systems combine sensors, machine learning algorithms, and real-time data processing. Diverse approaches are presented in the surveyed publications for three-dimensional pothole identification, including sensorbased detection, machine learning integration, and even federated learning. This assessment offers a thorough analysis of the current status of IoT-based pothole and hump detection systems, shows their advantages, and suggests possible areas for future research and development by looking at the developments and insights from these investigations.