A Framework for Remote Road Furniture Monitoring System Using Smart IoT Dashcams and Digital Twin

Monitoring the condition of road furniture, such as traffic lights, signposts, and guardrails, is critical for road safety and driving comfort. However, due to limited resources and the vast size of road infrastructure, comprehensive monitoring can be challenging. To address this issue, this study proposes a framework that automatically identifies damaged road furniture and displays their locations on the user interface, allowing inspectors to remotely monitor road furniture conditions. The framework leverages a road furniture digital twin, containing real-time information about road infrastructure, landmarks, and GPS coordinates. The framework was tested on the NDSU campus road, successfully detecting traffic poles with real-time information displayed on the user interface, reducing the need for manual inspections, and enabling proactive maintenance to improve road safety and driving comfort. The proposed framework is expected to facilitate the real-time remote monitoring of road furniture, minimizing the time, cost, and effort required for inspections.