An Ontology-Based System for Detecting and Repairing Road Potholes Through Community Involvement

Potholes pose significant risks to road safety, endangering both human lives and vehicle integrity. Enhancing the safety of road infrastructure hinges on the prompt identification and repair of these potholes. This article introduces an affordable pothole detection system that engages citizens by utilizing smartphones to efficiently report these dangers. The system uses people's mobile devices to capture images of potholes and record their location using GPS data rather than expensive or complex machine learning detection techniques. The reports are then geolocated on a map, allowing for a clear visual representation of the distribution of potholes in the area. Once reported, these potholes are recorded using an ontology and integrated into road maintenance management systems. We use a generic ontology called “a lightweight implementation of the unified fundamental ontology (gUFO)” for the implementation of our ontology, the system provides an organized and scalable framework for classifying pothole-related data. This method facilitates seamless data integration, ensures consistency across different data sources, and improves interoperability with existing infrastructure systems. The system's ability to efficiently share and interpret data is enhanced by Semantic Web technologies, thereby promoting road safety and actively involving the community in improving urban infrastructure through a smart and interconnected network.