University of Portsmouth develops AI tool for accurate car damage assessment
- An AI tool is being developed to accurately assess car damage post-accident, combining machine learning and computer vision technology.
- The University of Portsmouth is collaborating with ABL 1 Touch and Innovate UK to provide this tool to major UK insurance firms.
- The project aims to improve efficiency in assessing vehicle damage and enhance competitive advantage in the repair industry.
The University of Portsmouth's School of Computing, in collaboration with ABL 1 Touch and Innovate UK, is working on an innovative project to create an artificial intelligence tool. This tool is designed to accurately diagnose damage to vehicles after accidents and streamline the repair process. The initiative is particularly significant given that the Association of British Insurers reported that in 2024, motor insurers handled 2.4 million claims, marking a substantial payout of £11.7 billion. This uptick emphasizes the growing need for efficient damage assessment in the insurance industry. Professor Mohammed Bader at the University of Portsmouth stated that this tool will establish a technical benchmark for the industry, melding machine learning with computer vision technology. This integration aims to enhance the collaboration between engineers' hands-on expertise and advanced technological systems. By effectively diagnosing vehicle damage, the project is positioning itself as a transformative contributor to the sector. Graham Roberts, chief commercial officer of ABL 1 Touch, has highlighted the competitive advantage this AI-powered system could provide in a fast-paced industry where the diversity of vehicle damage types is considerable. Identifying and managing repairs efficiently is critical for businesses dealing with large volumes of accident cases. The company is focused on developing scalable solutions that minimize reliance on individual personnel while embracing mass data learning protocols, allowing for quicker and more accurate assessments. In conclusion, this project not only addresses the immediate practical needs of the automotive repair industry but also sets a precedent for future advancements in AI technology within the insurance and repair sectors. As this tool progresses, it could significantly transform how damage assessments are conducted, leading to more efficient operations and potentially reducing costs associated with insurance claims processing.