ScanSpot: 3D-Modelling "Digital Twin" Data For New Insurance Products

ScanSpot combines cutting-edge multi-modal sensor Light Detection And Ranging (LiDAR), thermal imaging and mmWave radar technology with machine-learning computer vision techniques to generate new risk classification data for the insurance industry to develop and cost new insurance products for renewable energy and freight/logistics customers.

The project assembles a British consortium of Aegis Energy, Oxford University, Blenheim Renewables and Nomad Engineering, collaborating with insurance advisers FreightSafe and MDMG Consulting. The project builds on recent pioneering research by Oxford in multi-sensor detection and tracking of moving objects (DATMO) technology. The project responds directly to insurance and industry priorities to improve the safety and security of renewable energy and EV-charging facilities across the UK, and addresses ESG risks limiting the speed of EV-adoption in the commercial sector, and the impacts of growing renewables and cargo-theft crime on British communities.

The shift to renewables in Britain has been accompanied by an evolution in the risks facing insurance companies and their customers. EV battery fires for instance are forecast to increase from 9,400 incidents in 2022 to 260,000 annually by 2035 (Thatcham Research, 2023). Police and insurers are also reporting a significant increase in the theft of high-value EV chargers and batteries, and copper/componentry from solar farms (Crimestoppers; TT-Club,2023). New risks add to the soaring problem of cargo theft costing insurers and the freight-forwarding industry upwards of £500m/year in 2022 (NaCVS).

ScanSpot will deliver a cloud-based software product for the insurance industry and their customers to analyse, classify and mitigate risks such as fires, theft and unsafe vehicle behaviours. The system compiles 15 months of novel data collected from a new multi-sensor array prototype installed at two British renewables/EV charger facilities, and applies AI deep-learning models for automated anomalous incident flagging. Data and the results of the project will be shared widely with insurers, police and industry. With a user-friendly app interface, ScanSpot will empower security monitors to act with confidence on targeted situations deserving further investigation, and provide facility owners with confidence that their insurance premia are being appropriately costed according to actual risk. ScanSpot can save insurers and their customers considerable premium and claim costs whilst directly addressing ESG concerns such as high insurance costs limiting the speed of EV adoption, increased rates of anti-social crime affecting the renewables and freight/logistics industries, and excess emissions caused by criminal damage, theft and redeliveries.