The University of Leicester has teamed up with aerial mapping provider, Bluesky International to develop geospatial data solutions for insurers.

The project combines machine learning and artificial intelligence with satellite imagery and aerial survey data to improve the analysis of urban environmental data such that it automatically recognises building classifications and structure detail.

"We were keen to explore the potential of AI and machine learning for the automatic identification and classification of data for use within the insurance sector," said James Eddy, technical director of Bluesky International. "So, having strong ties with the academic community having worked alongside university and higher education organisations on other projects, we approached the University of Leicester.

"Directed to the School of Mathematics and Actuarial Science, we were introduced to SPRINT. The space-based aspect means we can use mathematical methods to look at data in different forms, and, by the end of this project, we hope to develop a technique to extract data and produce it commercially for a range of sectors."

Ivan Tyukin, professor of Applied Mathematics at the University of Leicester added, “Satellite data is an extremely valuable resources, and the volume of this data grows very fast. It is hence important to develop methods enabling organisations to utilise this wealth of resources in the most efficient and reliable way. In our project we will employ state-of-the-art machine learning techniques to extract information from available satellite datasets and fuse this extracted information with Bluesky’s own proprietary data to increase Bluesky’s data analysis capabilities."

The Bluesky University of Leicester project will be funded by a grant from the £4.8m Space Research and Innovation Network for Technology, or SPRINT programme, which was created to provide businesses with access to university space expertise and facilities.

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