Using satellite imagery and AI to transform rural roads

We’re excited to introduce TRL as one of the top 5 solutions submitted to our Call for Submissions for technology solutions to realise sustainable roads in emerging markets.

TRL's solution uses satellite imagery and artificial intelligence to assess the condition of unpaved roads more efficiently, enabling roads to be prioritised for further inspection or treatment.

Currently, road authorities in many low- and middle-income countries have limited resources to gather information on rural roads, and traditional collection methods are slow and unreliable. As a result, most have limited knowledge of the condition of their unpaved rural roads.

TRL's solution provides previously unavailable highway inventory and condition data, enabling a step-change to a data-driven system that is optimised for the developing world to make better use of financial and physical resources, with the potential to transform roads, reduce emissions, and improve accessibility, affordability, and safety.

The solution was developed in six countries in Africa. To learn more about how it works, its benefits, and where it has been applied, visit the case study below.

View the case study