AI based decision support and automated winter maintenance.

Purpose and goal

The project aims to establish a full-scale implementation and operationalization of an AI-based winter road maintenance ecosystem based on Klimator´s products and forecasting models. The goal is to integrate Klimator´s forecasts and analyses into Maine DOT´s daily winter operations and take the solution from Proof of Concept to operational use, reduce salt usage and establish an environmental reporting that considers the watersheds.

Expected effects and result

The project is expected to deliver an operational AI decision support system integrated into Maine DOT´s daily winter maintenance, improving traffic safety and reducing operator workload. AI-controlled salting provides a basis for reduced salt use without compromising service levels. Chloride loads on sensitive watersheds are measured and documented for the first time. Results form the foundation for statewide scaling across Maine and broader US market distribution.

Planned approach and implementation

The project is structured in 4 work packages. WP4 integrates Maine DOT´s new RWIS IoT network into Klimator´s RSI models and deploys an AI nowcast model. WP5 installs the AHEAD system on salt vehicles for quality monitoring and analysis of savings potential in AI-controlled salting. WP6 links salt usage in watershed areas to measure chloride loads and support environmental reporting. WP7 evaluates operational and environmental performance and prepares for scaling across Maine and the US market.