Researchers: Stephen Famurewa, Johan Odelius (PL)
Sponsor: Interreg Nord
Project period: 2017-2019
Goal: Industrial Internet Applications in Winter Road Maintenance
Project status and results
Winter road maintenance optimization requires information about the current and future road condition for various road segments with a network. This information can be derived from weather data or vehicle-based road condition measurements in instances where road weather stations are sparsely located. This project addresses different measurements technologies for road condition monitoring and the use of the measurement for maintenance decision support. Besides the weather data obtained from measurement stations, laser and vibration-based measurement systems are used for road friction and roughness estimations. The condition data is processed, and the output is presented in real time using an intelligent web-based visualization tool and state-of the art IoT technologies. In addition, a road maintenance decision support system is also designed to alert contractors or administrators on most likely maintenance actions to be carried out. The alert modelling approach is a supervised machine learning model that is based on weather and road condition data, the approach is illustrated in the figure below.