Telematics and machine learning system for estimating the load condition of a heavy-duty vehicle

• Published in: Procedia computer science Vol. 232; pp. 2616 - 2625
• Main Authors: von Glehn, Fabio Ribeiro, Gonçalves, Bruno Henrique Pereira, Neto, Marlipe Garcia Fagundes, Fonseca, João Paulo da Silva
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 2024
• Subjects: Big data analytics; Fuel saving; Heavy-duty vehicles; Machine learning; Telematics; Telematics; Big data analytics; Heavy-duty vehicles; Machine learning; Fuel saving

This study employs machine learning techniques to determine whether trucks are loaded or empty based solely on data from the vehicle's communication network, especially from the engine module. We achieved an accuracy of over 85% for short hauls (0.5 to 5 km) and nearly 95% for long hauls (5 to...