Smart Sensing for Container Trucks

Chengyuan Xu, Bin Zhao, Rongwei Yang, Bingyi Liu, Jianping Wang, Jinfan Wang

Abstract: Container logistics is a typical logistics model with complex business processes. In recent years, operation optimization in logistics is identified as significant in cutting labor costs and boosting productivity. To implement operation optimization in container logistics, the accurate load measuring and operational situation information are the prerequisites. However, the current labor-driven measurement and situation recognition suffer from inevitable delays, errors, and expenses. To tackle these challenges, the authors propose a smart sensing system that intelligently achieves the container load measurement and operational situation recognition. In this paper, the authors present a novel approach for load measurement and the design of an edge-computing-powered controller. The kNN (k-Nearest Neigh-bor) has been introduced to develop an Operational Situation Recognition (OSR) model. The authors realize and implement the smart sensing system in the production environment. Rigorous analysis and prototype evaluations demonstrate the effectiveness of the proposed system.