Forklifts are essential for transporting goods in industrial environments. These machines face wear and tear during field operations, along with rough terrain, tight spaces and complex handling scenarios. This increases the likelihood of unintended impacts, such as collisions with goods, infrastructure, or other machinery. In addition, deliberate misuse has been stated, compromising safety and equipment integrity. This paper presents a low-cost and low-power impact detection system based on multiple wireless sensor nodes measuring 3D accelerations. These were deployed in a measurement campaign covering realworld operational scenarios. An algorithm was developed, based on this collected data, to differentiate high-impact events from normal usage and to localize detected collisions on the forklift. The solution successfully detects and localizes impacts, while maintaining low power consumption, enabling reliable forklift monitoring with multi-year sensor autonomy.
@article{arxiv.2509.04096,
title = {Low-Power Impact Detection and Localization on Forklifts Using Wireless IMU Sensors},
author = {Lyssa Ramaut and Chesney Buyle and Jona Cappelle and Liesbet Van der Perre},
journal= {arXiv preprint arXiv:2509.04096},
year = {2025}
}