CSL-YMS: Sensor-Fusion and Energy Efficient Task Scheduling

In many IIoT-based yard operations, accurately identifying the spatial position of containers is becoming increasingly relevant as operators try to automate stacking and retrieval processes by technologies like Container Spatial Localization (CSL). Despite this automation in IIoT, RTK-GPS–based container stacker positioning frequently lacks precision, which causes disruptions in stacking and reduces efficiency in space utilisation. Though it offers placement precision accurately up to 3 cm, this is still insufficient in high-volume Yard Management Systems (YMS). Consequently, this yields to variable container orientation, waste of usable space, increased man input is required in handling goods, and potential automated system failures. This research proposes a novel methodology that combines conventional RTK-GPS measurements with angular information captured from a BHI-260AP–based spreader sensor, allowing the system to correct container placement errors arising from orientation rather than only from positioning. In addition to the spatial positioning problem, we found that continuous IIoT operation raises concerns regarding energy use, particularly when micro-controllers remain active throughout the task cycle. As a solution, this integrates a dynamic task scheduling approach that puts the device in sleep modes whenever computation is not required. In our experiments, this strategy improved overall power efficiency by 34.44%, which makes long automated operation more practical.