While this may appear to be a highly specialized engineering issue, container yards are central to global supply chains, shaping how quickly goods move from factories to retailers and ultimately to consumers.
The problem is, in part, geometric: RTK-GPS modules are typically mounted at the top of the crane boom, not at the center of the spreader that grips the container. As the spreader rotates, this offset creates orientation-induced positioning errors.
Over time and across multiple stacks, these small discrepancies compound, disrupting spatial planning and yard efficiency. In ports handling hundreds of thousands of containers, even small alignment inconsistencies can lead to operational slowdowns and increased handling effort.
The research, reported in Applied Sciences, addresses this blind spot.
Deterministic Sensor-Fusion
In addition to positional data, the researchers integrated angular measurements from a Bosch BHI260AP inertial sensor mounted on the spreader. The fusion model combines absolute RTK-GPS coordinates from the boom, real-time angular orientation from the spreader, and known boom-length geometry to correct placement offsets.
Using direct geometric correction equations rather than probabilistic filtering techniques such as Extended Kalman Filters, the system deterministically compensates for orientation-induced errors.
The choice of a deterministic model reflects the operating conditions of yard cranes: Slow-motion dynamics and fixed mechanical geometry. Under these constraints, the authors argue that complex probabilistic filtering adds unnecessary computational burden without improving reliability.
Two core operations were evaluated, container drop and container pickup.
A System Designed For Realistic Operations
The proposed Container Spatial Localization-Yard Management System (CSL-YMS) consists of a base station equipped with an RTK receiver that generates correction data, and a Yard Crane Microcontroller (YC-MC) unit installed on the crane.
Communication takes place over 4G networks, while RFID modules identify containers and FLASH/SD storage records tracking data. Bluetooth supports local communication within the system.
Correction data is transmitted via 4G to an RTK server, which then broadcasts the information to crane units. The YC-MC processes positioning, orientation, and identification inputs in real time, forwarding tracking information to a remote server for monitoring and analysis.
Energy Efficiency Achieved by Power Task Clustering
Continuous IIoT operation can place sustained demands on embedded systems, particularly when microcontrollers remain active throughout task cycles. To address this, the team used a scheduling mechanism known as Power Task Clustering (PTC).
PTC applies empirically defined efficiency coefficients to dynamically adjust power and timing parameters. Modules such as GPS and communication components transition into sleep states when processing is not required.
At scale, even incremental efficiency gains of this kind can lower energy use across logistics infrastructure and contribute to more sustainable port operations.
Under laboratory-scale testing conditions, the approach reduced total energy consumption by 34.44 % and latency by 21.8 %. The authors also report an approximate improvement of 95 % in a composite internal energy–latency performance metric.
Importantly, the reduction in energy use did not come at the expense of responsiveness.
Tested in Controlled Conditions
The framework was tested using a wooden laboratory-scale prototype designed to validate geometric correction and scheduling performance. The setup did not incorporate full-scale crane vibration, shock loading, or electromagnetic interference typical of operational port environments.
Within these controlled conditions, the fused RTK-GPS and inertial sensing approach achieved centimetre-level positional stability, with clear convergence of error values across repeated trials.
However, validation on full-scale yard cranes operating in live port environments is still required.
Progress Towards Reliable Yard Automation
The study suggests that orientation-aware sensor fusion and energy-conscious scheduling can simultaneously improve localization accuracy and operational efficiency, rather than forcing a trade-off between the two.
If validated at port scale, the approach could support more reliable container stacking, improved space use, and longer-lasting IIoT deployments.
For researchers and engineers working in automated logistics, related areas worth further investigation include deterministic versus probabilistic fusion in constrained mechanical systems, adaptive power management in edge computing, and real-world validation strategies for IIoT-enabled crane automation.
Journal Reference
Dahiya, S., Chawla, R., & Fortino, G. (2026). CSL-YMS: Sensor-Fusion and Energy Efficient Task Scheduling. Applied Sciences, 16(4), 1732. DOI: 10.3390/app16041732
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