Summary
This paper presents the design and validation of an intelligent farm machinery operation control platform utilising Internet of Things technology to enable remote and autonomous operation of multiple agricultural machines on unmanned farms. The system incorporates improved DeepLabV3+ algorithms for high-precision field mapping and boundary detection, coupled with path planning, task scheduling, and safety management models. Platform integration tests demonstrate the feasibility of reducing operational personnel requirements and professional skill thresholds, with potential implications for future single-operator or fully autonomous farm management.
UK applicability
The platform's automation and remote control capabilities are potentially applicable to UK large-scale arable and mixed farming operations facing labour shortages, though uptake would depend on infrastructure compatibility, regulatory approval for autonomous machinery, and cost-benefit analysis relative to farm scale. The high-precision mapping methodology could support precision agriculture practices relevant to UK soil and environmental management standards.
Key measures
High-precision map construction error (<3 cm); automatic field boundary extraction completeness rate (96.71%); boundary extraction correctness rate (95.63%); number of personnel required for simultaneous multi-machinery operation
Outcomes reported
The study reports the design and testing of an Internet of Things (IoT) control platform enabling remote operation of multiple farm machinery types simultaneously. Key performance metrics included high-precision field mapping with sub-3 cm error, 96.71% automatic boundary extraction completeness, and 95.63% correctness rates.
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