Intelligent monitoring and control of farmland based on edge-cloud collaboration and digital twin for digital energy management: investment benefit analysis

• Published in: Renewables : wind, water, and solar Vol. 12; no. 1; pp. 43 - 13
• Main Author: Liu, Zheng
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer Nature B.V 01.12.2025; SpringerOpen
• Subjects: Accuracy; Adaptive algorithms; Agricultural equipment; Agricultural land; Agricultural resources; Bottlenecks; Collaboration; Crop diseases; Crop yield; Data analysis; Data collection; Decision making; Deep learning; Deep reinforcement learning; Digital energy management; Digital twins; Economic benefits; Edge computing; Energy consumption; Energy flow; Energy management; Energy storage; Energy utilization; Environmental monitoring; Game theory; Intelligent monitoring of farmland; Investment benefit analysis; Irrigation; Irrigation water; Latency; Maintenance costs; Monitoring systems; Network latency; Optimization; Photovoltaic cells; Photovoltaics; Reinforcement; Resource allocation; Sensors; Systems stability

The current farmland energy management and monitoring system still has problems, such as poor real-time data collection, low energy utilization efficiency, and insufficient intelligent decision-making. Focusing on digital energy management, this paper proposes a data collection and analysis based on...