A Novel Methodology for Sustainable Agriculture: IoT-Driven Water Management and Crop Planning Using LoRaWAN
Year: 2025
Type: article
Abstract: Efficient farming is an advanced and capital-based method of sustainable and clean food production. An IoT and AI-based system with the application of LoRaWAN technology is proposed for efficient environmental monitoring in farming. The system incorporates IoT devices installed in crop fields to provide real-time data visualization, monitoring, and control of key parameters such as temperature, humidity, soil moisture, TDS, and water levels. These sensors are attached to ESP32 microcontrollers with LoRaWAN modules, transmitting data at 915 MHz to ensure low-power, long-range communication. The system attains high accuracy (98.5%) when predicting water requirements, addressing issues like overfitting that are common in standard approaches. Additionally, the system follows an integrated novel methodology-gy that includes Assessment of the water balance to improve crop planning, and IoT-based optimized irrigation scheduling executed through a LoRaWAN-integrated cloud environment for data storage and visualization. Experimental results confirm the system's higher performance in enhancing water distribution and prediction, resulting in an 8% increase in water use efficiency and a 15% reduction in crop water utilization issues. These results highlight the potential of IoT and LoRaWAN technology to advance water resource management and promote sustainable agricultural practices in rural regions. The system also triggers warnings for low soil moisture, high TDS, and critically low water levels, with sensor data transmitted via LoRaWAN every 120 seconds to provide farmers with real-time insights for improved decision-making.
DOI: 10.14419/zx5zws07
Institution: Ashland University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4416596426
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