As the global population surpasses 7.2 billion and continues to grow, the persistent threat of food scarcity intensifies, necessitating the advancement of agricultural methodologies. This study introduces a comprehensive smart farming framework utilizing LoRa technology to address water scarcity and optimize resource usage. The developed prototype employs dual ESP32 ARDUINO and LoRa boards: one interfaced with environmental sensors within the field to measure temperature, soil moisture, and water flow, and a secondary one positioned within a 10 km radius connected via WiFi. The collected data is transmitted to BLYNK Platform for analysis, enabling precise, automated control of irrigation systems, thus saving farmers' time, costs, and energy. This system, tested in Morocco, specifically in the Doukkala region, a diverse agricultural area, where agriculture is integral to the economy, leverages IoT and sensor technologies to transform traditional farming practices. The suite of sensors deployed ensures optimal watering of crops. Managed through a mobile application with cloud integration, the system provides a robust solution even in areas of low internet connectivity. Utilizing renewable energy, this approach offers a resilient, accessible means for farmers to gauge environmental compatibility, supported by a dedicated information-providing website. This paper demonstrates that intelligent crop monitoring combined with autonomous irrigation constitutes a scalable and effective solution for achieving sustainable agriculture in an increasingly populous world.
- Aitlmoudden O., Housni M., Safeh N., Namir A. A Microservices-based Framework for Scalable Data Analysis in Agriculture with IoT Integration. International Journal of Interactive Mobile Technologies. 17 (19), 147–156 (2023).
- Ma Y.-W., Chen J.-L. Toward intelligent agriculture service platform with lora-based wireless sensor network. 2018 IEEE International Conference on Applied System Invention. 204–207 (2018).
- Ray P. P., Mukherjee M., Shu L. Internet of Things for Disaster Management State-of-the-Art and Prospects. IEEE Access. 5, 18818–18835 (2017).
- Brewster C., Roussaki I., Kalatzis N., Doolin K., Keith E. IoT in Agriculture: Designing a Europe-Wide Large-Scale Pilot. IEEE Communications Magazine. 55 (9), 26–33 (2017).
- Geng L., Dong T. An Agricultural Monitoring System Based on Wireless Sensor and Depth Learning Algorithm. International Journal of Online and Biomedical Engineering. 13 (12), 127–137 (2017).
- Persia S., Carciofi C., Faccioli M. NB-IoT and LoRA connectivity analysis for M2M/IoT smart grids applications. 2017 AEIT International Annual Conference. 1–6 (2017).