Enhancing Real-Time Monitoring and Control of Evapotranspiration Using an IoT-Based Data Logging System in Agriculture.

This study shows the construction and assessment of an IoT-based data logging system that can be used to improve real-time monitoring and control of evapotranspiration in farm environments. The aim of the research was to maximize water use, enhance crop production, and give a stable system of automated irrigation, which is capable of alluding dynamically to the changing environment. The system incorporates soil moisture, soil temperature and water tank level sensors with a microcontroller and a program of fuzzy logic to determine accurate irrigation needs. The collected data on the sensors are processed on real-time basis and adaptive controls can be used to adjust the water delivery using the pumps controlled by the relays. The main findings indicate that the system saves 20-30 percent of water used in the conventional irrigation systems, the system is 95 percent accurate in measuring the amount of soil moisture, and the system elevates the crop production by 15 percent. The system is also characterized by low response time of less than five minutes and high availability with a 98 percent availability during testing. The monitoring interfaces that allow advanced real-time monitoring such as the use of LCDs and mobile notifications make it possible to have a continuous monitoring and interventions take place. The results illustrate the benefits of using the IoT-based fuzzy logic control compared to traditional irrigation techniques, which can make substantial contributions to precision agriculture. The proposed system by offering cost-effective resource control, reducing human labor, and enhancing ecological approaches to modern agriculture is a viable, scalable, and sustainable solution to the current agricultural intensive methods. The further research of the system can be dedicated to its expansion and its integration with the current farm activities and the use of more sensors to monitor and secure the system.

Internet of Things, data logging, Fuzzy Logic

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