JoWUA

Abstract

This article proposes an IoT-based dynamic irrigation scheduling system that would enhance the process of water management and maximization of crop production in heterogeneous crop fields. The system uses cheap sensors such as water level sensors, soil moisture sensors, temperature/humidity sensors, and rain sensors to gather real-time information to make the right decisions related to irrigation. Through the incorporation of IoT technology, the system will be able to support automated irrigation, as well as manual control, and will be flexible with regard to the input of the farmer. One of the innovations is the dynamic scheduling mechanism that responds to the crop growth phases and thus optimizes the use of Water at each stage of the crop life cycle. Through the experimental findings, crop yield has increased by 10%, and water consumption by 20% has been reduced as opposed to the traditional techniques. The results of statistical analysis indicate that there is a positive correlation with a correlation coefficient of 0.92 between dynamic irrigation and better crop yield, with an average water saving of 18%. In addition, an F-test will prove the statistically significant differences (p < 0.05) in the water use and yield between the proposed system and the traditional irrigation systems. This design of the system functions within the limits of low-cost and low-energy, which is why it is a feasible solution in water-deficient areas. It also facilitates real-time monitoring and remote control, which increases convenience and accuracy for the farmers. The work can be useful in the field of sustainable food production by using the IoT in precision farming. The further development of the system will be based on the introduction of artificial intelligence to make irrigation predictable and the expansion of the functionality of the system to cover a larger variety of crops and environmental conditions, which will further boost agricultural productivity and environmental sustainability.