DESIGN OF A SMART IRRIGATION SYSTEM USING SOIL MOISTURE AND TEMPERATURE DATA FOR EFFICIENT WATER MANAGEMEN
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Abstract
The Agriculture will have to be well run so that it is sustainable, and it can address the issue of water scarcity. The ancient irrigation systems tend to be either manual or follow a routine pattern thus ineffective in the usage of water and low yields. This paper provides a summation of the design and evaluation of a smart irrigation system that relies on data on soil moisture and temperature to make irrigation decisions automatically. The proposed system applies a decision model that involves a set of rules to determine the most appropriate time to irrigate, i.e. the time when there is a need to do so. A structured dataset of crop type, soil moisture, temperature and pump status were used to simulate real-world irrigation scenarios. The system was tested under a controlled environment so as to measure its performance in regard to accuracy of the decisions made water efficiency and its sensitivity to the environment. The results showed that the system was most precise in predicting the irrigation requirements and conserved much of the unnecessary water usage compared to the traditional irrigation methods. The main factor that determined the irrigation decision was found to be soil moisture whereas temperature increased system adaptability to different environmental conditions. The proposed system is simple and economically feasible, which makes it a viable solution to implement in the real-life scenario, especially in the small- and medium-scale agricultural environment. The paper emphasizes the possibility of combining sensor-driven data and automation to enhance the efficiency of irrigation and help to implement sustainable water management strategies. Future work can include real time implementation as well as incorporation of other environmental parameters to further improve the performance of the system.
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