A LoRa-Based Internet of Things Smart Irrigation Control Solution with Hybrid Classifier CNN-SVM.

Water management is critical in nations with water scarcity and it affects farming significantly. Farming plays a major role in human livelihood with the increase in population. Presently, automated greenhouses integrating IoT-sensor devices that track vital parameters for agricultural operations can be found. The several data gained from the field provides a solid basis for farmers to tailor their irrigation practices consistently. This study proposes a LoRa-based Internet of things smart irrigation control solution with a hybrid classifier CNN-SVM. The proposed LoRaWAN combines Ultra-low-power IoT sensors that are tactically set up over the plantation field to track the soil parameters. The solution is aimed at bypassing weekly irrigation demanded in farming operations, in conformity to soil states and climatic. The direct collection of a live report from the farm area is conceived to reinforce the irrigation activity and present the farmer with sufficient data, like timing for irrigations, and mitigate the overall costs of conservation and water. The tracked soil measurement is delivered to the IoT cloud server for storage and analysis with machine learning algorithms to take up the schedules to perform in the field. The experimental analysis confirms the sovereignty of the proposed solution in terms of precision, recall, accuracy, and validate the energy and delivery ratio capacity. [ABSTRACT FROM AUTHOR]