An AI Based Irrigation and Weather Forecasting System utilizing LoRaWAN and Cloud Computing Technologies

Abstract

Artificial Intelligence (AI) has been flourishing recently as a viable solution for many applications and scenarios, including smart irrigation and weather forecasting systems. In these systems, it is crucial to have an accurate prediction for the weather and soil conditions to optimize the irrigation process such that the minimal amount of water is provided. In this paper, a smart irrigation system utilizing Artificial Intelligence (AI) and Long Range Wide Area Network (LoRaWAN) communication link is proposed. The system is composed of sensors that are used to measure soil moisture, atmosphere temperature, and humidity. This information is sent via LoRaWAN communication link to a remote center that gathers, analyzes the captured information, quantifies the appropriate amount of water for irrigation, and then sends the decision back to the irrigation system. Furthermore, the collected information will be stored in the cloud for wider accessibility. This paper describes the technical implementation of the smart irrigation system and focuses on the weather forecasting process, which is performed using the Wind Driven Optimization - Least Square Support Vector Machine (WDO-LS-SVM) algorithm. The obtained results show a better performance when compared to the LS-SVM, which verifies the effectiveness of jointly utilizing the WDO with the LS-SVM.