IoT Based Smart Irrigation System for Crops and Water Leakage Detection Using Image Processing

This paper will provide an image-processing technique for locating a water leak in subterranean pipes. When intelligent cities started to appear, several countries began to address this problem by utilizing technologies like intelligent water networks. However, this idea seeks to contribute to the context of smart cities using less complex and non-destructive technology. This study also makes a case for replacing the pretreatment stage of image processing with deep learning or machine learning techniques. It will be shown that this feature helps emphasize interesting spots and boost contrast. Thermal images of the soil's surface collected with an underground water leak were used to test the hypothesis. These conditions were presented in a lab using a flawless sandy soil model. Three sensors—ultrasonic sensors, soil moisture sensors, and temperature sensors—that are connected to a Raspberry Pi are used in this project. The system will use the idea of image processing to collect data from the plants. Before the fertilizer provision procedure is continued, this data will be compared to the Leaf Color Chart (LCC) chart. The project aims to create an effective irrigation system based on IoT. Utilizing sensors and image processing to improve irrigation effectiveness and monitor the soil's humidity, moisture, and temperature levels year-round.