IoT-Enabled Smart Drip Irrigation System Using Web-Based Applications and Inception Net for Enhanced Water Management

One of the most important challenges modern agriculture poses, particularly in areas experiencing water shortage, is water management efficiency. Many times, conventional irrigation systems lack the ability to precisely control water distribution and result in resource waste. Internet of Things (IoT)-activated smart drip irrigation systems offer a special solution by including real-time data collecting and machine learning models to maximize water use. In this work, a smart drip irrigation system enhanced by Inception Net for real-time monitoring and predictive analytics is presented. Underlying system control is a web-based application. Over the field, sensors dispersed collect data on soil temperature, humidity, and moisture content. Collected on a cloud platform for the Internet of Things, these data points are used by the Inception Net model to create precise water consumption forecasts. By means of a web-based application serving as the user interface, farmers may remotely monitor field conditions, receive alarms, and automatically schedule irrigation. The findings show rather significant increases in water efficiency and crop yield. Though crop yield rose by twenty-25%, forty percent less water was used than in conventional drip irrigation systems. Forecasting ideal water needs, the Inception Net model exceeded current models by 8-10% with an accuracy of 96.8%. The simplicity of application control and the availability of real-time insights help to explain why 87 percent of respondents of the user satisfaction survey gave good comments.