Crop Water Requirement Predication in Automated Drip Irrigation System Using IoT

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Mirza Nemath Ali Baig, Ayaaz Khan, MD. Salauddin, Mohd Zubair Khan


            The project "Crop Water Requirement Prediction in Automated Drip Irrigation System using IoT" aims to develop a system that optimizes water usage in agricultural irrigation by predicting crop water requirements. By employing IoT devices, sensors, and data analytics techniques, the system aims to enhance water efficiency, reduce water waste, and improve crop yield.The system utilizes soil moisture sensors to measure real-time soil moisture levels and collects weather data from external sources. These inputs are processed and analyzed using data analytics techniques to predict crop water requirements based on specific crop information and growth stages. An automated drip irrigation system, controlled by IoT devices, delivers water directly to the plant's root zones based on the predicted water requirements.The project's objectives include evaluating the accuracy of crop water requirement predictions, assessing water savings achieved compared to traditional irrigation methods, and monitoring crop health and yield. The collected data is analyzed to gain insights into irrigation strategies, weather conditions, and resource optimization. The user interface provides a convenient way for farmers to monitor and control the system, ensuring an asvaluable tool for enhancing driver safety.

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