Iot-Based Smart Irrigation System Using Machine Learning · Electronic Theses and Dissertations

Author: Kapimbi Melisa
Title: Iot-Based Smart Irrigation System Using Machine Learning
Abstract: ABSTRACT
The efficient management of water resources in agriculture is critical for sustainable farming practices. This research project presents an innovative IoT-based smart irrigation system that leverages machine learning to optimize irrigation water needs. The system utilizes real-time data from humidity, temperature, and soil moisture sensors deployed in the field to predict water requirements. An Arduino Uno microcontroller acts as the brain of the system, collecting data from the sensors and transmitting it to the internet via a WIFI module. The collected data is then sent to a random forest algorithm, which predicts water needs and triggers the pump to automatically open or close. The system features a mobile application and web interface, providing farmers with real-time sensor data and pump status. Remote monitoring and automation enable efficient water usage, reduced energy consumption, and improved crop health. The results show a significant reduction in water usage and improved crop yields, making this system a valuable contribution to the development of sustainable agriculture practices. This research contributes to enhancing the accuracy and reliability of irrigation water demand forecasting. The developed model offers valuable insights for farmers, aiding in better water resource management and sustainable agricultural practices. The findings highlight the potential of machine learning in optimizing irrigation practices, leading to improved resource allocation and reduced water wastage in the agricultural sector.
Date: JUNE 2024
Publisher: BUSE
Keywords: management of water resources, innovative IoT-based smart irrigation system, Arduino Uno microcontroller.
Supervisor: Mr H Chikwiriro

Item sets: Department of Computer Science

Media: Kapimbi Melisa