Authors:
Ukundabarezi Jean Methode

Addresses:
Department of Computer Science and Information Technology, Institut Supérieur de Technologie-Burkinafaso (IST Burkinafaso), Ouagadougou, Burkinafaso.

Abstract:

An IoT-based smart agriculture automatic irrigation system is a technologically advanced solution that enhances water efficiency in farming by leveraging Internet of Things (IoT) devices. The system integrates key components, including soil moisture sensors, weather stations, automated irrigation controls, remote monitoring, and data analytics, and supports integration with other systems. Its notable benefits include water conservation, improved crop yields, labour efficiency, and enhanced sustainability. This system finds applications in various agricultural settings, including field crops, greenhouses, and urban agriculture. As IoT technology continues to advance, agriculture is undergoing a significant transformation toward greater efficiency and sustainability. This paper introduces an innovative IoT-based smart irrigation system for agriculture that optimises water use, boosts crop productivity, and minimises manual labour. The system collects real-time soil moisture, weather, and crop health data from a network of sensors throughout agricultural areas. The system analyses this data to create exact watering schedules for each crop and field area using complex algorithms. The technology automates and optimises water distribution by using IoT-controlled actuators to provide the proper amount of water to crops at the right time. Water waste is reduced, and resource efficiency is improved. Farmers can also monitor and manage the system in real time using smartphone or computer interfaces.

Keywords: Internet of Things (IoT); Smart Agriculture; Automatic Irrigation; Soil Moisture; Crop Health; Real-Time Monitoring; Water Management; Resource Management.

Received on: 25/01/2025, Revised on: 04/04/2025, Accepted on: 14/06/2025, Published on: 07/12/2025

DOI: 10.69888/FTSIN.2025.000553

FMDB Transactions on Sustainable Intelligent Networks, 2025 Vol. 2 No. 4, Pages: 223-231

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