Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{207605,
        author = {Mithilesh M. Wasu and Dr. Kishor M. Dhole and Sagar A. Durge},
        title = {Wireless Sensor Network Technologies for Intelligent Smart Irrigation},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {3},
        pages = {1787-1800},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207605},
        abstract = {Agriculture is experiencing a rapid digital transformation driven by increasing global food demand, climate variability, water scarcity, and the need for sustainable resource management. Conventional irrigation methods rely on fixed schedules and manual decision-making, resulting in significant water wastage, energy inefficiency, and reduced crop productivity. Precision agriculture introduced site-specific management through sensor technologies, while digital agriculture further integrated the Internet of Things (IoT), Cloud Computing, wireless communication, and Artificial Intelligence (AI) to enable data-driven farm management. Among these technologies, Wireless Sensor Networks (WSNs) have emerged as the primary infrastructure for real-time environmental monitoring by continuously collecting soil moisture, temperature, humidity, and other agronomic parameters. Cloud – IoT platforms facilitate large-scale data storage, analytics, and remote monitoring, whereas Reinforcement Learning (RL) enables autonomous irrigation scheduling through sequential decision-making based on dynamic environmental conditions.
This paper systematically examines the evolution from traditional agriculture to precision and digital agriculture before providing an in-depth analysis of WSN architectures, sensing technologies, and communication protocols for intelligent irrigation. The paper critically reviews recent literature, compares existing WSN and AI-based irrigation systems, identifies current technological limitations, and analyzes challenges related to it.},
        keywords = {Smart Irrigation, Wireless Sensor Networks, Internet of Things, Cloud Computing, Precision Agriculture, Digital Agriculture, Reinforcement Learning, Artificial Intelligence, Sustainable Agriculture, Water Resource Management.},
        month = {August},
        }