IoT-Based Adaptive Irrigation Solution for Smart Farming

Year : 2025 | Volume : 12 | Issue : 03 | Page : 17 24
    By

    Dattatray Suresh Gatkal,

  • Priti S Lahane,

  • Harshali Balwant Shewale,

  • Madhusudan Dnyaneshwar Pangarkar,

  1. Student, Dept. of Information Technology, Savitribai Phule Pune University, Pune, Maharashtra, India
  2. Student, Dept. of Information Technology, Savitribai Phule Pune University, Pune, Maharashtra, India
  3. Student, Dept. of Information Technology, Savitribai Phule Pune University, Pune, Maharashtra, India
  4. Student, Dept. of Information Technology, Savitribai Phule Pune University, Pune, Maharashtra, India

Abstract

Facing escalating global challenges such as water scarcity and unpredictable weather conditions, precision farming emerges as a crucial solution for enhancing agricultural productivity and sustainability. This paper introduces a smart irrigation system which employs IoT-based technology, integrating sensors and a designed to enhance water efficiency and boost agricultural productivity. The system leverages live data related to soil moisture and temperature, cloud cover, and precipitation, coupled with a cloud-based infrastructure using Firebase for data management and a Python Flask backend for processing. This enables comprehensive data collection and analysis, providing actionable insights for effective irrigation management. The implementation of the RF [Random Forest] algorithm for predictive analysis further refines the irrigation process, ensuring efficient water use while maintaining optimal soil conditions. Additionally, the system includes automated controls to manage irrigation events with minimal human intervention, yet allows for manual overrides in specific scenarios such as particular sprays or crop stages. This smart irrigation system not only caters to the current requirements of maximizing agricultural output but also supports long-term sustainability goals by mitigating resource depletion and supporting scalable agricultural practices.

Keywords: Precision Agriculture, Smart Irrigation Systems, Internet of Things (IoT), Water Resource Management, Sustainable Farming, Automated Irrigation Control, Real-Time Data Monitoring, Weather Forecasting Integration, Machine Learning in Agriculture, Soil Moisture Analysis.

[This article belongs to Journal of Microcontroller Engineering and Applications ]

How to cite this article:
Dattatray Suresh Gatkal, Priti S Lahane, Harshali Balwant Shewale, Madhusudan Dnyaneshwar Pangarkar. IoT-Based Adaptive Irrigation Solution for Smart Farming. Journal of Microcontroller Engineering and Applications. 2025; 12(03):17-24.
How to cite this URL:
Dattatray Suresh Gatkal, Priti S Lahane, Harshali Balwant Shewale, Madhusudan Dnyaneshwar Pangarkar. IoT-Based Adaptive Irrigation Solution for Smart Farming. Journal of Microcontroller Engineering and Applications. 2025; 12(03):17-24. Available from: https://journals.stmjournals.com/jomea/article=2025/view=228744


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Regular Issue Subscription Review Article
Volume 12
Issue 03
Received 17/05/2025
Accepted 05/08/2025
Published 06/10/2025
Publication Time 142 Days
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