Enhancing Irrigation Efficiency through Machine Learning and IoT Integration

Year : 2024 | Volume : 15 | Issue : 03 | Page : 17 22
    By

    Meena Kumari,

  • Akshansh Mishra,

  • Aryan Vashisth,

  1. Assistant Professor, Department of Computer Science Engineering, ABES Institute of Technology, Ghaziabad, India
  2. Student, Department of Computer Science Engineering (AI), ABES Institute of Technology, Ghaziabad, India
  3. Student, Department of Computer Science Engineering (AI), ABES Institute of Technology,, Ghaziabad, India

Abstract

This study provides an integrated approach to enhance irrigation systems by fusing machine learning (ML) with Internet of Things (IoT) technologies. Agriculture is a major contributor to India’s economy, which is referred to as the backbone of the country. However, its production is highly dependent on several environmental and agronomic factors, with water being a critical resource. Irrigation consumes about 84% of the total available water in India; however, a significant portion is wasted due to poor management. We created a mechanism to automatically regulate water release valves based on the amount of soil moisture present in the crop’s root zone to overcome this difficulty. This system uses a predictive ML model that estimates more accurate irrigation durations. Furthermore, we integrated real-time soil sensors to collect critical data including nutrient level, pH, temperature, and rainfall, transmitting this information wirelessly to a mobile/web app. The app provides accurate real-time data and regulates valves to maintain optimal soil moisture levels. This innovative fusion of ML and IoT technologies empowers farmers with data-driven decision-making capabilities, ultimately leading to improved crop management and enhanced agricultural sustainability.

Keywords: Machine learning, internet of things, web app, automatic irrigation, soil moisture

[This article belongs to Journal of Electronic Design Technology ]

How to cite this article:
Meena Kumari, Akshansh Mishra, Aryan Vashisth. Enhancing Irrigation Efficiency through Machine Learning and IoT Integration. Journal of Electronic Design Technology. 2024; 15(03):17-22.
How to cite this URL:
Meena Kumari, Akshansh Mishra, Aryan Vashisth. Enhancing Irrigation Efficiency through Machine Learning and IoT Integration. Journal of Electronic Design Technology. 2024; 15(03):17-22. Available from: https://journals.stmjournals.com/joedt/article=2024/view=184086


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Regular Issue Subscription Original Research
Volume 15
Issue 03
Received 18/09/2024
Accepted 05/10/2024
Published 19/11/2024
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