Copyright © 2025 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{167923,
        author = {Sonashree T R and Suprabha G and Vachanshree and Chaithra A and Dr. C S Kavithadevi},
        title = {IoT Based Hydroponics System Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {4},
        pages = {824-827},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=167923},
        abstract = {This project presents the development and implementation of an Internet of Things (IoT)-based 5 hydroponics system merged with machine learning algorithms. The apparatus point to optimize the growth conditions for plants by continuously monitoring and controlling various environmental requirements such as nutrient levels, pH, temperature, humidity, as well as light intensity Sensors deployed in the hydroponic setup collect real-time details, which is then examined using machine learning models to predict the optimal conditions for different growth stages of the plants. The system also features automated nutrient and water delivery mechanisms, give rise to found in contact with predictive insights to maintain ideal conditions. Additionally, the integration of IoT allows remote monitoring and control via a user-friendly interface, providing notifications and actionable insights to the user. This intelligent hydroponics system enhances crop yield, reduces resource wastage, and ensures sustainable agricultural practices, demonstrating a significant advancement in precision agriculture.},
        keywords = {Hydroponics, IoT, ESP32,Machine Learning},
        month = {September},
        }