IoT Based Hydroponics System Using Machine Learning

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Sonashree T R; Suprabha G; Vachanshree; Chaithra A; Dr. C S Kavithadevi

IoT Based Hydroponics System Using Machine Learning

Authors: Sonashree T R, Suprabha G, Vachanshree, Chaithra A, Dr. C S Kavithadevi

Unique Paper ID: 167923
Volume: 11
Issue: 4
PageNo: 824-827

Keywords: Hydroponics IoT ESP32 Machine Learning

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.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 4
PageNo: 824-827

IoT Based Hydroponics System Using Machine Learning

Available:https://ijirt.org/article?manuscript=167923

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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