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Optimizing Greenhouse Conditions With Wireless Sensors and Machine Learning

Optimizing Greenhouse Conditions With Wireless Sensors and Machine Learning
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Author(s): Vasumathy M (Kingston Engineering College, Vellore, India), R. RoselinKiruba (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India)and J. Kavitha (Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India)
Copyright: 2026
Pages: 34
Source title: Optimizing Automation in Engineering With Energy Systems and Communication Networks
Source Author(s)/Editor(s): Vipin Balyan (Cape Peninsula University of Technology, South Africa), Tarun Varshney (Sharda University, India), Sandeep Gupta (Graphic Era University, India)and Gunjan Gupta (Cape Peninsula University of Technology, South Africa)
DOI: 10.4018/979-8-3373-2737-2.ch012

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Abstract

Traditional farming practices have increasingly given place to precision agriculture and IoT to bring in more efficient and sustainable crop management. The chapter deals with the development of an integrated framework for the optimization of the exploited greenhouse conditions using sensors and machine learning techniques for crop disease prediction and management. The proposed chapter presents a comprehensive framework for optimizing environments through the integration of sensors like temperature, humidity, soil moisture, CO2, and leaf wetness that has to be self-powered and battery-free and machine learning technologies. The purpose of the introduced framework is to provide an in-depth road map for combining advanced technology into agriculture and stimulating productive and sustainable farming practices. The framework is a significant milestone towards the future of precision agriculture that ensures economic stability and food security by using sensors and machine learning technologies.

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