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IoT-Integrated Machine Learning-Based Automated Precision Agriculture-Indoor Farming Techniques
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Author(s): Gowtham Rajendiran (Department of Computing Technologies, School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology, Chengalpattu, India)and Jebakumar Rethnaraj (Department of Computing Technologies, School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology, Chengalpattu, India)
Copyright: 2024
Pages: 29
Source title:
Using Traditional Design Methods to Enhance AI-Driven Decision Making
Source Author(s)/Editor(s): Tien V. T. Nguyen (Industrial University of Ho Chi Minh City, Vietnam)and Nhut T. M. Vo (National Kaohsiung University of Science and Technology, Taiwan)
DOI: 10.4018/979-8-3693-0639-0.ch013
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Abstract
Precision agriculture driven by the integration of the advanced technologies like internet of things (IoT) and machine learning (ML) is revolutionary precision agriculture, especially the indoor farming techniques. This chapter explores the comprehensive application of IoT and ML in automating indoor cultivation practices, examining their diverse benefits and practical uses in comparison with the traditional farming methodologies. IoT enables the indoor farmers to create controlled environments through interconnected sensors, monitoring crucial variables but not limited to temperature, humidity, and light intensity. Complemented by ML algorithms, data analysis becomes efficient, providing predictive models for crop growth, pest detection, and disease outbreaks. Automated environment climate control systems optimize resource utilization, while precision irrigation minimizes water usage. Real-time monitoring and early detection of plant health issues reduce crop losses, ensuring high-quality produce.
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