AI in agriculture: Smart greenhouses and indoor farming systems

Fuente: Zenodo
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Autor principal: Payili, Praveen
Formato: Recurso digital
Lenguaje:inglés
Publicado: Zenodo 2025
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author Payili, Praveen
author_facet Payili, Praveen
contents <p>This comprehensive article examines the transformative impact of artificial intelligence on modern indoor agriculture, focusing on key technological advancements in smart greenhouse management and controlled environment agriculture. The article explores critical areas, including precision environmental control, nutrient management in hydroponic systems, plant health monitoring and disease management, harvest optimization, quality control, and energy management with sustainability practices. AI-driven solutions have revolutionized traditional farming approaches by integrating deep learning algorithms, computer vision systems, and IoT sensor networks, enabling unprecedented levels of automation, resource efficiency, and crop yield optimization. Implementing these technologies has significantly improved agricultural metrics, from disease detection and prevention to harvest timing and quality assessment, while substantially reducing operational costs and environmental impact.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_16899609
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle AI in agriculture: Smart greenhouses and indoor farming systems
Payili, Praveen
Smart Agriculture
Artificial Intelligence
Controlled Environment Agriculture
Precision Farming
Agricultural Automation
<p>This comprehensive article examines the transformative impact of artificial intelligence on modern indoor agriculture, focusing on key technological advancements in smart greenhouse management and controlled environment agriculture. The article explores critical areas, including precision environmental control, nutrient management in hydroponic systems, plant health monitoring and disease management, harvest optimization, quality control, and energy management with sustainability practices. AI-driven solutions have revolutionized traditional farming approaches by integrating deep learning algorithms, computer vision systems, and IoT sensor networks, enabling unprecedented levels of automation, resource efficiency, and crop yield optimization. Implementing these technologies has significantly improved agricultural metrics, from disease detection and prevention to harvest timing and quality assessment, while substantially reducing operational costs and environmental impact.</p>
title AI in agriculture: Smart greenhouses and indoor farming systems
topic Smart Agriculture
Artificial Intelligence
Controlled Environment Agriculture
Precision Farming
Agricultural Automation
url https://doi.org/10.5281/zenodo.16899609