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Titlebook: IoT and AI in Agriculture; Smart Automation Sys Tofael Ahamed Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive li

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發(fā)表于 2025-3-21 19:50:21 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱IoT and AI in Agriculture
副標(biāo)題Smart Automation Sys
編輯Tofael Ahamed
視頻videohttp://file.papertrans.cn/476/475104/475104.mp4
概述Covers technologies & techniques such as IoT, AI, and ML in smart agriculture development from field to orchard crops.Elaborates on different type of hardware, platforms, and machine learning techniqu
圖書封面Titlebook: IoT and AI in Agriculture; Smart Automation Sys Tofael Ahamed Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive li
描述.This book covers smart agricultural space and its further development with an emphasis on ultra-saving labor shortages using AI-based technologies. A transboundary approach, as well as artificial intelligence (AI) and big data for bioinformatics, are required to increase timeliness and supplement the labor shortages, ensure the safety of intangible labor migration system to achieve one of the sustainable development goals (SDG) to secure food security (Society 5.0, SDG 1 and 2). With this in mind, the book focuses on the solution through smart Internet of Things (IoT) and AI-based agriculture, such as automation navigation, insect infestation, and decreasing agricultural inputs such as water and fertilizer, to maintain food security while ensuring environmental sustainability. Readers will gain a solid foundation for developing new knowledge through the in-depth research and education orientation of the book on how the deployment of outdoor and indoor sensors, AI/machine learning (ML), and IoT setups for sensing, tracking, collection, processing, and storing information over cloud platforms is nurturing and driving the pace of smart agriculture outdoor and indoors at this current
出版日期Book 2024
關(guān)鍵詞Smart agriculture; Deep learning; Smart horticultural crop management; Digital agriculture; Data driven
版次1
doihttps://doi.org/10.1007/978-981-97-1263-2
isbn_softcover978-981-97-1265-6
isbn_ebook978-981-97-1263-2
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Revolutionizing Agriculture: Embracing Modern Strategies for the Management of Coffee Leaf Rust Dis. This chapter highlights the transformative potential of deep learning in detecting coffee leaf rust in the fight against coffee leaf rust disease, which can offer a ray of hope for the advanced management of coffee leaf rust in the future.
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t type of hardware, platforms, and machine learning techniqu.This book covers smart agricultural space and its further development with an emphasis on ultra-saving labor shortages using AI-based technologies. A transboundary approach, as well as artificial intelligence (AI) and big data for bioinfor
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Book 2024 transboundary approach, as well as artificial intelligence (AI) and big data for bioinformatics, are required to increase timeliness and supplement the labor shortages, ensure the safety of intangible labor migration system to achieve one of the sustainable development goals (SDG) to secure food se
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