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Titlebook: Sensing, Data Managing, and Control Technologies for Agricultural Systems; Shaochun Ma,Tao Lin,Kuan-Chong Ting Book 2022 The Editor(s) (if

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书目名称Sensing, Data Managing, and Control Technologies for Agricultural Systems
编辑Shaochun Ma,Tao Lin,Kuan-Chong Ting
视频video
概述Introduction to high-tech agriculture.Focus on Data utilization and decision-making for agriculture automation.In-depth review on the concept, principle, characteristic, applications of machine vision
丛书名称Agriculture Automation and Control
图书封面Titlebook: Sensing, Data Managing, and Control Technologies for Agricultural Systems;  Shaochun Ma,Tao Lin,Kuan-Chong Ting Book 2022 The Editor(s) (if
描述.Agricultural automation is the emerging technologies which heavily rely on computer-integrated management and advanced control systems. The tedious farming tasks had been taken over by agricultural machines in last century, in new millennium, computer-aided systems, automation, and robotics has been applied to precisely manage agricultural production system. With agricultural automation technologies, sustainable agriculture is being developed based on efficient use of land, increased conservation of water, fertilizer and energy resources. The agricultural automation technologies refer to related areas in sensing & perception, reasoning & learning, data communication, and task planning & execution. Since the literature on this diverse subject is widely scattered, it is necessary to review current status and capture the future challenges through a comprehensive monograph..In this book we focus on agricultural automation and provide critical reviews of advanced control technologies, their merits and limitations, application areas and research opportunities for further development. This collection thus serves as an authoritative treatise that can help researchers, engineers, educators
出版日期Book 2022
关键词agricultural automation; guidance and steering control; sensing and perception; Internet of Things; agri
版次1
doihttps://doi.org/10.1007/978-3-031-03834-1
isbn_softcover978-3-031-03836-5
isbn_ebook978-3-031-03834-1Series ISSN 2731-3492 Series E-ISSN 2731-3506
issn_series 2731-3492
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Agricultural Internet of Things,ich guides the development of agricultural informatization. Agricultural IoT has changed the traditional agricultural production methods and promoted the transformation of agriculture to digitalization and intelligence. This chapter analyzes the concept and technical system of agricultural IOT and s
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Data-Driven Modeling for Crop Growth in Plant Factories,mpletely insulated from the external climate and are able to precisely and automatically control internal environmental factors such as light, temperature, humidity, CO. concentration, and nutrient solution. In such intensive agricultural production systems, massive crop-related data have emerged fr
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Data-Driven Modeling for Crop Mapping and Yield Estimation, methods have succeeded in crop mapping and yield estimation, using a combination of multi-source training data and the application of advanced machine learning technologies. This chapter reviews various data-driven approaches that have been applied in crop mapping and yield estimation, with particu
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Artificial Intelligence for Image Processing in Agriculture,roduces fundamental concepts and the training of CNN models. This chapter also reviews the applications of using CNN in various agricultural tasks, e.g., crop growth monitoring in open field and greenhouse, wood and fish species identification, and activity monitoring for animals.
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