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Title
Sensing, data managing, and control technologies for agricultural systems / Shaochun Ma, Tao Lin, Enrong Mao, Zhenghe Song, Kuan-Chong Ting, editors.
ISBN
9783031038341 (electronic bk.)
3031038347 (electronic bk.)
3031038339
9783031038334
Published
Cham, Switzerland : Springer, 2022.
Language
English
Description
1 online resource (1 volume) : illustrations (black and white, and color).
Item Number
10.1007/978-3-031-03834-1 doi
Call Number
S494.5.I5
Dewey Decimal Classification
338.1/6
Summary
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, and students in the field of sensing, control, and automation technologies for production agriculture.
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Source of Description
Description based on print version record.
Series
Agriculture automation and control.
Introduction : Overview of Sensing, data management, and control technologies for agricultural systems
Agricultural Internet of Things
Applied machine vision technologies in specialty crop production
Imaging Technology for High-Throughput Plant Phenotyping
Data-driven Modeling for Crop Growth in Plant factories
Data-driven modeling for crop mapping and yield estimation
Artificial Intelligence for Image Processing in Agriculture
Smart Farming Management
Emerging automated technologies on tractors
Applied time-frequency control in agricultural machines - Applied Unmanned Aerial Vehicle technologies: opportunities and constraints
Robotic Tree Fruit Harvesting: Status, Challenges, and Prosperities.
