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| 008 |
240403 ||| eng |
| 020 |
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|a 9783031511950
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| 100 |
1 |
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|a Balasubramanian, Sundaravadivazhagan
|e [editor]
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| 245 |
0 |
0 |
|a Intelligent Robots and Drones for Precision Agriculture
|h Elektronische Ressource
|c edited by Sundaravadivazhagan Balasubramanian, Gnanasankaran Natarajan, Pethuru Raj Chelliah
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| 250 |
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|a 1st ed. 2024
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| 260 |
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|a Cham
|b Springer Nature Switzerland
|c 2024, 2024
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| 300 |
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|a VIII, 479 p. 146 illus., 105 illus. in color
|b online resource
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| 505 |
0 |
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|a Introduction -- Intelligent computing with drones and robotics for Precision Agriculture -- Smart Farming and Precision Agriculture and Its Need in Today’s World -- Role of Machine Learning in Smart Farming and Its Applications -- Types of Soil Classification for the Identification of the Right Crop to be Cultivated -- Convergence of IoT, Big Data and Machine Learning for better yield Prediction in Smart Farming -- Soil Classification and Crop Prediction using Machine Learning Techniques -- Artificial Intelligence (AI) – enabled Drone Technology for Smart Farming -- Connected Drones for Smart Farming: The Use Cases and Challenges -- Drones and Robots in Smart Agriculture -- IoT-based Precision Agriculture and Crop Management using Machine Learning Approaches -- Smart Organic Agriculture in Traditional South Indian Based Farming System -- Crop and Fertilizer Recommendation System for Sustainable Agricultural Development -- The Role of Robotics and Drones in Precision Farming using Artificial Intelligence with an Automatic Learning Approach -- Applications of UAV-AD (Unmanned Aerial Vehicle-Agricultural Drones) in Precision Farming -- Machine Learning (ML) Algorithms on IoT and Drone Data for Smart Farming -- Recent improvements and major challenges in Digitized farming: A review -- A Comprehensive Review on the Internet of Things, 5G network, Drone Technologies for Smart Agriculture -- Internet of Things based Smart Agriculture Advisory System -- Conclusion
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| 653 |
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|a Control, Robotics, Automation
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| 653 |
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|a Control engineering
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| 653 |
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|a Telecommunication
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| 653 |
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|a Robotics
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| 653 |
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|a Communications Engineering, Networks
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| 653 |
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|a Agriculture
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| 653 |
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|a Automation
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| 700 |
1 |
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|a Natarajan, Gnanasankaran
|e [editor]
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| 700 |
1 |
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|a Chelliah, Pethuru Raj
|e [editor]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Signals and Communication Technology
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| 028 |
5 |
0 |
|a 10.1007/978-3-031-51195-0
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-031-51195-0?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 629.8
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| 520 |
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|a This book provides extensive information about smart farming, precision agriculture and the technologies that make them succeed. The authors provide detailed machine learning and deep learning models and algorithms that can be implemented effectively to improve smart farming methods. The authors also give elaborate information about the various IoT devices and types of drones that are used vastly in smart farming culture. The authors show specifically how methods and techniques used to improve the crop yield can be executed to help the farmers to improve the agricultural process and cultivation methods using a rule-based methodology. The purpose of this book is to articulate the need for processes, platforms, practices, patterns, and rules to be followed for the better yield of crop production and how IoT, robotics and drones can be used to improve the economy of the countries in the field of agriculture. In a nutshell, the book shows how the combination of multiple cutting-edge technologies leads to the realization of state-of-the-art infrastructures for next-generation agriculture. Provides insight on collecting and analyzing data using machine learning and deep learning methods for smart farming; Includes detail on how to use AI, IoT, drone technology and robotics effectively in smart farming; Details irrigation methods, soil classification, and prominent cultivation tools that can be improved using technology
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