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024 7 _a10.1007/978-981-97-5878-4
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072 7 _aTEC003000
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245 1 0 _aArtificial Intelligence Techniques in Smart Agriculture
_h[electronic resource] /
_cedited by Siddharth Singh Chouhan, Akash Saxena, Uday Pratap Singh, Sanjeev Jain.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXXII, 287 p. 93 illus., 86 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
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347 _atext file
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505 0 _aChapter 1. Assessing the importance and need of Artificial Intelligence for Precision Agriculture -- Chapter 2. Challenges in Achieving Artificial Intelligence in Agriculture -- Chapter 3. Introduction to Artificial Intelligence techniques in Agricultural applications and their future aspects -- Chapter 4. Agricultural Artificial Intelligence: Obstacles and Opportunities -- Chapter 5. Smart Farming Management System: Pre and Post Production Interventions -- Chapter 6. Introduction to various intelligent devices and implementation platforms -- Chapter 7. Fruit Counting and Analysis Using Artificial Intelligence Approaches -- Chapter 8. Deep Learning-Based Plant Stress Diagnosis: An Optimized Generative Augmentation Model Approach -- Chapter 9. Transformative Impact of AI-Driven Computer Vision in Agriculture -- Chapter 10. An in-depth analysis of artificial intelligence-based crop pest management and water supply regulation -- Chapter 11. AI for Data-Driven Decision Making in Smart Agriculture: From Field to Farm Management -- Chapter 12. AI based Regulation of Water supply and Pest Management in Farming -- Chapter 13. Advancement and Challenges of Implementing Artificial Intelligence of Things in Precision Agriculture -- Chapter 14. Enabling Digital Platforms: Towards Smart Agriculture -- Chapter 15. IoT and Drone-Based Field Monitoring and Surveillance System -- Chapter 16. IoT based Real Time Farm Management System for Smart Agriculture.
520 _aThis edited volume explores the integration of artificial intelligence to improve crop production. It addresses the critical need for intelligent crop management in light of the world's escalating population. Encompassing a spectrum of technologies, including computer vision, image processing, soft computing, machine learning, and deep learning, the book explores advancements in decision-making systems. It integrates data science methodologies, Internet of Things, wireless communications, and a range of sensors and actuators to provide precise, timely, and cost-effective solutions to agricultural challenges, ultimately enhancing both the quality and quantity of crop yields. The book empowers its audience to direct their efforts towards designing models and prototypes that benefit society and the environment, making it an indispensable resource for those eager to shape the future of intelligent agriculture. It serves as a comprehensive guide for students, scholars, and academicians keen on delving into the transformative field of artificial intelligence in agriculture. Researchers, scientists, and field experts will find invaluable insights to guide their exploration and contribution to this domain.
650 0 _aAgriculture.
_968079
650 0 _aAgricultural biotechnology.
650 0 _aArtificial intelligence.
_958441
650 0 _aImage processing
_xDigital techniques.
_964228
650 0 _aComputer vision.
650 1 4 _aAgriculture.
_968079
650 2 4 _aAgricultural Biotechnology.
650 2 4 _aArtificial Intelligence.
_958441
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_965550
700 1 _aChouhan, Siddharth Singh.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
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700 1 _aSaxena, Akash.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
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700 1 _aSingh, Uday Pratap.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_973245
700 1 _aJain, Sanjeev.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_973246
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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856 4 0 _uhttps://doi.org/10.1007/978-981-97-5878-4
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