000 05378cam a2200649 i 4500
001 9781003508625
003 FlBoTFG
005 20251030122256.0
006 m o d
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008 240923t20252025flua ob 001 0 eng
040 _aOCoLC-P
_beng
_erda
_cOCoLC-P
020 _a9781003508625
_qelectronic book
020 _a1003508626
_qelectronic book
020 _a9781040269091
_qelectronic book
020 _a1040269095
_qelectronic book
020 _a9781040269053
_q(electronic bk. : PDF)
020 _a1040269052
_q(electronic bk. : PDF)
020 _z9781032832807
_qhardcover
020 _z9781032832821
_qpaperback
024 7 _a10.1201/9781003508625
_2doi
035 _a(OCoLC)1474345362
035 _a(OCoLC-P)1474345362
050 0 4 _aS494.5.D3
072 7 _aTEC
_x007000
_2bisacsh
072 7 _aTEC
_x008000
_2bisacsh
072 7 _aTEC
_x003070
_2bisacsh
072 7 _aTJFM
_2bicssc
245 0 0 _aSmart agriculture :
_bharnessing machine learning for crop management /
_cedited by Amol Dattatray Dhaygude, Suman Kumar Swarnkar, Priya Chugh, Yogesh Kumar Rathore.
250 _aFirst edition.
264 1 _aBoca Raton, FL :
_bCRC Press,
_c2025.
264 4 _c©2025
300 _a1 online resource (xiii, 167 pages) :
_billustrations.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aIntelligent Data-Driven Systems and Artificial Intelligence
505 0 0 _gChapter 1.
_tReviewing detection of plant disease by making use of machine learning mechanism --
_gChapter 2.
_tFuture prospects and challenges of digital transformation in agriculture and dairy industries mechanisms --
_gChapter 3.
_tInnovative IoT-driven solutions for real-time crop health surveillance and precision agriculture --
_gChapter 4.
_tOptimizing resource allocation in precision agriculture through the application of K-means clustering --
_gChapter 5.
_tUpholding ethical standards in modern agriculture: an examination of privacy-preserving machine learning techniques --
_gChapter 6.
_tExploring the effectiveness of decision trees for comprehensive detection of crop diseases in agricultural environments --
_gChapter 7.
_tIntegrating deep learning and image recognition in smart farming --
_gChapter 8.
_tExploring the effectiveness of decision trees for comprehensive detection of crop diseases in agricultural environments --
_gChapter 9.
_tEnhancing crop yield prediction accuracy through the application of gradient descent optimization algorithms --
_gChapter 10.
_tMachine learning models for early detection of pest infestation in crops: a comparative study
520 _a"This book, "Smart Agriculture: Harnessing Machine Learning for Crop Management," is a comprehensive guide designed to explore the various facets of integrating machine learning into agricultural practices. It aims to provide readers with a solid foundation in machine learning concepts while demonstrating their practical applications in real-world farming scenarios. It also examines the role of remote monitoring and precision agriculture, highlighting how technologies such as remote sensing and recurrent neural networks can optimize farming practices. This book: Emphasizes sustainable agricultural practices and data-driven decision-making for eco-friendly farming. Highlights the importance of using environmentally friendly practices, and how machine learning can play a pivotal role in achieving sustainability goals. Discusses topics such as crop optimization, disease detection, pest control, resource management, precision agriculture, and sustainability. Covers predictive analytics for weather forecasting, Internet of Things applications for precision agriculture, and the role of sensors in data collection. Illustrates optimizing resource allocation, irrigation with artificial intelligence, and machine learning for soil health assessment. Whether you are a researcher, a student, an agricultural professional, or a technology enthusiast, this book offers valuable insights into the transformative power of machine learning in agriculture. It invites readers to explore the potential of machine learning to transform farming practices, improve food security, and promote environmental sustainability"--
_cProvided by publisher.
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aArtificial intelligence
_xAgricultural applications.
_994195
650 0 _aMachine learning.
_955059
650 0 _aAgricultural informatics.
_995375
650 7 _aTECHNOLOGY / Electricity
_2bisacsh
_992937
650 7 _aTECHNOLOGY / Electronics / General
_2bisacsh
_992988
650 7 _aTECHNOLOGY / Agriculture / Sustainable Agriculture
_2bisacsh
_995005
700 1 _aDhaygude, Amol Dattatray,
_eeditor.
_995376
700 1 _aSwarnkar, Suman,
_eeditor.
_995000
700 1 _aChugh, Priya,
_eeditor.
_995377
700 1 _aKumar Rathore, Yogesh,
_eeditor.
_995378
830 0 _aIntelligent Data-Driven Systems and Artificial Intelligence.
_995379
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781003508625
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942 _cE-Books
999 _c68050
_d68050