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001 9781003311782
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040 _aOCoLC-P
_beng
_erda
_epn
_cOCoLC-P
020 _a9781003311782
_q(electronic bk.)
020 _a1003311784
_q(electronic bk.)
020 _z9781032223575
020 _a9781000644333
_q(electronic bk. : PDF)
020 _a1000644332
_q(electronic bk. : PDF)
020 _z9781032318653
020 _a9781000644371
_q(electronic bk. : EPUB)
020 _a1000644375
_q(electronic bk. : EPUB)
024 7 _a10.1201/9781003311782
_2doi
035 _a(OCoLC)1336501251
035 _a(OCoLC-P)1336501251
050 4 _aS494.5.D3
072 7 _aCOM
_x004000
_2bisacsh
072 7 _aTEC
_x003000
_2bisacsh
072 7 _aCOM
_x095000
_2bisacsh
072 7 _aUYQ
_2bicssc
082 0 4 _a338.10285
_223/eng/20220722
245 0 0 _aArtificial Intelligence and Smart Agriculture Applications.
250 _aFirst edition.
264 1 _a[Place of publication not identified] :
_bAuerbach Publications,
_c2022.
300 _a1 online resource (xx, 335 pages).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
505 0 0 _g1. --
_tApplication of drone and sensors in advanced farming: the future smart farming technology --
_g2. --
_tDevelopment and research of a greenhouse monitoring system --
_g3. --
_tA cloud-computing model for implementing smart agriculture --
_g4. --
_tApplication of conversational artificial intelligence for farmer's advisory and communication --
_g5. -- The
_tuse of an intelligent fuzzy logic controller to predict the global warming effect on agriculture: the case of the chickpea cicer arietinum L. --
_g6. --
_tUsing machine learning algorithms for mapping soil macronutrient elements variability with digital environmental data in an alluvial plain --
_g7. -- A
_tsmart IoT framework for soil fertility enhancement assisted via deep neural networks --
_g8. --
_tPlant disease detection with the help of advanced imaging sensors --
_g9. --
_tArtificial intelligence-aided phenomics in high throughput stress phenotyping of plants --
_g10. --
_tPlant disease detection using hybrid deep learning architecture in smart agriculture application --
_g11. --
_tClassification of coffee leaf diseases through image processing techniques --
_g12. -- The
_tuse of artificial intelligence to model oil extraction yields from seeds and nuts --
_g13. --
_tApplications of artificial intelligence in pest management --
_g14. --
_tApplying clustering technique for rainfall received by different district of Maharashtra state --
_g15. --
_tPredicting rainfall for Aurangabad division of Maharashtra by applying auto-regressive moving average model (ARIMA) using Python programming.
520 _aAn essential resource work for understanding how to design and develop smart applications for present and future problems of the field of agriculture.-- Dr. Deepak Gupta, Maharaja Agrasen Institute of Technology, Delhi, India As a result of the advances in Artificial Intelligence (AI), many aspects of daily life have been transformed by smart digital technology. Advanced intelligent algorithms can provide powerful solutions to real-world problems. Smart applications have become commonplace. All areas of life are being changed by smart tools developed to deal with complex issues challenging both humanity and the earth. Artificial Intelligence and Smart Agriculture Applications presents the latest smart agriculture applications developed across the globe. It covers a broad array of solutions using data science and AI to attack problems facing agriculture worldwide. Features: Application of drones and sensors in advanced farming A cloud-computing model for implementing smart agriculture Conversational AI for farmer's advisory communications Intelligent fuzzy logic to predict global warming's effect on agriculture Machine learning algorithms for mapping soil macronutrient elements variability A smart IoT framework for soil fertility enhancement AI applications in pest management A model using Python for predicting rainfall The book examines not only present solutions but also potential future outcomes. It looks at the role of AI-based algorithms and the almost infinite combinations of variables for agricultural applications. Researchers, public and private sector representatives, agriculture scientists, and students can use this book to develop sustainable and solutions for smart agriculture. This book's findings are especially important as the planet is facing unprecedented environmental challenges from over-farming and climate change due to global warming.
588 _aOCLC-licensed vendor bibliographic record.
650 7 _aCOMPUTERS / Artificial Intelligence
_2bisacsh
650 7 _aTECHNOLOGY / Agriculture / General
_2bisacsh
650 0 _aAlternative agriculture.
650 0 _aAgricultural innovations.
650 0 _aArtificial intelligence
_xAgricultural applications.
700 1 _aKose, Utku,
_d1985-
_eeditor.
700 1 _aPrasath, V. B. Surya,
_eeditor.
700 1 _aMondal, M. Rubaiyat Hossain,
_eeditor.
700 1 _aPodder, Prajoy,
_eeditor.
700 1 _aBharati, Subrato,
_eeditor.
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781003311782
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999 _c5255
_d5255