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AI and Data Analytics in Precision Agriculture for Sustainable Development [Kõva köide]

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  • Formaat: Hardback, 352 pages, kõrgus x laius: 235x155 mm, 100 Illustrations, color; 9 Illustrations, black and white; XIII, 352 p. 109 illus., 100 illus. in color., 1 Hardback
  • Sari: Studies in Computational Intelligence 1215
  • Ilmumisaeg: 03-Jul-2025
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 303193086X
  • ISBN-13: 9783031930867
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  • Kõva köide
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  • Formaat: Hardback, 352 pages, kõrgus x laius: 235x155 mm, 100 Illustrations, color; 9 Illustrations, black and white; XIII, 352 p. 109 illus., 100 illus. in color., 1 Hardback
  • Sari: Studies in Computational Intelligence 1215
  • Ilmumisaeg: 03-Jul-2025
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 303193086X
  • ISBN-13: 9783031930867
Teised raamatud teemal:
This book offers a comprehensive analysis of artificial intelligence (AI) and data analytics in precision agriculture. The integration of technology in agriculture is revolutionizing traditional farming practices, paving the way for sustainability. Precision farming, powered by AI, IoT, and big data, optimizes resource use by enabling real-time monitoring of soil health, weather conditions, and crop growth. Automated irrigation systems and drones reduce water wastage and enhance productivity.



Biotechnology advances, such as genetically modified crops and CRISPR gene editing, improve yield, pest resistance, and climate adaptability. Vertical farming and hydroponics offer space-efficient solutions, minimizing land degradation and water consumption. Robotics and autonomous machinery streamline labor-intensive tasks, reducing reliance on chemical inputs.



Blockchain ensures transparency in the food supply chain, promoting fair trade and reducing food fraud. Renewable energy sources, like solar-powered farms, further lower agricultures carbon footprint. By adopting these innovations, farmers can produce more with fewer resources, ensuring food security while preserving the environment.



Embracing technology-driven agriculture is crucial for meeting global food demands sustainably, combating climate change, and fostering economic resilience in farming communities. The future of agriculture lies in intelligent, data-driven, and eco-friendly solutions that balance productivity with environmental stewardship.
Precision Agriculture for Sustainable Development: Concepts and
Applications.- AI4AI: Revolutionizing Agriculture with Artificial
Intelligence.- Evolving Role of Applied AI in Crop Farming.- Role of
Artificial Intelligence in Precision Farming.- Precision Agriculture: Fuzzy
Logic or Deep Neural Network Models for Robust Crop Disease Screening.-
Machine Learning Models for Crop Management.- Enhancing Agricultural Climate
Resilience through Machine Learning Models and Hyper-Parameter Tuning.-
Enhancing Crop Resilience to Climate Change with AI.- AI-Based Smart
Irrigation Systems for Water Conservation.- Sensor Technologies and
Blockchain Integration for Data-Driven Precision Agriculture.- Satellite
Imagery and GIS Applications in Precision Agriculture.- Leveraging GIS and
Remote Sensing for Agricultural Advancement and Economic Development.-
Projecting Ecological Footprint and Biocapacity: Insights into Sustainable
Agriculture and Development.- Projecting Ecological Footprint and
Biocapacity: Insights into Sustainable Agriculture and Development.-
Evaluating Sentinel-2 and Sentinel-1 for Land Use / Land Cover Classification
in a Rice-Producing Region of Uruguay.- Enhancing Potato Crop Health: A
CNN-Based System for Early   Detection of Early and Late Blight.- Development
of a Neutrosophic Set Theory based Feature Selection method for
Classification of Paddy Seed.- Optimizing Potato Crop Water Quality:  A
Comparative Analysis of Machine Learning Techniques and Gradient Boosting
Approaches.- EFFECTS OF THE FREQUENCY EMISSIONS OF THE Tadarita brasiliensis
SIMULATED USING ELECTRONIC DEVICE FOR REPELLING Copitarsia decolora
(Lepidoptera: Noctuidae) ADULTS.
Dr. Sita Rani works in the Department of Computer Science and Engineering at Guru Nanak Dev Engineering College, Ludhiana. She earned her Ph.D. in computer science and engineering from I.K. Gujral Punjab Technical University, Kapurthala, Punjab, in 2018.  She completed postdoc from Big Data Mining and Machine Learning Lab, South Ural State University, Russia, from May 2022 to August 2023. She has also completed post graduate certificate program in data science and machine learning from Indian Institute of Technology, Roorkee, in 2023. She has more than 20 years of academic and research experience during which she has worked at various designations like HoD, Training and Placement Officer, and Deputy Dean Research.  She is Active Member of ISTE, IEEE, and IAEngg.  She has been recognized in the top 2% scientists list published by Stanford University for the year 2024.  She is Receiver of ISTE Section Best Teacher Award- 2020.



Dr. Soumi Dutta is Associate Professor at Sister Nivedita University, India. She has completed her Ph.D. (CST), IIEST, Shibpur. She received her B.Tech. (IT) and M.Tech. (CSE) securing 1st position (Gold medallist), from MAKAUT. She is certified as Publons Academy Peer Reviewer, 2020, and Certified Microsoft Innovative Educator, 2020. Her research interests are data mining, information retrieval, online social media analysis, and image processing. She has published 51 conference and journal papers in Springer, IEEE, IGI Global, Taylor & Francis, etc. She has 17 books in Palgrave Macmillan, Springer, IET, and IGI Global. She is Peer Reviewer and TPC Member in different international journals. She was Editor in CIPR 2020, CIPR2019, IEMIS 2020, CIIR 2021, IEMIS 2018, IEMIS 2022, ICIDA 2022, ICIDA 2023, CIIR 2023 and special issues in IJWLTT. She has published 7 patents and 1 Copyright. She has one authored book in Elsevier. 



Dr. Álvaro Rocha holds the title of Honorary Professor. He is Professor of information systems at the University of LisbonISEG, Researcher at the ADVANCE (the ISEG Centre for Advanced Research in Management), and Collaborator Researcher at both LIACC (Laboratory of Artificial Intelligence and Computer Science) and CINTESIS (Center for Research in Health Technologies and Information Systems). His main research interests are maturity models, information systems quality, online service quality, requirements engineering, intelligent information systems, e-Government, e-Health, and information technology in education. He is also Vice-Chair of the IEEE Portugal Section Systems, Man, and Cybernetics Society Chapter and Founder and Editor-in-Chief of both following Scopus and/or WoS journals. Moreover, he has served as Vice-Chair of Experts for the European Commissions Horizon 2020 Program. In Google Scholar, he has an H5-Index = 36, having 5965 citations. He has 197 of his publications indexed in the Web of Science database (Core Collection).



Dr. Korhan Cengiz, Assoc. Prof., was born in Edirne, Turkey, in 1986. He received the B.Sc. degrees in electronics and communication engineering from Kocaeli University and business administration from Anadolu University, Turkey, in 2008 and 2009, respectively. He took his M.Sc. degree in electronics and communication engineering from Namik Kemal University, Turkey, in 2011, and the Ph.D. degree in electronics engineering from Kadir Has University, Turkey, in 2016. Since October 2023, he is at the world top 2% scientist list. Since March 2023, he has been Senior Researcher in the Department of Information Technologies, University of Hradec Kralove, Kralove, Czech Republic. Since September 2022, he has been Associate Professor in the Department of Computer Engineering, Istinye University, Istanbul, Turkey. Since April 2022, he has been Chair of the research committee of University of Fujairah, United Arab Emirates. He is Editor of more than 20 books.