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AI, Edge and IoT-based Smart Agriculture. Intelligent Data-Centric Systems

  • Book

  • November 2021
  • Elsevier Science and Technology
  • ID: 5230592

AI, Edge, and IoT Smart Agriculture integrates applications of IoT, edge computing, and data analytics for sustainable agricultural development and introduces Edge of Thing-based data analytics and IoT for predictability of crop, soil, and plant disease occurrence for improved sustainability and increased profitability. The book also addresses precision irrigation, precision horticulture, greenhouse IoT, livestock monitoring, IoT ecosystem for agriculture, mobile robot for precision agriculture, energy monitoring, storage management, and smart farming. The book provides an overarching focus on sustainable environment and sustainable economic development through smart and e-agriculture.

Providing a medium for the exchange of expertise and inspiration, contributions from both smart agriculture and data mining researchers around the world provide foundational insights. The book provides practical application opportunities for the resolution of real-world problems, including contributions from the data mining, data analytics, Edge of Things, and cloud research communities working in the farming production sector. The book offers broad coverage of the concepts, themes, and instruments of this important and evolving area of IOT-based agriculture, Edge of Things and cloud-based farming, Greenhouse IOT, mobile agriculture, sustainable agriculture, and big data analytics in agriculture toward smart farming.

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Table of Contents

1. Internet of things (IoT) and data analytics in smart agriculture: Benefits and challenges 2. Edge computing�- Foundations and applications 3. IoT-based fuzzy logic-controlled novel and multilingual mobile application for hydroponic farming 4. Functional framework for IoT-based agricultural system 5. Functional framework for edge-based agricultural system 6. Precision agriculture: Weather forecasting for future farming 7. Crop management system using IoT 8. Smart irrigation and crop security in agriculture using IoT 9. The Internet of Things in agriculture for sustainable rural development 10. Internet of Things (IoT) in agriculture toward urban greening 11. Smart e-agriculture monitoring systems 12.Smart agriculture using renewable energy and AI-powered IoT 13. Smart irrigation-based behavioral study of Moringa plant for growth monitoring in subtropical desert climatic condition 14. Surveying smart farming for smart cities 15. Farm Automation 16. A fog computing-based IoT framework for prediction of crop disease using big data analytics 17. Agribots: A gateway to the next revolution in agriculture 18. SAW: A real-time surveillance system at an agricultural warehouse using IoT 19. The predictive model to maintain pH levels in hydroponic systems 20. A crop-monitoring system using wireless sensor networking 21. Integration of RFID and sensors in agriculture using IOT 22. Prediction of crop yield and pest-disease infestation 23. Machine learning-based remote monitoring and predictive analytics system for crop and lives 24. Exploring performance and predictive analytics of agriculture data 25. Climate condition monitoring and automated systems 26. Decision-making system for crop selection based on soil 27. Cyberespionage: Socioeconomic implications on sustainable food security 28. Internet of Things on sustainable aquaculture system 29. IoT-based monitoring system for freshwater fish farming: Analysis and design 30. Transforming IoT in aquaculture: A cloud solution 31. Toward the design of an intelligent system for enhancing salt water shrimp production using fuzzy logic


Ajith Abraham Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, Auburn, WA, United States. Dr. Abraham is the Director of Machine Intelligence Research Labs (MIR Labs), a Not-for-Profit Scientific Network for Innovation and Research Excellence connecting Industry and Academia. The Network with HQ in Seattle, USA has currently more than 1,500 scientific members from over 105 countries. As an Investigator / Co-Investigator, he has won research grants worth over 100+ Million US$. Currently he works as a Professor of Artificial Intelligence in Innopolis University, Russia and is a Chairholder of the Yayasan Tun Ismail Mohamed Ali Professorial Chair in Artificial Intelligence of UCSI, Malaysia. Dr. Abraham works in a multi-disciplinary environment and he has authored / coauthored more than 1,400+ research publications out of which there are 100+ books covering various aspects of Computer Science. One of his books was translated to Japanese and few other articles were translated to Russian and Chinese. Dr. Abraham has more than 45,500+ academic citations (h-index of 100 as per google scholar). He has given more than 150 plenary lectures and conference tutorials (in 20+ countries). Since 2008, Dr. Abraham was the Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing (which has over 200+ members) during 2008-2021 and served as a Distinguished Lecturer of IEEE Computer Society representing Europe (2011-2013). Dr. Abraham was the editor-in-chief of Engineering Applications of Artificial Intelligence (EAAI) during 2016-2021 and is currently serving / served the editorial board of over 15 International Journals indexed by Thomson ISI. Dr. Abraham received Ph.D. degree in Computer Science from Monash University, Melbourne, Australia (2001) and a Master of Science Degree from Nanyang Technological University, Singapore (1998). Sujata Dash Department of Computer Application, Maharaja Srirama Chandra BhanjaDeo University (erstwhile North Orissa University), Baripada, Mayurbhanj, Odisha, India. Sujata Dash is Professor of Computer Science at North Orissa University in the Department of Computer Science, Baripada, India. She is a recipient of Titular Fellowship from Association of Commonwealth Universities, UK and was a visiting professor of Computer Science Department of University of Manitoba, Canada. She has published more than 160 technical papers as well as textbooks, monographs and edited books. She is a member of international professional associations and is a reviewer and editorial board member for multiple international journals. Her current research interest includes Machine Learning, Data Mining, Big Data Analytics, Bioinformatics, Fuzzy sets and systems, Rough sets, Soft Computing and Intelligent Agents. Joel J.P.C. Rodrigues Federal University of Piaui (UFPI), Teresina - PI, Brazil; Instituto de Telecomunicacoes, Portugal. Joel J. P. C. Rodrigues is a professor at the Federal University of Piau�, Brazil, and senior researcher at the Instituto de Telecomunica��es, Portugal. He is the leader of the Next Generation Networks and Applications (NetGNA) research group (CNPq), an IEEE Distinguished Lecturer, Member Representative of the IEEE Communications Society on the IEEE Biometrics Council, and the President of the scientific council at ParkUrbis - Covilh� Science and Technology Park. He has been general chair and TPC Chair of many international conferences, including IEEE ICC, IEEE GLOBECOM, IEEE HEALTHCOM, and IEEE LatinCom. He has authored or coauthored over 800 papers in refereed international journals and conferences, 3 books, 2 patents, and 1 ITU-T Recommendation. He had been awarded several Outstanding Leadership and Outstanding Service Awards by IEEE Communications Society and several best papers awards. Prof. Rodrigues is a member of the Internet Society, a senior member ACM, and Fellow of IEEE. Biswaranjan Acharya Department of Computer Science, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India. Biswa Ranjan Acharya is an academic currently associated with Kalinga Institute of Industrial Technology Deemed to be University along with pursuing PhD in computer application from Veer Surendra Sai University of Technology (VSSUT), Burla, Odisha, India. He received MCA in 2009 from IGNOU, New Delhi, India and M.Tech in Computer Science and Engineering in the year of 2012 from Biju Pattanaik University of Technology (BPUT), Odisha, India. He is also associated with various educational and research societies like IEEE, IACSIT, CSI, IAENG, and ISC. He has industry experience as a software engineer. He currently is working on research in multiprocessor scheduling along with fields such as Data Analytics, Computer Vision, Machine Learning and IOT. Subhendu Kumar Pani Krupajal Engineering College, Prashanti Vihar, Near CIFA, Kausalya Ganga, Bhubaneswar, Khordha, Odisha, India. Subhendu Kumar Pani received his Ph.D. from Utkal University Odisha, India. He has more than 16 years of teaching and research experience His research interests include data mining, big data analysis, web data analytics, fuzzy decision making and computational intelligence. He is a fellow in SSARSC and life member in IE, ISTE, ISCA, OBA.OMS, SMIACSIT, SMUACEE, CSI.