AI, Edge and IoT-based Smart Agriculture
View on ScienceDirect

AI, Edge and IoT-based Smart Agriculture

1st Edition - November 10, 2021

Write a review

  • Editors: Ajith Abraham, Sujata Dash, Joel J.P.C. Rodrigues, Biswaranjan Acharya, Subhendu Kumar Pani
  • eBook ISBN: 9780128236956
  • Paperback ISBN: 9780128236949

Purchase options

Purchase options
DRM-free (EPub, PDF)
eBook Format Help
Available
Sales tax will be calculated at check-out

Institutional Subscription

Support CenterReturns & Refunds
Free Global Shipping
No minimum order

Description

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.  

Key Features

  • Integrates sustainable agriculture, Greenhouse IOT, precision agriculture, crops monitoring, crops controlling to prediction, livestock monitoring, and farm management
  • Presents data mining techniques for precision agriculture, including weather prediction, plant disease prediction, and decision support for crop and soil selection
  • Promotes the importance and uses in managing the agro ecosystem for food security
  • Emphasizes low energy usage options for low cost and environmental sustainability

Readership

Researchers in various fields including computer science, researchers working in Agriculture domain, Application of IOT in agriculture, artificial intelligence, machine learning, image processing, agricultural big data analytics, smart agriculture, sustainable agriculture, e-agriculture, green IOT, agricultural supply chain. Graduates, post graduates and  researchers of Agricultural Engineering/ Computer Science/Mechanical Engineering

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

Product details

  • No. of pages: 574
  • Language: English
  • Copyright: © Academic Press 2021
  • Published: November 10, 2021
  • Imprint: Academic Press
  • eBook ISBN: 9780128236956
  • Paperback ISBN: 9780128236949

About the Editors

Ajith Abraham

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).

Affiliations and Expertise

Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, Auburn, WA, United States

Sujata Dash

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.

Affiliations and Expertise

Professor of Computer Science, Department of Computer Application, Maharaja Sriram Chandra Bhanj University (restwhile North Orissa University), Baripada, Mayurbhanj, Odisha, India

Joel J.P.C. Rodrigues

Joel J. P. C. Rodrigues is a professor at the Federal University of Piauí, Brazil, and senior researcher at the Instituto de Telecomunicações, 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 – Covilhã 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.

Affiliations and Expertise

Federal University of Piaui (UFPI), Teresina - PI, Brazil; Instituto de Telecomunicacoes, Portugal

Biswaranjan Acharya

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.

Affiliations and Expertise

Department of Computer Science, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India

Subhendu Kumar Pani

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.

Affiliations and Expertise

Krupajal Engineering College, Prashanti Vihar, Near CIFA, Kausalya Ganga, Bhubaneswar, Khordha, Odisha, India

Ratings and Reviews

Write a review

There are currently no reviews for "AI, Edge and IoT-based Smart Agriculture"