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.
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.
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
Dr. Ajith Abraham is a Pro Vice-Chancellor at Bennette University.
He is the director of Machine Intelligence Research Labs (MIR
Labs), Australia. MIR Labs are a not-for-profit scientific network
for innovation and research excellence connecting industry and
academia. His research focuses on real world problems in the fields
of machine intelligence, cyber-physical systems, Internet of
things, network security, sensor networks, Web intelligence, Web
services, and data mining. He is the Chair of the IEEE Systems Man
and Cybernetics Society Technical Committee on Soft Computing. He
is editor-in-chief of Engineering Applications of Artificial
Intelligence (EAAI) and serves on the editorial board of several
international journals. He received his PhD in Computer Science
from Monash University, Melbourne, Australia.
Sujata Dash holds the position of Professor at the Information
Technology School of Engineering and Technology, Nagaland
University, Dimapur Campus, Nagaland, India, bringing more than
three decades of dedicated service in teaching and mentoring
students. She has been honoured with the prestigious Titular
Fellowship from the Association of Commonwealth Universities,
United Kingdom. As a testament to her global contributions, she
served as a visiting professor in the Computer Science Department
at the University of Manitoba, Canada. With a prolific academic
record, she has authored over 200 technical papers published in
esteemed international journals, and conference proceedings, and
edited book chapters by reputed publishers Serving as a reviewer
and Associate Editor for approximately 15 international
journals.
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. 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. Dr.
Subhendu Kumar Pani received his Ph.D. from Utkal University,
Odisha, India in the year 2013. He is working as a professor at
Krupajal Engineering College under BPUT, Odisha, India. He has more
than 20 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 the recipient of 5 researcher awards. In addition to research,
he has guided two PhD students and 31 M. Tech students. He has
published 150 International Journal papers (100 Scopus index). His
professional activities include roles as Book Series Editor (CRC
Press, Apple Academic Press, Wiley-Scrivener), Associate Editor,
Editorial board member and/or reviewer of various International
Journals. He is an Associate with no. of the conference societies.
He has more than 250 international publications, 5 authored books,
25 edited and upcoming books; 40 book chapters into his account. He
is a fellow in SSARSC and a life member in IE, ISTE, ISCA, and
OBA.OMS, SMIACSIT, SMUACEE, CSI.
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