AI, Edge and IoT-based Smart Agriculture
- 1st Edition - November 10, 2021
- Latest edition
- Editors: Ajith Abraham, Sujata Dash, Joel J.P.C. Rodrigues, Biswaranjan Acharya, Subhendu Kumar Pani
- Language: English
AI, Edge, and IoT Smart Agriculture integrates applications of IoT, edge computing, and data analytics for sustainable agricultural development and introduces Edge of Thing-bas… Read more
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Description
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
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
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
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
Product details
- Edition: 1
- Latest edition
- Published: November 10, 2021
- Language: English
About the editors
About the editors
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Ajith Abraham
Ajith Abraham, PhD (2001) in artificial intelligence from Monash University, Australia, is the Vice Chancellor of Sai University, India. Prior to joining Sai University, he held senior positions at several prominent institutions and was the founding director of Machine Intelligence Research Labs, a nonprofit scientific network for innovation and research excellence headquartered in Seattle, United States. Dr. Abraham has led or co-led research projects valued at over $110 million, funded by organizations in the United States, the European Union, Italy, the Czech Republic, France, Malaysia, China, and Australia. He has worked in multidisciplinary environments for more than 35 years and is a prolific co-author of research publications in artificial intelligence and its industrial applications. Several of his works have been translated into Chinese and Russian, and one of his books has been translated into Japanese. Dr. Abraham is consistently featured in the Stanford/Elsevier list of the world’s top 2% most-cited scientists. From 2016 to 2021, he served as Editor-in-Chief of Engineering Applications of Artificial Intelligence (EAAI), one of the longest-standing journals in the field (founded in 1988). He has also served on the editorial boards of more than 15 international journals indexed by Thomson ISI.
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Sujata Dash
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Joel J.P.C. Rodrigues
Joel J.P.C. Rodrigues is affiliated with the Federal University of Piauí and serves as Leader of the Center for Intelligence at Fecomércio/CE, Brazil. He is a Highly Cited Researcher (Clarivate) and ranked no. 1 among computer science researchers in Brazil by Research.com. He is also the leader of the Next Generation Networks and Applications (NetGNA) research group (CNPq), a Member Representative of the IEEE Communications Society on the IEEE Biometrics Council, and President of the Scientific Council at ParkUrbis – Covilhã Science and Technology Park. Prof. Rodrigues has held several leadership roles within IEEE, including Director for Conference Development on the IEEE Communications Society (ComSoc) Board of Governors, IEEE Distinguished Lecturer, Technical Activities Committee Chair for the IEEE ComSoc Latin America Region, and Past Chair of the IEEE ComSoc Technical Committees on eHealth and Communications Software. He has also served as a Steering Committee member of the IEEE Life Sciences Technical Community and as Publications Co-Chair. He is Editor-in-Chief of the International Journal of E-Health and Medical Communications and serves on the editorial boards of several high-impact journals, primarily within IEEE. He has acted as General Chair and Technical Program Committee (TPC) Chair for numerous international conferences, including IEEE ICC, IEEE GLOBECOM, IEEE HEALTHCOM, and IEEE LatinCom. A very prolific author, he has received multiple Outstanding Leadership and Outstanding Service Awards from the IEEE Communications Society, along with several best paper awards. He is a member of the Internet Society, a Senior Member of ACM, and a Fellow of AAIA and IEEE.
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Biswaranjan Acharya
Biswaranjan Acharya received his MCA degree from IGNOU, New Delhi, India, in 2009, and his MTech degree in Computer Science and Engineering from Biju Patnaik University of Technology (BPUT), Rourkela, Odisha, India, in 2012. He earned his PhD in Computer Science from Veer Surendra Sai University of Technology (VSSUT), Burla, Odisha, India. He is currently an Associate Professor at the Jagadguru Kripalu Institute of Technology, Jagadguru Kripalu University, Cuttack, Odisha, India. He has over ten years of academic experience at reputed institutions, including Ravenshaw University and KIIT Deemed to be University, as well as industry experience as a software engineer.
Dr. Acharya is an active research article author for internationally recognized journals and holds over 50 patents. He also serves as a reviewer for several peer-reviewed journals. His research interests include multiprocessor scheduling, data analytics, computer vision, machine learning, and the Internet of Things. He is an active member of several professional and academic organizations, including IEEE, IACSIT, CSI, IAENG, and ISC.
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