Mohamed Abdel-Basset, Hossam Hawash, Laila Abdel-Fatah
Artificial Intelligence and Internet of Things in Smart Farming (eBook, PDF)
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Mohamed Abdel-Basset, Hossam Hawash, Laila Abdel-Fatah
Artificial Intelligence and Internet of Things in Smart Farming (eBook, PDF)
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This book provides a broad overview of the areas of AI that can be used for smart farming applications, either through successful engineering or ground-breaking research. Among them, the highlighted tactics are soil management, water management, crop management, livestock management, harvesting, and the integration of IoT in smart farming.
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This book provides a broad overview of the areas of AI that can be used for smart farming applications, either through successful engineering or ground-breaking research. Among them, the highlighted tactics are soil management, water management, crop management, livestock management, harvesting, and the integration of IoT in smart farming.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 314
- Erscheinungstermin: 1. April 2024
- Englisch
- ISBN-13: 9781003861850
- Artikelnr.: 69861789
- Verlag: Taylor & Francis
- Seitenzahl: 314
- Erscheinungstermin: 1. April 2024
- Englisch
- ISBN-13: 9781003861850
- Artikelnr.: 69861789
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Dr. Mohamed Abdel-Basset is an IEEE Senior Member. He received the B.Sc., M.Sc., and PhD degrees in operations research from the Faculty of Computers and Informatics, Zagazig University, Egypt. He is currently an Associate Professor, Head of department of computer science with the Faculty of Computers and Informatics, Zagazig University. He has published more than 400 articles in international journals and conference proceedings. He is working on the application of multi-objective and robust metaheuristic optimization techniques. His current research interests include optimization, machine learning, deep learning, artificial intelligence, operations research, data mining, computational intelligence, applied statistics, decision support systems, robust optimization, engineering optimization, multi-objective optimization, swarm intelligence, evolutionary algorithms, and artificial neural networks.
Dr. Laila Abdel-Fatah received her B.S. M.Sc. and PhD. degrees in information systems and decision support from the Faculty of Computers and Informatics, Zagazig University, Egypt. She is currently a Lecturer with the Faculty of Computers and Informatics at Zagazig University. Her research interests include computation intelligence (CI), fuzzy logic, artificial intelligence (AI), the Internet of Things (IoT), metaheuristic algorithms, geographic information systems (GIS), and spatial optimization.
Dr. Hossam Hawash is a senior researcher at Zagazig University, Faculty of Computers and Informatics, Department of Computer Science, Egypt. He obtained his bachelor's and master's degrees in computer science in 2012 and 2016, respectively, from the Faculty of Computers and Informatics, Department of Computer Science, Egypt. His area of interest includes computation intelligence, Optimization, machine learning, deep learning, artificial intelligence, fuzzy learning, explainable artificial intelligence, and the Internet of things.
Dr. Laila Abdel-Fatah received her B.S. M.Sc. and PhD. degrees in information systems and decision support from the Faculty of Computers and Informatics, Zagazig University, Egypt. She is currently a Lecturer with the Faculty of Computers and Informatics at Zagazig University. Her research interests include computation intelligence (CI), fuzzy logic, artificial intelligence (AI), the Internet of Things (IoT), metaheuristic algorithms, geographic information systems (GIS), and spatial optimization.
Dr. Hossam Hawash is a senior researcher at Zagazig University, Faculty of Computers and Informatics, Department of Computer Science, Egypt. He obtained his bachelor's and master's degrees in computer science in 2012 and 2016, respectively, from the Faculty of Computers and Informatics, Department of Computer Science, Egypt. His area of interest includes computation intelligence, Optimization, machine learning, deep learning, artificial intelligence, fuzzy learning, explainable artificial intelligence, and the Internet of things.
1. Introduction to Smart Farming. 2. Big Data in Smart Farming. 3.
Conceptualization of Machine Learning for Smart Farming. 4. From Field to
Database: Sensors, Data Collection, and Efficient Management in Smart
Farming. 5. Maximizing Yield, Minimizing Water: Machine Intelligence for
Precision Irrigation and Water Management. 6. Innovations in Livestock
Monitoring: A Machine Learning Journey. 7. Enhancing Crop Health with
Machine Learning: Disease and Weed Identification Strategies. 8. Automated
Harvesting and Robotics in Agriculture. 9. The Convergence of AI and IoT in
Smart Farming. 10. Toward Agriculture 5.0: The Convergence of Machine
Learning and Nanotechnology for Next-Generation Farming.
Conceptualization of Machine Learning for Smart Farming. 4. From Field to
Database: Sensors, Data Collection, and Efficient Management in Smart
Farming. 5. Maximizing Yield, Minimizing Water: Machine Intelligence for
Precision Irrigation and Water Management. 6. Innovations in Livestock
Monitoring: A Machine Learning Journey. 7. Enhancing Crop Health with
Machine Learning: Disease and Weed Identification Strategies. 8. Automated
Harvesting and Robotics in Agriculture. 9. The Convergence of AI and IoT in
Smart Farming. 10. Toward Agriculture 5.0: The Convergence of Machine
Learning and Nanotechnology for Next-Generation Farming.
1. Introduction to Smart Farming. 2. Big Data in Smart Farming. 3.
Conceptualization of Machine Learning for Smart Farming. 4. From Field to
Database: Sensors, Data Collection, and Efficient Management in Smart
Farming. 5. Maximizing Yield, Minimizing Water: Machine Intelligence for
Precision Irrigation and Water Management. 6. Innovations in Livestock
Monitoring: A Machine Learning Journey. 7. Enhancing Crop Health with
Machine Learning: Disease and Weed Identification Strategies. 8. Automated
Harvesting and Robotics in Agriculture. 9. The Convergence of AI and IoT in
Smart Farming. 10. Toward Agriculture 5.0: The Convergence of Machine
Learning and Nanotechnology for Next-Generation Farming.
Conceptualization of Machine Learning for Smart Farming. 4. From Field to
Database: Sensors, Data Collection, and Efficient Management in Smart
Farming. 5. Maximizing Yield, Minimizing Water: Machine Intelligence for
Precision Irrigation and Water Management. 6. Innovations in Livestock
Monitoring: A Machine Learning Journey. 7. Enhancing Crop Health with
Machine Learning: Disease and Weed Identification Strategies. 8. Automated
Harvesting and Robotics in Agriculture. 9. The Convergence of AI and IoT in
Smart Farming. 10. Toward Agriculture 5.0: The Convergence of Machine
Learning and Nanotechnology for Next-Generation Farming.