Smart Technologies for Sustainable Agriculture

Integrating Ecological Practices with Computational Intelligence
1. Auflage 2027
ISBN: 978-1-041-14153-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 360 Seiten, Format (B × H): 178 mm x 254 mm

Reihe: Computational Intelligence in Sustainable Agriculture

This book offers an in-depth analysis of technologically smart and sustainable agricultural systems, focusing on methods, tools, and practical applications that enhance ecological, social, and economic sustainability. It addresses pressing global challenges such as natural resource depletion, climate change, and growing food demand. The book covers agroecological practices, climate-smart agriculture, sustainable crop and livestock production, and strategies for biodiversity, soil health, and resource efficiency. It integrates advanced technologies, biotechnologies, renewable energy, policy frameworks, and financing models, supported by case studies from diverse global contexts.

- Comprehensive coverage of agroecology, climate-smart and regenerative agriculture methods, with detailed policy frameworks supporting sustainable agricultural transitions

- Analysis of socio-economic impacts, including rural livelihoods and food security

- Exploration of cutting-edge technologies and renewable energy in farming

- Practical case studies from developed and developing countries, insights into digital tools and precision farming techniques

- Focus on environmental sustainability, biodiversity, and resource management

This book is for scholars, students, practitioners seeking innovative farming methods, and policymakers developing green agriculture policies.

Zielgruppe

Academic

Autoren/Hrsg.

Shafik, Wasswa

Zakari, Rufai Yusuf

Kalinaki, Kassim

Tumuhimbise, Robooni

Haruna, Ahmed Abba

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Naturwissenschaften Agrarwissenschaften Agrarwissenschaften Nachhaltige Landwirtschaft
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik

Inhaltsverzeichnis

Part I: Foundations of Sustainable Agriculture 1. Concept and Perception of Sustainable Agricultural Systems 2. Theoretical Frameworks of Sustainable Agriculture 3. Computational Intelligence Techniques in Sustainable Agriculture Part II: Methods for Sustainable Agricultural Systems 4. Agroecological Practices for Sustainable Agriculture 5. Climate-Smart Agriculture 6. Sustainable Crop and Livestock Prediction Using Machine Learning Methods 7. Climate Change Adaptation and Mitigation Strategies in Agriculture 8. Predictive Modeling for Precision Agriculture Using AI and Data Analytics 9. Neural Networks in Forecasting Weather Impacts on Agriculture Part III: Tools and Technologies for Sustainable Agriculture 10. Precision Agriculture-Assisted Digital Tools and Technology Acceptance for Sustainable Agriculture 11. Biotechnologies for Sustainable Agriculture 12. Renewable Energy in the Agricultural Sector 13. Sustainable Water Management Tools 14. Machine Learning-Based Climate Resilience Forecasting for Sustainable Agriculture 15. Deep Learning for Automated Crop Health Monitoring Using Remote Sensing Part IV: Applications and Case Studies 16. Financing Sustainable Agriculture in Africa 17. Data Analytics for Enhancing Agricultural Supply Chains and Market Access in Africa 18. Machine Learning Models for Optimizing Crop Productivity in Sub-Saharan Africa 19. Improving Renewable Energy in Agriculture Through Circular Economy Approaches to Biomass Residue Valorisation 20. Systemic Barriers to Effective Agricultural Disaster Preparedness 21. Emerging Trends and Future Technologies in Sustainable Agriculture 22. Autonomous Targeted Spraying for Weed and Pest Control Using Machine Perception

Über Autor(innen)

Wasswa Shafik (born 23 May 1992) in Makindye, Kampala City, Uganda, is a Computer Scientist, Information Technologist, Founder, and Research Director at the Dig Connectivity Research Laboratory (DCRLab), Kampala, Uganda. He received his Bachelor’s in information technology engineering with a minor in mathematics at Ndejje University, Luweero, Uganda, and a Master’s in information technology engineering (communication and computer networks option) at Yazd University, Yazd, Islamic Republic of Iran. He pursued his PhD in digital science (computer science) at the School of Digital Science, Universiti Brunei Darussalam, Brunei Darussalam. His research broadly examines, integrates, and focuses on developing computationally and statistically efficient models and algorithms to address complex questions about artificial intelligence and machine learning problems. His specific research interests include sustainable development, smart agriculture, computer vision, ecological informatics, applied artificial intelligence, the Internet of Things, cybersecurity and privacy, and smart computing.

Rufai Yusuf Zakari is a member of the Nigeria Foundation for Artificial Intelligence (NFAI) and a distinguished data science researcher, technologist, and educator with over a decade of experience in both industry and academia. He earned his bachelor’s degree in computer science from Bayero University Kano and went on to obtain his master’s degree in computer science and engineering from Jodhpur National University. He obtained his PhD in Data Science from the School of Digital Science, Universiti Brunei Darussalam (UBD). Since 2016, Rufai has been a lecturer at the Kano State Polytechnic, where he has contributed significantly to the academic development of his students and the institution. He also serves as a lecturer at Skyline University Nigeria, within the Department of Computer Science. Rufai's areas of research encompass a broad range of topics, including Artificial Intelligence (AI) for Environmental Science, Data Analytics, Computer Vision, Machine Learning (ML)/Deep Learning (DL), Digital Image Processing, Remote Sensing, and Geographical Information Systems (GIS). His work often focuses on the intersection of AI and environmental issues, particularly in the application of advanced technologies to address challenges related to environmental science and climate change

Kassim Kalinaki (MIEEE) is a computer science researcher, technologist, and educator with more than ten years of experience in the industry and academia. He received his Diploma in Computer engineering from Kyambogo University, a BSc in computer science and engineering, a MSc. Computer Science and Engineering from Bangladesh's Islamic University of Technology (IUT), and a PhD in Computer Science at the School of Digital Science, Universiti Brunei Darussalam (UBD). Since 2014, He has lectured at the Islamic University in Uganda (IUIU), where he most recently served as the Head of Department Computer Science department (2019-2022). He’s the founder and principal investigator of Borderline Research Laboratory (BRLab) and his areas of research include Ecological Informatics, Data Analytics, Computer Vision, ML/DL, Digital Image Processing, Cybersecurity, IoT/AIoMT, Remote Sensing, and Educational Technologies.

Robooni Tumuhimbise is currently a Director of Research at the National Agricultural Research Organization (NARO), Rwebitaba Zonal Agricultural Research and Development Institute, Uganda. He is a result-oriented Crop Scientist with 15 years of experience in agricultural research and development, working on RTB crops, especially cassava, cocoyam, banana, and tea. After completing his PhD in Plant Breeding from the University of KwaZulu-Natal, South Africa, where his research was on cassava breeding for early storage root yield and resistance to viral diseases, he joined the National Banana Program of NARO, Uganda, as a banana Breeder. As a banana Breeder, he successfully led a research team of over 100 people that released five superior cooking banana varieties currently being promoted in East Africa. He has co-supervised over 15 postgraduate students and published over 40 articles in peer-reviewed journals.

Ahmed Abba Haruna is a distinguished educator, researcher, and leader in Information Technology. He holds Fellowships with the Higher Education Academy (FHEA), UK; the Federation of International Gender and Human Rights (FIGHR), USA; and the Institute of Management Consultants (FIMC). With over 12 years of experience teaching Computer Science and IT across Malaysia, Mauritius (UK University), Nigeria, and Saudi Arabia, Dr. Ahmed is currently an Assistant Professor of Computer Science at the University of Hafr Al Batin in Saudi Arabia. Dr. Ahmed earned his Ph.D. and M.Sc. in Information Technology from Universiti Teknologi PETRONAS, Malaysia, and a Bachelor’s in Information Technology from Infrastructure University Kuala Lumpur, Malaysia. He also holds a Postgraduate Certificate in Higher Education (PGCHE) from Middlesex University, UK. Internationally recognized.