AI and Data Science-Driven Decision-Making for Resilient and Sustainable Agriculture - Rilegato

Rilegato

ISBN 13: 9798337399034

Casa editrice: Igi Global Scientific Publishing, 2026

Riassunto

The growing challenges of climate change, resource scarcity, population growth, and food security increase the need for innovative approaches to agricultural management and decision-making. Artificial intelligence (AI) and data science transform the agricultural sector by enabling data-driven insights, predictive analytics, and intelligent automation that support more resilient and sustainable farming practices. Through the integration of advanced technologies like machine learning, remote sensing, Internet of Things (IoT) devices, and big data analytics, organizations can make informed decisions that optimize productivity, reduce environmental impacts, and enhance resource efficiency. AI and data science-driven decision-making for sustainable agriculture reveals new methods, applications, and emerging trends that shape the future of smart, adaptive, and environmentally responsible agricultural systems. AI and Data Science-Driven Decision-Making for Resilient and Sustainable Agriculture explores how advanced AI and data science methodologies can support robust, transparent, and adaptive decision-making across agricultural systems facing increasing uncertainty and systemic stress. It covers foundational frameworks, advanced AI and statistical methods, multi-scale system integration, governance and resilience assessment, and real-world case studies. This book covers topics such as smart farming, data science, and supply chains, and is a useful resource for engineers, agriculturalists, academicians, researchers, and scientists.

Su questo libro

Informazioni sugli autori

Jorge Alberto Ruiz-Vanoye is a Professor and Researcher at Universidad Politécnica de Pachuca (UPP), a National Researcher under the Secretaria de Ciencia, Humanidades, Tecnología e Innovación program, and an Adjunct Researcher at the National Laboratory of Autonomous Vehicles and Exoskeletons (LANAVEX). Additionally, he holds the title of Lecturer-level Researcher for the Agency for the Quality of the University System of Catalonia (Generalitat de Catalunya). His research interests include Smart Cities, Smart Water, Smart Education, Smart Government, Smart Healthcare, Smart Farming, Smart Energy, Smart Sports, Smart Food, Smart Tourism, Algorithmic Finance, Algorithmic Portfolio Management, Applications and Theory of Algorithms, Bio-inspired Algorithms, Combinatorial Optimization Problems, Compilers, Computational Intelligence, Computational Complexity Theory, Computational Financial Intelligence, Complexity of Algorithms, Complexity of Instances, Computational Statistics, Computer Networks, Computer Science Security, Cybercrimes, Data Mining, Education, Evolutionary Computation, Heuristic Optimization Techniques in Bioinformatics, Hybrid Evolutionary Algorithms, Hybrid Optimization Algorithms, Machine Learning, Meta-heuristics, Operations Research, Operations Management, Parallel & Distributed Computing, Production Planning and Logistics Optimization, Project Scheduling Problems, Software Engineering, and Transgenic Algorithms.

Ocotlan Diaz-Parra is a Professor and Researcher at Universidad Politécnica de Pachuca (UPP), a National Researcher under the Secretaria de Ciencia, Humanidades, Tecnología e Innovación program, and an Adjunct Researcher at the National Laboratory of Autonomous Vehicles and Exoskeletons (LANAVEX). His research interests include Smart Cities, Smart Water, Smart Education, Smart Government, Smart Healthcare, Smart Farming, Smart Energy, Smart Sports, Smart Food, Smart Tourism, Algorithmic Finance, Algorithmic Portfolio Management, Applications and Theory of Algorithms, Bio-inspired Algorithms, Combinatorial Optimization Problems, Compilers, Computational Intelligence, Computational Complexity Theory, Computational Financial Intelligence, Complexity of Algorithms, Complexity of Instances, Computational Statistics, Computer Networks, Computer Science Security, Cybercrimes, Data Mining, Education, Evolutionary Computation, Heuristic Optimization Techniques in Bioinformatics, Hybrid Evolutionary Algorithms, Hybrid Optimization Algorithms, Machine Learning, Meta-heuristics, Operations Research, Operations Management, Parallel & Distributed Computing, Production Planning and Logistics Optimization, Project Scheduling Problems, Software Engineering, and Transgenic Algorithms.

Dettagli dell'edizione

• Editore: Igi Global Scientific Publishing
• Data di pubblicazione: 2026
• Lingua: Inglese
• ISBN 13: 9798337399034
• Rilegatura: Hardcover
• Numero di pagine: 554
• Redattore: Ruiz-Vanoye Jorge A, Diaz-Parra Ocotlan
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile