This book explains the best practices and their respective outcomes in artificial intelligence (AI) to meet sustainable development goals and demands. It examines the practices, technologies, and innovations at the core of various research issues to meet the sustainable development demands in agriculture to balance social, economic, and environmental sustainability with AI.
AI in Agriculture for Sustainable and Economic Management discusses AI-driven nanotechnology approaches for precision agriculture and solutions for the optimization of farming resources and their management. The authors examine the impact of AI in agriculture and how technology-driven sustainable farming with smart waste-water treatment for zero waste for the circular economy can extend crop shelf-life. It discusses how AI expertise can be advantageous to envisage and evaluate the increasing demands of productivity, and to help to maintain ecosystems and strengthen the capacity for crop adaptation in response to drastic changes in climate and weather, natural disasters, and other significant factors. These findings and practices are also useful to emphasize how an agricultural ecosystem can be advanced and industrialized so that it can aid not only large commercial farms but also smaller farmlands. Finally, it also discusses how AI practices will help to find a balance between the volume of food manufactured and the proper maintenance of the ecosystem.
This book is intended for researchers and upper graduate students interested in artificial intelligence in agricultural engineering, AI advances in crop science and technology for sustainable development.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für Beruf und Forschung
Professional Reference
Illustrationen
13 s/w Photographien bzw. Rasterbilder, 32 s/w Zeichnungen, 33 s/w Tabellen, 45 s/w Abbildungen
33 Tables, black and white; 32 Line drawings, black and white; 13 Halftones, black and white; 45 Illustrations, black and white
Maße
Höhe: 240 mm
Breite: 161 mm
Dicke: 18 mm
Gewicht
ISBN-13
978-1-032-58569-7 (9781032585697)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Dr. Sirisha Potluri is an Associate Professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Bowrampet, Hyderabad, Telangana, India. Her research areas include cloud Computing, Edge Computing, Artificial Intelligence and Data Analytics. She has more than 8 years of teaching experience in various subjects- Computer Programming using C, Python Programming, Data Structures, Core JAVA, Advanced JAVA, OOP using C++, Operating Systems, Distributed Operating System, Human Computer Interaction, C# and .NET Programming, Computer Graphics, Web Technology, UNIX Programming, Distributed and Cloud Computing, Data Mining and Warehousing, Scripting Languages, Database Management Systems, Software Engineering, and Software Process Management.
Dr. Suneeta Satpathy received her Ph.D. from Utkal University, Bhubaneswar, Odisha, in 2015, with Directorate of Forensic Sciences, MHA scholarship from Govt of India. She is currently working as an Associate Professor, Faculty of Emerging Technologies, SRI SRI University, Cuttack, Odisha. Her research interests include Computer Forensics, Cyber Security, Data Fusion, Data Mining, Big Data analysis, and Decision Mining.
Dr. Santi Swarup Basa received his Ph.D. degree from Maharaja Sriram Chandra Bhanjadeo University (Erstwhile North Orissa University), Baripada, Odisha, M.Tech (Comp.Sc.) from F.M.University, Balasore, Odisha and MCA from BPUT, Rourkela, Odisha. He is currently working as an Assistant Professor in the Department of Computer Science, MSCB University, Baripada, Odisha. His research interests include Software Engineering, Web Engineering, Data Mining, and Cloud Computing. He has 18 years of teaching experience. He is a life member of ISTE and ISC.
Dr. Antonio Zuorro is a Professor and Researcher at the Department of Chemical, Materials and Environmental Engineering of Sapienza - University of Rome, in the scientific disciplinary sector ING-IND / 24 (Principles of Chemical Engineering). He is also circular and bio-economy expert. He is also Dissemination and Exploitation Manager with expertise in organization and execution of communication plans and actions for the exploitation of bio-based results. He graduated in Chemical Engineering (BioChemical Engineering specialization) at the University of Rome "La Sapienza", later on he obtained, with "excellent" evaluation, the PhD in Chemical Engineering of the Environment and Safety.
Herausgeber*in
CE Bhubaneswar
1. Artificial Intelligence: Towards sustainable, smart, and green agriculture. 2. Artificial Intelligence in Achieving Sustainable Development Goals: Models and Approaches. 3. Smart Solutions for a Sustainable Future: Unlocking the Potential of AI for a Sustainable Future in Architecture, Energy, and Agriculture. 4. AI for Optimization of Farming Resources and their Management. 5. Democratising Intelligent Farming Solutions to Develop Sustainable Agricultural Practices. 6. AI- driven approach for Precision Agriculture. 7. Precision Agriculture and AI: Nurturing Sustainable Food Ecosystems. 8. Agriculture and AI: A Subtle Conjunction of Predictive Analysis and Voice Assistant in the World of Agriculture. 9. Machine Learning and IoT in Smart Agriculture. 10. Empowering Agriculture: IoT for Sustainable Farming Practices. 11. An Analysis Efficient Cloud Based Scheduling Infrastructure: Driving the Shift of Artificial Intelligence in Farming. 12. Animal Intrusion Detection System using Semantic Segmentation and YOLO V4 Object Detector. 13. Smart Farming for Sustainable Development -
A Study at Sonepur District of Odisha. 14. Analytical Approaches to Sustainable Farming Systems. 15. Is Ethiopia Coffee Cooperatives Farmers Proficient to Predict Capital Structure with Mediation of AI Based Knowledge Systems and Asset Liquidity?. 16. Is Marketing Intermediaries' Mediation required for Livestock and Products Marketing to uplift the Economic Status of Pastoralist Community in Ethiopia?.
