Overview
- Presents heuristics and mathematical optimization techniques to address supply-chain and food production issues
- Introduces machine learning, artificial intelligence, and data science techniques
- Proposes macroeconomic and agricultural economics data science techniques to ensure small farms' economic sustainability
Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 331)
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Table of contents (11 chapters)
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Front Matter
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Introduction to Artificial Intelligence and Heuristics
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Front Matter
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Food Security Machine Learning and Heuristics Models
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Front Matter
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Back Matter
Keywords
About this book
This book introduces readers to advanced data science techniques for signal mining in connection with agriculture. It shows how to apply heuristic modeling to improve farm-level efficiency, and how to use sensors and data intelligence to provide closed-loop feedback, while also providing recommendation techniques that yield actionable insights.
The book also proposes certain macroeconomic pricing models, which data-mine macroeconomic signals and the influence of global economic trends on small-farm sustainability to provide actionable insights to farmers, helping them avoid financial disasters due to recurrent economic crises.
The book is intended to equip current and future software engineering teams and operations research experts with the skills and tools they need in order to fully utilize advanced data science, artificial intelligence, heuristics, and economic models to develop software capabilities that help to achieve sustained food security for future generations.
Authors and Affiliations
About the author
Chandrasekar Vuppalapati is a seasoned Software IT Executive with diverse experience in software technologies, enterprise software architectures, cloud computing, big data business analytics, internet of things (IoT), and software product and program management. He has held engineering and product leadership positions at Microsoft, GE Healthcare, Cisco Systems, St. Jude Medical, and Lucent Technologies. Chandrasekar has an MS in software engineering from San Jose State University (USA) and an MBA from Santa Clara University (USA) and currently teaches software engineering, large-scale analytics, data science, mobile computing, cloud technologies, and web and data mining at San Jose State University (USA).
Bibliographic Information
Book Title: Artificial Intelligence and Heuristics for Enhanced Food Security
Authors: Chandrasekar Vuppalapati
Series Title: International Series in Operations Research & Management Science
DOI: https://doi.org/10.1007/978-3-031-08743-1
Publisher: Springer Cham
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-031-08742-4Published: 17 September 2022
Softcover ISBN: 978-3-031-08745-5Published: 18 September 2023
eBook ISBN: 978-3-031-08743-1Published: 16 September 2022
Series ISSN: 0884-8289
Series E-ISSN: 2214-7934
Edition Number: 1
Number of Pages: XXX, 891
Number of Illustrations: 1 b/w illustrations
Topics: Operations Research/Decision Theory, Food Science, Artificial Intelligence, Optimization, Operations Management, Data Mining and Knowledge Discovery