Artificial Intelligence and Heuristics for Enhanced Food Security

This book provides advanced data science techniques for signal mining in agriculture, focusing on heuristic modeling, sensors, data intelligence, and recommendation techniques to improve farm-level efficiency and provide actionable insights. It also proposes macroeconomic pricing models to help farmers avoid financial disasters.

Format: Hardback
Length: 891 pages
Publication date: 17 September 2022
Publisher: Springer International Publishing AG

This comprehensive book delves into advanced data science techniques, specifically focusing on their application in signal mining for agriculture. It offers insightful guidance on how to enhance farm-level efficiency through the use of heuristic modeling, leveraging sensors and data intelligence to provide closed-loop feedback, and employing recommendation techniques that yield actionable insights. Moreover, the book proposes macroeconomic pricing models that data-mine macroeconomic signals and the influence of global economic trends on small-farm sustainability, providing farmers with valuable actionable insights to help them navigate financial challenges caused by recurrent economic crises.

The primary objective of this book is to equip current and future software engineering teams and operations research experts with the necessary skills and tools to fully leverage advanced data science, artificial intelligence, heuristics, and economic models. By doing so, they can develop software capabilities that contribute to achieving sustained food security for future generations.

The book is organized into several chapters, each dedicated to exploring different aspects of advanced data science and its application in agriculture. The first chapter provides an introduction to the field, highlighting the importance of signal mining in agriculture and the challenges faced by farmers. The subsequent chapters delve into specific techniques, such as heuristic modeling, sensor data analysis, and recommendation systems, providing detailed explanations and practical examples.

One of the key strengths of the book is its emphasis on practical applications. It showcases real-world case studies and examples from various agricultural sectors, demonstrating how advanced data science techniques can be applied to improve farm productivity, reduce waste, and enhance sustainability. The authors also provide insights into the latest technological advancements, such as blockchain and machine learning, and their potential impact on agriculture.

Furthermore, the book addresses the challenges associated with implementing advanced data science techniques in agriculture. It discusses the need for interdisciplinary collaboration, data privacy and security concerns, and the importance of ethical considerations in data-driven decision-making. The authors offer practical solutions and recommendations to address these challenges, ensuring that the benefits of advanced data science are realized while minimizing potential risks.

In conclusion, this book is a valuable resource for software engineering teams, operations research experts, and anyone interested in leveraging advanced data science techniques for agriculture. It provides a comprehensive and practical guide to developing software capabilities that contribute to achieving sustained food security for future generations. By equipping readers with the skills and tools needed to fully utilize advanced data science, artificial intelligence, heuristics, and economic models, this book empowers them to make meaningful contributions to the field of agriculture.

Weight: 1544g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031087424
Edition number: 1st ed. 2022