Transforming Agriculture For The Digital Age Integrating Artificial Intelligence Cloud Computing And Big Data Solutions For Sustainable And Smart Farming Systems
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Transforming Agriculture for the Digital Age: Integrating Artificial Intelligence, Cloud Computing, and Big Data Solutions for Sustainable and Smart Farming Systems
Author: Sathya Kannan
language: en
Publisher: Deep Science Publishing
Release Date: 2025-06-06
Agriculture stands at the threshold of a digital transformation that promises to reshape how food is grown, managed, and distributed across the globe. Transforming Agriculture for the Digital Age: Integrating Artificial Intelligence, Cloud Computing, and Big Data Solutions for Sustainable and Smart Farming Systems delves into this pivotal shift, offering a comprehensive exploration of how emerging technologies are being harnessed to revolutionize the agricultural sector. In the face of mounting global challenges—including climate change, resource scarcity, population growth, and supply chain disruptions—traditional farming methods are no longer sufficient. The integration of Artificial Intelligence (AI), Cloud Computing, and Big Data offers powerful tools to optimize crop yields, enhance soil health, monitor weather patterns, reduce waste, and make farming more resilient and sustainable. This book is a reflection of the urgent need to modernize agriculture through precision and intelligence. Designed for agricultural scientists, technologists, policymakers, entrepreneurs, and students, this volume provides insights into the practical applications of smart farming technologies. It presents case studies, technological frameworks, and forward-looking strategies that demonstrate how data-driven decision-making is enabling real-time insights and automation across the agricultural value chain—from farm to fork. By examining innovations such as AI-powered crop monitoring, cloud-based farm management platforms, and predictive analytics for resource optimization, the book emphasizes a critical message: the future of agriculture is not only digital but also deeply sustainable and inclusive. It highlights the importance of bridging the digital divide and ensuring that smallholder and rural farmers also benefit from technological advancements. As we move into an era where food security, environmental sustainability, and technological innovation intersect, this book aims to serve as a foundational guide and an inspiration to those shaping the future of smart agriculture.
Ethical Considerations and Bias Detection in Artificial Intelligence/Machine Learning Applications
Author: Jayesh Rane
language: en
Publisher: Deep Science Publishing
Release Date: 2025-07-10
At a time when artificial intelligence (AI) and machine learning (ML) are used to make sensitive societal decisions such as the ones related to criminal justice, healthcare, finance, education, employment, algorithmic fairness and bias mitigation are among the most important but challenging issues at hand. The goal of this book is to provide a holistic view across various disciplines of the ethical base, detection methods, and technical measures for trustworthy AI systems. Starting from a solid foundation of statistical bias, transparency systems and fairness-aware ML models, this book methodically looks at state-of-the-art methodologies, where we highlight their shortcomings and introduce a unified model framework for detecting bias and transparent algorithms. Moving beyond technical diagnoses, it examines key sociotechnical and policy tools that are required to implement AI responsibly, providing guidance to researchers, engineers, policy makers, and organizational leaders. Literature review has been driven following the experimental case, the fairness trade-offs, intersectional bias, explainability and regulatory compliance are discussed in depth by the authors. This work underscores that fairness in automated decision-making systems depends not only on algorithmic accuracy, but also institutional will and stakeholder engagement. The chapters in this book function as both an academic primer and a resourceful handbook, transitioning readers through an ever-growing ethical AI terrain. Whether you are a data scientist building and deploying an algorithm that encourages ethical speech, or a regulator working to create and refine guidelines around such algorithms, this book provides you with both the tools and the understanding you need for ethical technology development and deployment.
Merging Artificial Intelligence With the Internet of Things
Artificial intelligence (AI) and the Internet of Things (IoT) converge to create smart, interconnected systems. This intelligent connectivity enhances the efficiency and innovation of the systems with greater automation, improved decision-making capabilities, and faster reaction times. By amplifying each other, they can transform engineering, security, and management in numerous settings. As a result, their blending is shaping the future of technology in smart cities, healthcare, agriculture, and other sectors. Merging Artificial Intelligence With the Internet of Things stimulates further research into AIoT applications and provides a robust framework for teaching the next generation of tech innovators. By presenting a blend of theoretical knowledge and practical case studies, it bridges the gap between academia and industry, encouraging interdisciplinary research and collaboration. Covering topics such as bio-inspired algorithms, clinical care, and food security, this book is an excellent resource for technology professionals, technology developers, industry leaders, policymakers, professionals, researchers, scholars, academicians, and more.