Editors: Subhendu Kumar Pani, Suneeta Satpathy, Sachi Nandan Mohanty

Series Title: Applied Artificial Intelligence in Data Science, Cloud Computing and IoT Frameworks

AI and ML Solutions Driving Modern Farming and Urban Innovation

Volume 3

eBook: US $89 Special Offer (PDF + Printed Copy): US $143
Printed Copy: US $98
Library License: US $356
ISSN: 3029-2255 (Print)
ISSN: 3029-2247 (Online)
ISBN: 979-8-89881-211-9 (Print)
ISBN: 979-8-89881-210-2 (Online)
Year of Publication: 2025
DOI: 10.2174/97988988121021250301

Introduction

Advancing Intelligence: Exploring Smart Systems and Future Innovations with Machine Learning is a comprehensive volume collection examining how Artificial Intelligence (AI) and Machine Learning (ML) are reshaping industries, societies, and technologies worldwide. Written by global experts, the series combines theoretical foundations with practical applications, showcasing how intelligent systems address pressing challenges across healthcare, agriculture, urban development, business intelligence, and cybersecurity.

  • - Volume 2: Transformative Healthcare Solutions Powered by AI and ML investigates intelligent tools for precision medicine, medical informatics, wearable devices, and patient-centric care, demonstrating how AI enhances diagnosis and treatment outcomes.
  • - Volume 3: AI and ML Solutions Driving Modern Farming and Urban Innovation explores sustainable farming, smart agriculture, environmental monitoring, and intelligent city infrastructures for improved quality of life.
  • - Volume 4s: AI-Driven Competitive Intelligence and Next-Generation Security focuses on financial analytics, business intelligence, cybersecurity, and digital forensics, emphasizing strategies for resilience in a data-driven era.


Key Features

  • - Integrates AI and ML into healthcare, agriculture, urban, and business systems.
  • - Applies intelligent tools to improve diagnosis, sustainability, efficiency, and security.
  • - Analyzes case studies and global perspectives for real-world relevance.
  • - Explores future-ready innovations shaping intelligent, resilient ecosystems.
  • - Addresses both societal opportunities and technical challenges of AI adoption.

Readership:

Designed for researchers, academicians, graduate students, and professionals in AI, computer science, data science, and engineering, as well as practitioners in healthcare, agriculture, urban planning, business, and cybersecurity seeking actionable insights.

Foreword

In an era defined by technological convergence, Applied Artificial Intelligence in Data Science, Cloud Computing and IoT Frameworks: Volume 2 – AI and ML Solutions Driving Modern Farming and Urban Innovation emerges as a timely and visionary contribution to the global discourse on intelligent transformation. This volume arrives at a moment when Artificial Intelligence (AI) and Machine Learning (ML) have evolved beyond research laboratories to become foundational forces shaping industries, economies, and societies. Their integration with Cloud Computing and the Internet of Things (IoT) is driving unprecedented innovation, enabling sustainable solutions, and redefining the way humanity interacts with its environment.

The agricultural and urban sectors, in particular, lie at the heart of this transformation. Confronted by challenges such as food insecurity, climate change, urban congestion, and resource inefficiency, these domains demand solutions that blend intelligence with sustainability. AI-powered analytics, when coupled with the scalability of cloud infrastructures and the real-time responsiveness of IoT ecosystems, provide a powerful framework for addressing these issues. From precision agriculture that optimizes yield while conserving resources, to smart city systems that enhance mobility and reduce emissions, the innovations explored within this volume exemplify how data-driven intelligence can catalyze equitable and sustainable progress.

Distinguished by its synthesis of theoretical depth and practical insight, this book bridges the gap between conceptual understanding and real-world implementation. Each chapter presents rigorous analyses alongside applied frameworks, case studies, and experimental outcomes that illuminate the tangible impact of AI and ML technologies across rural and urban landscapes. By integrating cross-disciplinary perspectives, the volume offers researchers, practitioners, and policymakers a comprehensive guide to advancing smarter, greener, and more resilient ecosystems.

Beyond its technical merit, this volume stands as a reflection of collective human ingenuity directed toward the greater good. It envisions a future where innovation serves not only as a tool of progress but as a means of harmonizing technological advancement with environmental and societal well-being. The editors and contributors have assembled a body of work that captures both the promise and responsibility of intelligent systems in shaping the next era of sustainable development.

Shu Hu
School of Applied and Creative Computing
Director, Purdue Machine Learning and Media Forensics (M2) Lab
Purdue University