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Elsevier

Machine Learning and Urban Health

Advancing Wellness through Data Analytics

  • 1st Edition - January 1, 2027
  • Latest edition
  • Editors: Deepak Kumar, Rajeev Ranjan, Juli Kumari, Mahesh Kumar Singh
  • Language: English

Data-Driven Sustainable Urban Health for Smart Cities explores how advanced data analytics and machine learning are reshaping the future of urban wellness. As cities worldw… Read more

Description

Data-Driven Sustainable Urban Health for Smart Cities explores how advanced data analytics and machine learning are reshaping the future of urban wellness. As cities worldwide evolve into highly interconnected, technology-driven spaces, new opportunities—and challenges—emerge for ensuring sustainable urban health. This timely volume addresses the critical question: how can we harness the power of data to improve health outcomes in complex urban environments? Traditional models of urban health management often fall short in the face of modern socio-environmental pressures and rapid urbanization. This book bridges that gap by presenting data science and artificial intelligence as essential tools for navigating the multifaceted nature of urban health. From predicting disease outbreaks to identifying vulnerable populations and optimizing resource allocation, the book highlights how machine learning is transforming the public health landscape. Drawing on real-world case studies and diverse datasets—including environmental sensors, population health indicators, and urban infrastructure metrics—the book provides actionable insights for researchers, policymakers, urban planners, and public health professionals. It emphasizes not only technical innovation but also the ethical and equitable use of health data to reduce disparities and enhance quality of life for all city residents. By integrating theory with application, Data-Driven Sustainable Urban Health for Smart Cities serves as both a foundational text and a visionary guide for building smarter, healthier, and more resilient urban communities in the 21st century.

Key features

  • Explores how data science and AI techniques can be applied to analyze complex urban health data, predict disease outbreaks, identify at-risk populations, and inform targeted public health interventions
  • Combines perspectives from public health, urban planning, environmental science, and data analytics, offering real-world case studies and actionable tools for policymakers, researchers, and practitioners
  • Highlights how data-driven insights can reduce health disparities, support ethical decision-making, and foster wellness in evolving smart city ecosystems

Readership

Researchers and Academicians in Public Health, Urban Planning, Environmental Science and Data Science. Policymakers and Government Officials in Urban Development and Health Infrastructure. As well as Urban Planners, Smart City Developers, Public Health Professionals, and Graduate Students

Table of contents

1. Introduction to Urban Health Challenges

2. Smart Cities: The Vision for Sustainable Urban Wellness

3. The Power of Data Analytics in Urban Health

4. Machine Learning: Revolutionizing Urban Health Insights

5. Case Studies: Real-World Applications in Urban Health Data Analysis

6. Sustainability and Health Equity in Urban Communities

7. Challenges and Ethical Considerations

8. Future Directions in Urban Health Data Analytics

9. Conclusion: Building Healthier, Smarter Cities Together

Product details

  • Edition: 1
  • Latest edition
  • Published: January 1, 2027
  • Language: English

About the editors

DK

Deepak Kumar

Dr. Deepak Kumar is a Research Scientist in the Atmospheric Sciences Group at Texas Tech University. He previously served as a Research Scientist at the Atmospheric Sciences Research Center, State University of New York at Albany, and as an Assistant Professor at Amity University, Delhi-NCR. His research focuses on geospatial sciences, computational sciences, climate change, sustainability, and the urban–climate–energy nexus. His work integrates remote sensing, geoinformatics, environmental studies, energy systems, urban weather, and climate modelling to support interdisciplinary research and policy applications. Dr. Kumar has experience in research design, data analysis, modelling, visualization, and implementation across environmental and climate-related projects. He also contributes to academic and professional activities through conference participation, outreach, training, and scholarly associations.

Affiliations and expertise
Research Scientist, Atmospheric Sciences Group, Department of Geosciences, Texas Tech University, Lubbock, TX, USA

RR

Rajeev Ranjan

Dr. Rajeev Ranjan is an Associate Professor, Department of Electronics and Communication Engineering at Chandigarh University in Punjab, India Dr. Ranjan received his B.Tech. degree in Electronics and Telecommunication Engineering from Biju Patnaik University of Technology, Odisha, India, an M.Tech. degree in Electronics and Communication Engineering from Jaypee Institute of Information Technology, Noida, India and a Ph.D. in Electronics and Communication Engineering from Thapar University, Punjab. He’s an active researcher in the field of Biomedical signal processing and image processing using machine learning. He has published over 25+ research papers in Web of Science/Scopus-indexed International Journals and Conferences by Elsevier, Springer, Taylor & Francis and IEEE. His current research interests include Biomedical signal processing, Image processing, Natural Language processing and Radar signal processing. He has organized and attended many Workshops, Seminars, FDP and National and International Conferences in India and given the expert talk in the various institutes of India.

Affiliations and expertise
Associate Professor, Chandigarh University, Punjab, India

JK

Juli Kumari

Juli Kumari is an academic research professional currently, pursuing a PhD in the Department of Computer Science and Engineering at Indira Gandhi Delhi Technical University for Women, New Delhi. She received her B.Tech. Degree in Information Technology from Biju Patnaik University of Technology, Odisha, an M.Sc. in Bioinformatics from Central University of South Bihar, Gaya, Bihar, and M.Tech. in Computer Science and Engineering from Indira Gandhi Delhi Technical University for Women, Kashmiri Gate, New Delhi. She’s an active researcher in the interdisciplinary fields of Artificial Intelligence, Machine Learning, and Health Informatics. She received a Project Grant for one year as a Women Scientist/PI in Bioinformatics from the Department of Science and Technology, Government of India. She has actively participated in expert talks and IEEE Women in Engineering Meet-and-Greet programs at various institutes across India. Her research interests span bioinformatics, health informatics, data mining, artificial intelligence, machine learning, and deep learning.
Affiliations and expertise
Senior Research Fellow, Indira Gandhi Delhi Technical University for Women, Delhi, India

MS

Mahesh Kumar Singh

Dr. Mahesh Kumar Singh is an Associate Professor in Department of ECE, Aditya University, India. Dr. Singh received his B.Tech. degree in Electronics and Communication Engineering from KNGD Modi Engineering College, Uttar Pradesh Technical University and an M.Tech. degree in Electronics and Communication Engineering from the Department of Electronics and Communication Engineering, Jaypee University of Engineering and Technology. He completed his PhD in Speech Signal Processing from Department of Electronics and Communication Engineering, Jaypee University of Engineering and Technology. He has been a reviewer for various research articles in diverse peer-reviewed journals and his involvement in the academic community is underscored by his participation in organizing and attending numerous workshops, seminars, Faculty Development Programs, as well as national and international conferences. He has Worked as Research Advisor, CL Educate Ltd. and worked as Assistant Professor in the Department of Electronics and Communication Engineering, Babu Banarsi Das Institute of Technology Delhi-NCR.

Affiliations and expertise
Associate Professor, Department of ECE, Aditya University, India