Sudan Jha, PhD – Department of Computer Science and Engineering, Kathmandu University, Kavre, Nepal
Sarbagya Ratna Shakya, PhD – Department of Mathematical Sciences, Eastern New Mexico University, NM, USA
Sultan Ahmad, PhD – Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Alkharj, Saudi Arabia
Suman Thapaliya – Texas International College, Hadigaun, Kathmandu, Nepal

Series: Computer Science, Technology and Applications; Internet Theory, Technology and Applications
BISAC: COM004000; COM095000
DOI: https://doi.org/10.52305/SBJV7733

Book Reviews
“A masterclass in the convergence of Edge AI and healthcare. This volume provides the exact technical roadmap needed to bring high-tech diagnostics to low-resource settings. A must-read for digital health architects.” – Professor Dr. Deepak Prashar

“By tackling the triple challenge of connectivity, privacy, and latency, Jha and his colleagues have curated a collection that is as ethically grounded as it is technically sophisticated.” – Dr. Mohammad Khalid Imam Rahmani, College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia; Senior IEEE member

“Finally, a volume that treats ‘inclusivity’ as a technical requirement rather than just a social goal. Dr. Sudan Jha and his colleagues provide a groundbreaking roadmap for decentralizing healthcare, proving that the most advanced Edge AI and privacy protocols can—and should—be deployed in the world’s most resource-constrained environments. This is a seminal work for anyone committed to the democratization of digital health.” – Dr. Amin ul Haq, TeCIP Institute Scoula Superiore Sant’Anna (SSSA), Pisa, Italy

Book Description
This book presents a comprehensive and technically rigorous exploration of how intelligent, secure, and distributed technologies can transform healthcare delivery in rural and resource-constrained environments. In response to the growing global demand for equitable access to healthcare, this volume focuses on the integration of edge computing, low-power wide-area networks (LPWAN), and privacy-preserving artificial intelligence (AI) to build decentralized, scalable, and sustainable health-monitoring infrastructures. The book is structured around three core technological pillars. First, edge computing enables data processing at or near the point of collection—such as wearable devices, mobile health kiosks, and remote diagnostic units—thereby reducing latency, minimizing dependence on cloud connectivity, and lowering energy consumption. Second, LPWAN technologies, including LoRaWAN and NB-IoT, are presented as essential communication backbones that provide long-range, energy-efficient connectivity in geographically remote and infrastructure-limited settings. Third, privacy-preserving AI methods, such as federated learning and differential privacy, are examined in depth to ensure secure, compliant, and trustworthy handling of sensitive healthcare data. Through detailed case studies, the book demonstrates real-world deployments of these technologies, including solar-powered smart health kiosks for remote diagnostics, wearable sensors with on-device AI for continuous patient monitoring, and federated learning frameworks that enable cross-institutional collaboration without exposing patient data. These examples illustrate how decentralized and AI-driven systems can significantly improve early diagnosis, chronic disease management, and emergency response, even in environments characterized by limited connectivity, unreliable power supply, and shortages of healthcare professionals. Beyond implementation, the book critically addresses the practical and policy challenges associated with deploying such systems, including technical literacy, infrastructure investment, interoperability, data governance, and regulatory compliance. It emphasizes the need for solutions that are ethically grounded, locally maintainable, and adaptable to diverse socio-technical and cultural contexts.

Ultimately, this volume comprises 13 chapters contributed by 35 authors from diverse geographical regions across all continents. It serves as a strategic roadmap for researchers, engineers, healthcare practitioners, and policymakers seeking to design and deploy inclusive and intelligent healthcare systems. By integrating cutting-edge research with practical deployment frameworks, the book bridges the gap between technological innovation and real-world healthcare impact, advancing the goal of equitable and accessible care for all.