AI-Driven Edge Intelligence for Smart Cities, Healthcare, and Autonomous Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 April 2026 | Viewed by 171
Special Issue Editors
Interests: AI-driven edge computing; smart cities; healthcare informatics; autonomous systems; spatio-temporal analytics; federated learning; fog and cloud-edge collaboration; sustainable computing; intelligent transportation systems; real-time decision-making, cybersecurity and resilience
Interests: multi-robot/vehicle systems; multi-robot/vehicle task assignment; path planning; motion planning; operational research; heuristic algorithms; optimal control
Special Issue Information
Dear Colleagues,
The convergence of artificial intelligence (AI) and edge computing is reshaping the landscape of next-generation intelligent systems by enabling real-time, secure, and efficient data processing closer to data sources. Traditional cloud-centric solutions face limitations in terms of latency, scalability, privacy, and energy efficiency, which makes them less suitable for mission-critical applications in smart cities, healthcare, and autonomous systems. By integrating AI into edge and edge–cloud–fog ecosystems, researchers and practitioners can develop sustainable, adaptive, and context-aware solutions to address these challenges.
This Special Issue aims to gather cutting-edge research contributions on AI-driven edge intelligence that enhances decision-making, optimizes resource utilization, and supports resilient and secure infrastructures. In smart cities, AI-powered edge systems can revolutionize traffic management, energy distribution, and public safety. In healthcare, edge intelligence offers efficient diagnostics, continuous monitoring, and privacy-preserving solutions. For autonomous systems, it enables low-latency decision-making and real-time control in highly dynamic environments. We welcome original research articles, surveys, and case studies that explore novel algorithms, system architectures, optimization frameworks, and applications, with the ultimate goal of advancing intelligent, sustainable, and human-centric technologies.
Dr. Ahmad Ali
Dr. Xiaoshan Bai
Dr. Lanqing Yang
Guest Editors
Manuscript Submission Information
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Keywords
- AI-driven edge computing
- smart cities
- healthcare informatics
- autonomous systems
- spatio-temporal analytics
- federated learning
- fog and cloud-edge collaboration
- multi-robot system, sustainable computing
- intelligent transportation systems
- real-time decision-making, cybersecurity and resilience
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