Información de la Revista

IEEE Pervasive Computing

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Factor de Impacto:
1.8
Editor:
IEEE
ISSN:
1536-1268
Vistas:
27461
Seguidores:
7

Solicitud de Artículos

IEEE Pervasive Computing is an academic journal published by IEEE. (ISSN 1536-1268, impact factor 1.8).

About IEEE Pervasive Computing IEEE Pervasive Computing explores the role of computing in the physical world–as characterized by visions such as the Internet of Things and ubiquitous computing. Designed for researchers, practitioners, and educators, this quarterly magazine acts as a catalyst for realizing the ideas described by Mark Weiser in 1988. The essence of this vision is the creation of environments saturated with sensing, computing, and wireless communication that gracefully support the needs of individuals and society. Many key building blocks for this vision are now viable commercial technologies: wearable and handheld computers, wireless networking, location sensing, Internet of Things platforms, and so on. However, the vision continues to present deep challenges for experts in areas such as hardware design, sensor networks, mobile systems, human-computer interaction, industrial design, machine learning, data science, and societal issues including privacy and ethics. Through special issues, the magazine explores applications in areas such as assisted living, automotive systems, cognitive assistance, hardware innovations, ICT4D, manufacturing, retail, smart cities, and sustainability. In addition, the magazine accepts peer-reviewed papers of wide interest under a general call, and also features regular columns on hot topics and interviews with luminaries in the field.
Última actualización por Dou Sun el

Special Issues

Special Issue on Revisiting Mobility Día de Entrega: 2026-10-01 Important Dates Title and abstracts due: 1 October 2026 (email to [email protected]) Full Manuscripts due: 8 October 2026 (via submission site) Publication: July - September 2027 Call for Papers Mobility is undergoing a profound transformation. Advances in sensing, connectivity, distributed intelligence, and automation are reshaping how people, goods, and services move through physical environments. From connected vehicles and autonomous drones to intelligent transport infrastructure and multimodal urban mobility platforms, transportation systems are becoming deeply intertwined with pervasive computing technologies. Today’s mobility ecosystems are no longer confined to isolated vehicles or static infrastructure. They are dynamic, data-rich, and context-aware environments where embedded intelligence supports real-time decision-making, adaptive routing, cooperative perception, and human–machine collaboration. Edge computing, sensor fusion, and AI-driven analytics are enabling vehicles and transport systems to operate with increasing autonomy, safety, and efficiency. At the same time, revisiting mobility through a pervasive computing lens raises fundamental challenges. Transport systems must operate under stringent constraints—low latency, high reliability, safety certification, cybersecurity resilience, and regulatory compliance—often in highly dynamic and adversarial conditions. The integration of pervasive intelligence into vehicles, drones, and infrastructure demands new architectures, verification frameworks, and interaction paradigms. This Special Issue invites contributions that critically examine the evolution of mobility systems through pervasive computing. We seek both technical innovations and reflective analyses that explore how distributed sensing, data-driven intelligence, and embedded computation are redefining transport across land, air, and urban spaces. We invite original and high-quality submissions addressing, but not limited to, the following topics: Sensing and Context-Awareness in Mobility Systems — real-time perception, multimodal sensing, cooperative awareness, traffic context modelling, environmental intelligence. Mobility data collection and fusion: Multi-source multi-granularity mobility data generated by different sensors like GNSS, WiFi, Bluetooth, LoRA; or from different transportation modes like bus, subway, bike. Edge Intelligence and Real-Time Decision Making — on-device AI, low-latency inference, adaptive routing, distributed learning, bandwidth-constrained optimisation. Distributed and Cooperative Mobility Systems — V2X communication, swarm coordination, fleet intelligence, collaborative perception, infrastructure–vehicle integration. Safety, Reliability, and Resilience — fault tolerance, safety certification, cybersecurity, adversarial robustness, real-time dependability. Human–Machine Interaction in Transport — shared autonomy, multimodal interfaces, situational awareness, trust calibration, human oversight. Data, Machine Intelligence, and Mobility Platforms — mobility data analytics, foundation models, federated learning, predictive modelling, privacy-preserving AI. Sustainability and Societal Impact — energy-efficient transport, inclusive mobility, urban resilience, ethical autonomy, regulatory frameworks. Case Studies and Real-World Deployments — smart cities, autonomous vehicles, drone ecosystems, logistics platforms, large-scale operational validation. We also welcome papers addressing any aspect of this field, provided that the connection to pervasive computing is central and clear. Review or summary articles offering critical evaluations of the state of the art or in-depth analyses of emerging technologies will also be considered if they demonstrate academic rigor and relevance. Articles submitted to IEEE Pervasive Computing should not exceed 6,000 words, including all text, the abstract, keywords, bibliography, biographies, and table text. The word count must include 250 words for each table and figure. References should be limited to at most 20 citations (40 for survey papers). Authors are encouraged, but not required, to use a template for submission (accepted articles will ultimately be typeset by magazine staff for publication). https://www.computer.org/digital-library/magazines/pc/cfp-revisiting-mobility
Última actualización por Dou Sun el

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