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The intensifying global climate crisis presents one of the most urgent and complex challenges of our time, demanding coordinated action across scientific, technological, and policy domains. In this context, pervasive computing—with its ability to embed intelligent systems seamlessly into physical, social, and ecological environments—holds unique potential to support mitigation, adaptation, and resilience strategies at scale. From distributed sensing and intelligent infrastructure to real-time behavioral feedback and edge analytics, pervasive systems are increasingly positioned to shape environmental decision-making and foster sustainable practices across diverse sectors.
Recent advances in mobile, wearable, embedded, and ambient computing platforms have created unprecedented opportunities for scalable, in situ climate data collection, energy-aware system operation, low-power AI, and citizen engagement. At the same time, these advances raise pressing questions about environmental cost, sustainability-by-design, and the carbon footprint of pervasive technologies themselves. As the discipline evolves, it must critically examine its own role—not only in measuring and modeling the effects of climate change, but also in actively shaping socio-technical systems that support environmental responsibility.
This special issue invites contributions that explore the intersection of pervasive computing and climate challenges, including both applied innovations and reflective critiques. We seek work that addresses the design, deployment, and evaluation of pervasive systems in climate-relevant contexts, as well as studies that analyze the environmental implications of pervasive technology itself.
We invite original and high-quality submissions on topics including, but not limited to:
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.
For author information and guidelines on submission criteria, please visit the Author Information Page. Please submit papers through the IEEE Author Portal, and be sure to select the special-issue name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal. Abstracts should be sent by email to the guest editors directly.
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).
In addition to submitting your paper to IEEE Pervasive Computing, you are also encouraged to upload the data related to your paper to IEEE DataPort. IEEE DataPort is IEEE's data platform that supports the storage and publishing of datasets while also providing access to thousands of research datasets. Uploading your dataset to IEEE DataPort will strengthen your paper and will support research reproducibility. Your paper and the dataset can be linked, providing a good opportunity for you to increase the number of citations you receive. Data can be uploaded to IEEE DataPort prior to submitting your paper or concurrent with the paper submission. Thank you!
Contact the guest editors at pvc3-2026@computer.org
IEEE Pervasive Computing always welcomes submissions into its regular queue that cover the role of computing in the physical world – as characterized by visions such as the Internet of Things and ubiquitous computing. Topics of interest include hardware design, sensor networks, mobile systems, human-computer interaction, industrial design, machine learning, and data science, as well as societal issues including privacy and ethics. Please read the Author Information page before submitting. Simply select the “Regular” option when submitting at the submission site (submissions are possible at any time; no need for prior abstract by email).
