*Title and abstracts due: 22 October 2018 (by email to
<[log in to unmask] <[log in to unmask]>>)Full Manuscripts due: 1
November 2018 (via submission site)Publication date: July-September 2019*

Recent years have seen an explosion in the use of data science and AI as a
central tenant in numerous computing applications, products, research, and
innovation. Examples of the success of data science abound - applying new
machine-learning techniques to problems such as vision and speech
recognition and translation has made commonplace levels of performance that
would have seemed impossible a few years ago.

In parallel, developments in pervasive computing are increasingly enabling
us to instrument our physical environment with complex sensors and
actuators and creating a connected world that generates huge volumes of
interconnected data. The importance of these trends can be seen in the
growing momentum of exemplars such as the Internet of Things (IoT), smart
environments and smart cities. These applications demand a new focus on how
we capture, process, and use data in pervasive environments.

Beyond the hype, it is clear to see how our world is genuinely becoming one
that is increasingly data-centric, in which both physical and electronic
services depend on the collection, analysis, and application of large
volumes of heterogeneous data.

This special issue focuses on work at the intersection of data science / AI
and pervasive computing. In particular, we solicit contributions that focus
on the following aspects of pervasive data science:

   - New hardware and software to support data collection in pervasive
   - Ownership, trust and provenance of pervasive data.
   - Privacy and consent in highly instrumented pervasive environments.
   - New techniques for data processing and inference in pervasive and IoT
   - Adaptation and optimization of g data processing algorithms for use on
   pervasive / IoT devices.
   - The use of data science and AI to support ubiquitous computing
   challenges such as localization and activity recognition.
   - Decision making and actuation based on data from pervasive and IoT
   - Application areas for data science and AI in pervasive computing and
   the IoT (e.g. autonomous vehicles, augmented cognition, smart cities and
   digital health).
   - Using pervasive data science and AI in robotics.

For examples of additional challenges in the field see "Pervasive Data
Science," in IEEE Pervasive Computing, vol. 16, no. 3, pp. 50-58, 2017.

The guest editors invite original and high-quality submissions addressing
all aspects of this field, as long as the connection to pervasive computing
and/or the Internet of Things is clear and central to the paper. Review or
summary articles — for example critical evaluations of the state of the
art, or an insightful analysis of established and upcoming technologies —
may be accepted 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 should include 250 words for
each table and figure. References should be limited to at most 15 citations
(30 for survey papers). Authors should use the magazine template
<http://ems.computer.org/public/files/template.dotx>for submission (see

Note that the magazine 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 are, e.g., hardware design, sensor networks, mobile systems,
human-computer interaction, industrial design, machine learning, data
science, but also societal issues including privacy and ethics. Simply
select the “Regular” option when submitting at the submission site
<https://mc.manuscriptcentral.com/pc-cs> (no need for prior abstract by

*Special Issue Guest Editors:*

   - Nigel Davies, Lancaster University, UK
   - Nic Lane, Oxford University, UK
   - Mirco Musolesi, University College London, UK

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