[Om-announce] CFP: IEEE TII Special Section on “Engineering Industrial Big Data Analytics Platforms for Internet of Things”

[Kuan-Ching Li]

[Please accept our apologies if you receive multiple copies of this Call
for Papers (CFP)]


CALL FOR PAPERS for
Special Section on “Engineering Industrial Big Data Analytics Platforms for
Internet of Things”
IEEE Transactions on Industrial Informatics


Over the last few years, a large number of Internet of Things (IoT)
solutions have come to the IoT marketplace. Typically, each of these IoT
solutions is designed to perform a single or minimal number of tasks
(primary usage). For example, a smart
sprinkler may only be activated if the soil moisture level goes below a
certain level in the garden. Further, smart plugs allow users to control
electronic appliances (including legacy appliances) remotely or create
automated schedules. Undoubtedly, such automation not only brings
convenience to their owners but also reduces resource wastage. However,
these IoT solutions act as independent systems. The data collected by each
of these solutions is used by them and stored in access-controlled silos.
After primary usage, data is either thrown away or locked down in
independent data silos. We believe a significant amount of knowledge and
insights are hidden in these data silos that can be used to improve our
lives; such data includes our behaviours, habits, preferences, life
patterns and resource consumption. To discover such knowledge, we need to
acquire and analyses this data together in a large scale. Typical data
analytics approaches are expected to facilitate process of inspecting,
cleaning, transforming, and modeling data with the goal of discovering
useful information, suggesting conclusions, and supporting decision-making.
Large scale data analysis is the process of applying data analysis
techniques to a large amount of data, typically in big data repositories.
Such large scale analysis requires specialized algorithms, systems and
processes to
be developed in order to review, analyze and present information in a form
that is more meaningful for organizations or end users. IoT middleware
platforms have been developed in both academic and industrial settings in
order to facilitate IoT data management tasks including data analytics.
However, engineering these general purpose industrial-grade big data
analytics platforms need to address many challenges as listed below to be
able to support data analytical needs in different types of IoT
applications.

This Special Section is focused on consolidating research efforts that aim
at engineering big data analytics platforms for Internet of Things
paradigms. Topics include, but are not limited to, the following research
topics and technologies:
 Big data analytics, new algorithms and approaches
 Privacy preserving data analysis
 Big data for urban informatics
 Internet of Things middleware platforms
 Engineering IoT systems
 Experience reports on software development challenges for the IoT and
takeaways;
 Software engineering challenges for mission-critical IoT systems;
 high reactivity, scalability, heterogeneity, configurability,
resource-constrained systems, and robustness;
 Software methods and development techniques for the IoT
 Industry grade tools, platforms, and environments for developing software
for the IoT
 Big data analytics software architectures
 Developing reusable analytics tools and frameworks
 Data analysis tools for developer community

Papers discussing new application areas and the resulting new developments
data analytics in Internet of Tings platforms are especially welcome.
Results obtained bysimulations must be validated in bounds by experiments
or analyticalresults.

*Manuscript Preparation and Submission
Follow the guidelines in “Information for Authors” in the IEEE Transaction
on Industrial Informaticshttp://tii.ieee-ies.org/
Please submit your manuscript in electronic form through Manuscript Central
web site: http://mc.manuscriptcentral.com/tii. On the submitting page #1 in
popup menu of manuscript type, select: "SS on Engineering Industrial Data
Analytics Platforms for Internet of Things"

Submissions to this Special Section must represent original material that
has been neither submitted to, nor published in, any other journal.
Extended versions of papers previously published in conference proceedings
may be eligible for consideration if conditions listed in
http://tii.ieee-ies.org/o/PC.pdf are fulfilled. Before submitting
manuscript check the review criteria (http://tii.ieee-ies.org/o/RC.pdf) and
other information(http://tii.ieee-ies.org/o/DI.pdf)

Note: The recommended papers for the section are subject to final approval
by the Editor-in-Chief. Some papers may be published outside the special
section, at the EIC discretion.

*Timetable:
Deadline for manuscript submissions March 1, 2017
Expected publication date (tentative) October 2017

*Guest Editors
Charith Perera [Coordinator]
Department of Computing, Faculty of Maths, Computing and Technology, Walton
Hall, Milton Keynes, United Kingdom charith.perera at ieee.org
Athanasios V. Vasilakos
Department of Computer Science, Electrical and Space Engineering, Luleå
University of Technology
Gul Calikli
Chalmers University of Technology, Gothenburg, Sweden
Quan Z. Sheng
School of Computer Science, University of Adelaide, Australia
Kuan-Ching Li
Dept. of Computer Science and Information Engineering (CSIE), Providence
University, Taiwan
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