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Subject:
From:
Alessandra De Paola <[log in to unmask]>
Reply To:
Alessandra De Paola <[log in to unmask]>
Date:
Wed, 21 Jun 2017 10:33:04 +0200
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Workshop on Data Fusion in the Internet of Things (DFIoT)

http://dfiot2017.nce.ufrj.br/

Co-located with IEEE 15th International Conference on Pervasive
Intelligence and
Computing – PICom 2017 (http://cse.stfx.ca/~picom2017/)
Orlando, USA

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CALL FOR PAPERS

The recent technological advances in computer and communication
technologies have been
fostering an enormous growth in the number of smart objects available for
usage. The
integration of these smart objects into the Internet originated the concept
of Internet of Things
(IoT). The IoT vision advocates a world of interconnected objects, capable
of being identified,
addressed, controlled, and accessed via the Internet. Such objects can
communicate with
each other, with other virtual resources available on the web, with
information systems and
human users. IoT applications involve interactions among several
heterogeneous devices,
most of them directly interacting with their physical surroundings.

New challenges emerge in this scenario as well as several opportunities to
be exploited. One
of such opportunities regards the leveraging of the massive amount of data
produced by the
widely-spread sensors to produce value-added information for the end users.
In this context,
techniques to promote knowledge discovery from the huge amount of sensing
data are
required to fully exploit the potential usage of the IoT devices. In this
context, data fusion
techniques are data techniques dealing with the association, correlation,
and combination of
data and information from single and multiple sources to achieve refined
position and identity
estimates, and complete and timely assessments of situations and threats,
and their
significance. Since IoT data is usually dynamic and heterogeneous, it
becomes important to
investigate techniques for understanding and resolving issues about data
fusion in IoT.
Employment of such Data fusion techniques are useful to reveal trends in
the sampled data,
uncover new patterns of monitored variables, make predictions, thus
improving decision
making process, reducing decisions response times, and enabling more
intelligent and
immediate situation awareness.

The goal of this Workshop is to present and discuss the recent advances in
the
interdisciplinary data fusion research areas applied to IoT. We aim to
bring together
specialists from academia and industry in different fields to discuss
further developments and
trends in the data fusion area.

Topics appropriate for this workshop include (but are not necessarily
limited to):

• Data collection and abstraction in IoT
• Knowledge fusion in IoT
• Machine learning, data mining and fusion for IoT
• Data streams fusion in IoT
• Data models for IoT
• Fusion models for IoT
• Subjective Logic applied to IoT
• Dynamic analysis in IoT
• Social data fusion and social IoT
• Probabilistic reasoning in IoT
• Decision systems in IoT
• Web data fusion
• Image Fusion
• Tracking

The submission dates are:

• Submission Due: 10 July 2017
• Author Notification: 10 August 2017
• Camera-ready Paper Due: 15 August 2017

Authors are invited to submit their original research work that has not
previously been
published or under review in any other venue. Papers should be prepared in
IEEE CS
Proceedings format and submitted via EDAS systems.
Research papers should explore a specific technology problem and propose a
complete
solution to it. Authors should submit 6 pages Research papers using IEEE
template. At least
one of the authors of any accepted paper is requested to register and
present the paper at
the conference.

Organizing Committee:

• Claudio M. de Farias – Federal University of Rio de Janeiro - Brazil
• Flávia C. Delicato – Federal University of Rio de Janeiro – Brazil
• Luci Pirmez – Federal University of Rio de Janeiro - Brazil

Program Committee:

• Atslands Rego – Federal University of Ceará – Brazil
• Danielo Gomes – Federal University of Ceará – Brazil
• Kevin Wang – The University of Auckland – New Zealand
• Rodrigo Pereira David – INMETRO – Brazil
• Antonio Balzanella – Dipartimento di Matematica e Fisica, Seconda
Universita degli
Studi di Napoli – Italy
• Celio Albuquerque – Fluminense Federal University – Brazil
• Haibo Zhang – University of Otago – New Zealand
• Paulo Pires – Federal University of Rio de Janeiro – Brazil
• Raquel A. F. Mini – PUC-Minas – Brazil
• Andre Aquino – Federal University of Alagoas – Brazil
• Wei Li – University of Sydney – Australia
• Antonio Guerrieri – ICAR – Italy
• Reyes Juarez Ramirez – University of Baja California – Mexico
• Jose Brancalion – Embraer – Brazil
• Andrea Omicini – University of Bolonha – Italy
• Flavio Mello – Federal University of Rio de Janeiro – Brazil
• Jonice Oliveira – Federal University of Rio de Janeiro – Brazil
• Jó Ueyama – University of São Paulo – Brazil
• Haibin Zhu – Nipissing University – Canada
• Raffaele Gravina – University of Calabria – Italy
• Arnoldo Diaz Ramirez – Instituto Tecnologico de Mexicali – Mexico
• Joni Amorim – University of Campinas – Brazil
• José Neuman – Federal University of Ceará – Brazil
• Alessandra De Paola – Università degli Studi di Palermo – Italy
• Florin Pop – University Politehnica of Bucharest / ICI Bucharest – Romenia
• Belur Dasarathy – Independent Consultant – USA
• Giancarlo Fortino – University of Calabria – Italy
• Priscila Machado Vieira Lima – Federal University of Rio de Janeiro –
Brazil
• Audun Josang – University of Oslo – Norway
• Francisco Herrera – University of Granada – Spain
• Adriana Vivácqua – Federal University of Rio de Janeiro – Brazil



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Alessandra De Paola - Ph.D.
DIID - Dipartimento dell'Innovazione Industriale e Digitale
Università degli Studi di Palermo
Viale delle Scienze, Edificio 6, 3° piano
90128 Palermo
phone: +39 091 238 62604
e-mail: [log in to unmask]

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