-------- Weitergeleitete Nachricht -------- Betreff: [WI] DFIOT 2017 - Extended Deadline 10 Aug. 2017 Datum: Wed, 5 Jul 2017 18:58:43 +0200 Von: Alessandra De Paola alessandra.depaola@unipa.it Antwort an: Alessandra De Paola alessandra.depaola@unipa.it
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Workshop on Data Fusion in the Internet of Things (DFIoT)
Co-located with IEEE 15th International Conference on Pervasive Intelligence and Computing – PICom 2017 (http://cse.stfx.ca/~picom2017/ http://cse.stfx.ca/%7Epicom2017/) 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 August 2017 • Author Notification: 24 August 2017 • Camera-ready Paper Due: 1 September 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
------------------------------------------------------------- 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: alessandra.depaola@unipa.it mailto:alessandra.depaola@unipa.it
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