Trends and Advances for Data Mining and Classification on Internet of Things (IoT) systems

Posted on July 20, 2016 in Special Issue
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Trends and Advances for Data Mining and Classification on Internet of Things (IoT) systems

Wed 01 Feb 2017

Computer Communications invites manuscript submission in the area of Data Mining and Classification on Internet of Things (IoT) systems

1. Introduction/Overview

We’re currently shifting from the Information Age to the Intelligence Age. The Intelligence Age will be characterized by autonomous communication between intelligent devices that are sensitive to a person’s presence and respond by performing a specific task that enhances that person’s lifestyle.

In this perspective, the Internet of Things envisages a plethora of heterogeneous objects interacting with people and the physical environment.

Things are able to sense a user’s presence, movement and behavior, analyze that data in order to learn about that user, and then make an intelligent decision to perform a task based on the data.

The widespread diffusion of Internet of Things (IoT) represents a potentially huge amount of data to manage, store and explore. In this scenario, it requires more efficient and scalable data analysis methods and raises additional challenges on data mining and analytics, including preserving users’ security and privacy. Data management in IoT systems is an emerging research area and there is generally a deficiency to understand the suitable approaches to support this field. The success of an IoT systems depends on the efficient integration of its devices, sensors and data management techniques, as well as of novel protection techniques.

Therefore, this special issue tries to be a meeting point where researchers in Data Mining and Classification on IoT could have the opportunity to present current research results, and to look for new ways of transformation of the technological ecosystem in all its complexity, while to guaranteeing both technically and regulatory the neutrality of the future internet.

2. Why this topic is Important to Journal of Computer Communications readers

Computer Communications is an international and prestigious journal; in this perspective this SI, focusing on Data Mining and Classification on IoT, will be able to collect several scientific contributions from different research areas, since the IoT paradigm can be considered a quite consolidated but at the same time an emerging paradigm with a plethora of applications (e-health, cultural heritage, industrial, transportation, data mining, etc.) and consequently new technical flaws and threats of intrusions.

In this special section, we invite researchers from academia, industry, and government to discuss challenging ideas, novel research contributions, demonstration results, and standardization efforts on the Internet of Things and related areas.

Topics of interest include, but not limited to the following:

IoT platforms for Big Data and Data analytics;
Environmental sensing and computing;
Personalized services in IoT systems;
Ambient-oriented technologies;
Ambient context modeling and reasoning;
Smart environments and applications;
Data Classification on IoT environments;
Interaction techniques and technologies in IoT systems;
Intelligent data analysis;
Social Data Mining techniques;
Real-time intelligence;
Data streams mining techniques:
Algorithms for data mining on IoT environments;
Algorithms for Big Data analytics and data mining on IoT environments;
Intelligent sensors and sensing applications
Challenges in big data storage and processing;
Mining and recommendation techniques for IoT environments;
Data mining analytics applied to Smart Cities;
Data mining techniques applied to Cultural Heritage domain;
IoT architecture, tools and applications for Data analysis.

3. Guest Editor Information

Francesco Piccialli, University of Naples “Federico II”, Italy

Dr. Francesco Piccialli is a researcher in University of Naples, Federico II, Italy. He received the M.S. and PhD. degrees in Computational and Computer Science in 2012 and 2015 respectively. Dr. Francesco Piccialli serves as committee member, track chair, invited session chair of many international conferences and workshop (EUSPN 2016, ICDIM2016, 3GPCIC 2016, CADSA 2015/2016, KES-IIMSS 2016, VICTA 2014/2015/2016, etc.). He is also the organizer of two international workshop named V.I.C.T.A. and Da.M.I.S. His research topics are focused on Internet of Things paradigm, design of Smart Environments, Cultural Heritage applications within IoT. Recently, he have been working on smart framework to support an innovative fruition schema for Cultural spaces, applying it in many real cultural context in Naples city, Italy.

Jason J. Jung, Chung-Ang University, Korea

Jason J. Jung is an Associate Professor in Chung-Ang University, Korea, since September 2014. Before joining CAU, he was an Assistant Professor in Yeungnam University, Korea since 2007. Also, He was a postdoctoral researcher in INRIA Rhone-Alpes, France in 2006, and a visiting scientist in Fraunhofer Institute (FIRST) in Berlin, Germany in 2004. He received the B.Eng. in Computer Science and Mechanical Engineering from Inha University in 1999. He received M.S. and Ph.D. degrees in Computer and Information Engineering from Inha University in 2002 and 2005, respectively. Dr. Jung serves as Editorial board member of many international journals, e.g., Journal of Universal Computer Science, International Journal of Intelligent Information and Database Systems, International Journal of Social Network Mining and International Journal of Web Engineering and Technology. He has edited 10 special issues in international journals, 2 conference proceedings. He is the author of about 100 international publications. His research topics are knowledge engineering on social networks by using many types of AI methodologies, e.g., data mining, machine learning, and logical reasoning. Recently, he have been working on intelligent schemes to understand various social dynamics in large scale social media (e.g., Twitter and Flickr).

Silvia Giordano, PhD from EPFL, is Professor at SUPSI, Distinguished Professor and Thousand Talents Plan Professor at Tianjin University of Technology, China and associate researcher at CNR. She directs the NetLab, and is responsible for the Social Area. Her work in the field ad hoc networks produced several seminal papers in key research directions, with hundreds of citations. Currently she is working in the area of human mobility and social computing with very innovative results in the field of localization, and with seminal work that calls for a new understanding of the concept of social distance. She is editor of several journals, and in the steering and organising committee of major conferences. She is ACM Distinguished Scientist, IEEE Senior member, and ACM Distinguished Speaker.

Jiannong Cao, is a chair professor and the head of the Department of Computing at The Hong Kong Polytechnic University. He is also the director of the Internet and Mobile Computing Lab in the department. Before joined The Hong Kong Polytechnic University in 1997, he has been on faculty of computer science in James Cook University and The University of Adelaide in Australia, and the City University of Hong Kong. Dr. Cao is currently, an adjunct professor of Sun Yat-sen University and National University of Defense Technology, a guest professor of Shenzhen University. He also held several adjunct and visiting positions, including adjunct chair professor of Central South University, adjunct professor of Beijing Jiaotong University, Shanghai Jiaotong University, Northeastern University, Northwest Polytechnic University, a visiting research professor in the National Key Lab for Novel Software Technology, Nanjing University of China, a visiting fellow in the School of Computer Engineering, Nanyang Technological University of Singapore, a visiting scholar of the Institute of Software-Chinese Academy of Science, and Peking University Overseas Scholar Lecture Program.

4. Submission Instructions

Please see http://www.elsevier.com/locate/comcom for preparation guidelines and visit http://ees.elsevier.com/comcom to submit your manuscript. To ensure that all manuscripts are correctly identified for inclusion into the special issue, please select \”SI: DMIoT\” when you reach the Article Type step in the submission process. For further information, please contact the guest editors.

5. Important Dates

Submission deadline: 1 Feb 2017

Acceptance Notification: 1 July 2017