Special Issue on Data Mining in
Pervasive Environments
The
explosion of sensors and mobile phones and their interaction with human life
funnel a phenomenal amount of data through pervasive computing environments. The
data from these sensors (environmental sensors such as motion sensors; smart
phone sensors such as accelerometers and GPS; and object sensors such as RFID
tags) have to be carefully analyzed to extract interesting and relevant information.
The sheer volume of sensor data, as well as its streaming and distributed
nature, poses many challenges to the data mining, mobile sensing and knowledge
discovery community. Analyzing these data trails can support different
applications in a novel way. The applications may vary from personal and
community healthcare (smart home independent living, fitness and exercising),
green computing (building energy management, environment monitoring), urban
sensing (intelligent transportation system, natural resource management),
marketing industry (advertisement, consumer shopping habits) and after all
social networking.
We
solicit high quality and original unpublished papersfrom researchers working on
data mining in pervasive environments to highlight current challenges, and to
showcase the latest results. The results will demonstrate how current data
mining, mobile sensing and knowledge discovery methods can be extended to
mining solutions for dealing with challenging real world problems. The unique
nature of sensor data in pervasive environments demands for novel data mining,
mobile sensing and knowledge discovery methods that can handle large, multi-modal,
heterogeneous and distributed streams of data. We hope that the results of this
special issue not only can be beneficial for the pervasive computing community,
but the resulting algorithms and solutions will also be adapted by researchers
in various other application fields.
The
major topics of the special issue include, but not limited to:
1.
Unsupervised methods for discovering interesting
patterns such as human activity and behavior based on:
•
Novel
data mining methods
•
Relational
and graph mining methods
•
Real
time analysis of dynamic sensor data
•
Models
for sensor fusion
•
Multimodal
context recognition
2.
Supervised machine learning methods for
analyzing data in pervasive environments
•
Generative
and Discriminative models
•
Relational
models
•
Graphical
models
3.
Mobile sensing
•
Mobile data collection models
•
Mining large scale sensor data
•
Sensing and machine learning techniques
•
Participatory, opportunistic and collaborative
sensing
•
Activity recognition and personal
health monitoring using mobile phones
4.
Case studies based on success stories
of data mining techniques for real-world pervasive computing applications
•
Low
level sensor data (accelerometers, GPS, RFID, Motion sensors, etc), Physiological
sensors, smart phone based sensing, video and audio, other mediums
•
Data
fusion and uncertainty reasoning for situation awareness
•
Novel
proposals on architecture and middleware design for smart environments services
•
Services
and applications in pervasive healthcare, green building energy management and
intelligent transportation, etc.
•
Test-beds
and real world deployments
Some
of the fundamental questions that will be addressed in this special issue (but
not limited to) are: What data mining or mobile sensing techniques support
real-time recognition of human activities?, What are the solutions for improving
the generalization of these pervasive data mining systems to support wide scale
deployment and use?, What are the challenges and
potential solutions for collecting pervasive data for modeling and analysis?,
What are the strategies for benchmarking the results of various sensorial
approaches in pervasive environments?
All submissions have to be prepared according to the Guide for Authors as published in the Journal website at www.ees.elsevier.com/pmc/. Authors should select SI: Data Mining, from the “Choose Article Type” pull-down menu during the submission process. All contributions must not have been previously published or be under consideration for publication elsewhere. A submission based on one or more papers that appeared elsewhere has to comprise major value-added extensions over what appeared previously (at least 30% new material). Authors are requested to attach to the submitted paper their relevant, previously published articles and a summary document explaining the enhancements made in the journal version.
Paper submission deadline: September 15,
2013
First Notification: December 15, 2013
Final Notification: February 15, 2014
Nirmalya Roy, University of Maryland at
Baltimore County, nirmalya.roy@gmail.com
Parisa Rashidi, Northwestern University, parisa.rashidi@northwestern.edu
Liming Chen, University of Ulster, l.chen@ulster.ac.uk
Larry Holder, Washington State
University, holder@eecs.wsu.edu