[Tccc] Call for Papers: ML4SENSORS 2012 Workshop_Submissions due 23 March 12
Justina
justina.senkus
Fri Mar 16 08:07:44 EDT 2012
CALL FOR PAPERS
International Workshop Machine Learning for Sensors and Sensor Networks
Applications ML4SENSORS 2012
in conjunction with S-CUBE 2012 - International Conference on Sensor
Systems and Software
Lisbon, Portugal
Workshop date: 4 June, 2012
Workshop website: http://users.med.up.pt/pprodrigues/ml4sensors/
Conference Website: http://s-cubeconference.org/2012/show/home
HIGHLIGHTS
- All accepted papers will be published by Springer and made available
through SpringerLink Digital Library, one of the world's largest
scientific libraries
- Proceedings will be submitted for indexing by Google Scholar, ISI, EI
Compendex, Scopus and many more.
- The event is endorsed by the European Alliance for Innovation
(http://eai.eu/), a leading community-based organisation devoted to the
advancement of innovation in the
field of ICT
[Scope]
It has been established empirically that onboard processing of data
generated from sensor devices is the most economic mode of processing,
due to limited power of battery operated sensor nodes. Sensors tend to
drain their energy rapidly on sending and/or receiving data. Therefore,
there is a necessity in processing sensed data using the limited
computational power onboard the sensor node.
The main goal of the workshop is to provide a forum for sensor network
researchers and practitioners to share their recent results on the
deployment of machine learning techniques in sensor networks, and gather
researchers working on machine learning algorithms for applied sensor
network problems.
Numerous important applications require machine learning techniques to
process data generated from sensor networks. However, the realisation of
such applications is faced by a number of research challenges. Limited
computational power of the sensing devices requires machine learning
techniques to be resource efficient and resources aware. Additionally,
distributed processing of the data is required, having each node
performing a local learning from the sensed data. Moreover, data
duplication is an issue that needs to be addressed in sensor networks,
especially dense sensor networks. Finally, data quality is of concern
given that sensor networks may be deployed in an environment of wild
weather conditions that can affect the performance of the sensing
devices. These issues and more are required to be addressed.
[Topics]
The topics include but are not restricted to:
- Supervised machine learning from sensor data
- Unsupervised machine learning from sensor data
- Machine learning for sensor network comprehension
- Integration of learning algorithms in sensors
- Deployment of machine learning algorithms in sensor networks
- Reliability issues in sensor network learning applications
- Resource-aware knowledge discovery in sensor networks
- Theoretical models for distributed machine learning in sensor networks
- Real-world problem design and sensor network knowledge discovery
requirements
- Case-studies of machine learning applications in sensor networks
- Sensor data stream models and stream learning in sensor networks
- Scalable machine learning algorithms
IMPORTANT DATES
Submission deadline: 23 Mar 2012 ** NEAR **
Notification: 20 Apr 2012
Camera-ready deadline: 4 May 2012
Workshop date: 4 Jun 2012
PAPER TYPES
The workshop is open for four types of submissions:
- Regular papers should present established research with enough
scientific contribution to the field.
- Work in Progress papers are meant for ongoing research that is
expected to provide further advances in the future.
- Short papers should present current/future perspectives on the field
of machine learning applications for sensors and sensor networks.
- Demo papers are meant for researchers wanting to present their
applications on a session specially devoted to demonstrations.
PAPER SUBMISSION
Papers must be formatted using the Springer LNICST Authors' Kit.
Instructions and templates are available from Springer's LNICST
homepage. Please make sure that your paper adheres to the format as
specified in the instructions and templates.
Regular and Work in Progress papers are allowed up to 12 pages including
all figures, tables and references. Short and Demo papers are restricted
to 6 pages.
Papers should be submitted through EAI Confy system.
Please visit the workshop web site for more information:
http://users.med.up.pt/pprodrigues/ml4sensors/
WORKSHOP PROGRAM CHAIRS
Pedro Pereira Rodrigues - University of Porto, Portugal
email: pprodrigues at med.up.pt
Joao Gama - University of Porto, Portugal
email: jgama at fep.up.pt
Mohamed Medhat Gaber - University of Portsmouth, UK
email: mohamed.gaber at port.ac.uk
EAI
The European Alliance for Innovation is a dynamic eco-system for
fostering ICT enabled innovation to improve European competitiveness and
to benefit society. EAI uses open e-platforms to inspire grassroots
collaboration among all relevant actors, from organizations to
individuals, to stimulate community driven innovation to its
institutional and individual members worldwide. Through
EAI,organizations find ideas and talent, and individual innovators find
organizations for their ingenuity and craft. Join the innovation
community at www.eai.eu
More information about the TCCC
mailing list