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DESCRIPTION. Ambient Intelligence (AmI) refers to the use of an array of distributed sensors and actuators/effectors, incorporated into everyday objects, such as cabinet doors, stoves, lamps, screens and so on in a transparent way, meaning that they are invisible to the user, in order to monitor the user’s status and provide assistance as needed, such as advice, feedback, guidance or warning, based on information collected and historical data. This concept, which has now become reality, originated in 1988 at the Xerox Palo Alto Research Centre (PARC), and resulted from the work entitled “The Computer for the 21st Century” of the respected American scientist, Mark Weiser. AmI is now used to develop solutions in multiple applicative contexts. For instance, with the aging population, AmI if often seen as an avenue of solution to help the persons suffering from loss of autonomy to remain at home. In the industrial context, AmI is foreseen as a way to deploy business intelligence and optimize production by helping the workers, using multiple sensors deployed in the production environment. However, in all applicative situations of AmI where the goal is to assist the user, there is one key challenge that is the same, which is how to identify, within the smart environment, the ongoing activities of the user from observed basic sensors data. This challenge is referred to, in the scientific community, as the problem of Human Activity Recognition (HAR). In such a context, the main objective of this workshop is to investigate new solutions to scientific problems occurring in the various topics related to HAR in the context of smart environments and ambient intelligence. More importantly, this workshop aims to be interdisciplinary by seeking contributions from researchers in the fields of technology, engineering, health, etc.
Topics of interest This workshop aims to explore various topics including, but not limited to the following:
• Algorithms for plan, activity, intent, or behavior recognition or prediction
• Machine learning for activity recognition
• Modeling and knowledge engineering for HAR
• HAR and the real-time simulation of activities
• High-level activity and event recognition
• Activity recognition of multiple concurrent users
• Results of real life experiments with HAR systems
• Fine-grained activity recognition
• Spatial and temporal features of HAR
• Cognitive and others personalization models for activity recognition
• Recognition of emotions of a user
• Any pertinent topics related to the development of deployment of HAR systems
This one-day workshop will consist of invited talks from experts, technical and position papers presentations organized into topical sessions (decided based on submissions), and a poster session depending on the participation. To encourage discussion, the workshop will be limited to 50 invited participants. We plan to have a keynote speaker and a demo session.
SUBMISSION. The organizing committee is currently seeking either technical papers up to 6 pages in the conference format, or else, for poster presentations, authors should submit a short paper or extended abstract, up to 2 pages describing research relevant to the workshop.
Workshop website:
http://liara.uqac.ca/ant19-workshop-arise.htm
Please submit your paper via easy chair:
https://easychair.org/conferences/?conf=arise2019
Chair Bruno Bouchard, Ph.D., IEEE Senior, [email protected]
Sébastien Gaboury, Ph.D., Co-Chair, [email protected]
Kévin Bouchard, Ph.D., Co-Chair [email protected]
LIARA Laboratory University of Quebec at Chicoutimi (UQAC) Tel: (418) 545-5011 555, boul. de l'Université Chicoutimi, QC, G7H 2B1, Canada
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