Behaviour Recognition in Ambient and Smart Environments (Be-AmI 2011)


A wide-range of application domains within the fields of ambient intelligence, and pervasive and ubiquitous computing environments require the ability to represent and reason about dynamic spatial phenomena. Real world ambient intelligence systems that monitor and interact with an environment populated by humans and other artefacts require a formal means for representing and reasoning with spatio-temporal, event and action based phenomena that are grounded to real aspects of the environment being modelled. A fundamental requirement within such application domains is the representation of dynamic knowledge pertaining to the spatial aspects of the environment within which an agent, system or robot is functional. At a very basic level, this translates to the need to explicitly represent and reason about dynamic spatial configurations or scenes and desirably, integrated reasoning about space, actions and change. With these modelling primitives, primarily the ability to perform predictive and explanatory analyzes on the basis of available sensory data is crucial toward serving a useful intelligent function within such environments.

The course will introduce the audience to applications of behaviour recognition which are starting to have a practical impact in the real world, but it will also familiarise the audience with the underlying methods and techniques. It will serve the following objectives:



ECTS Points: 4
Duration: 4 weeks; June 2011.

Time and place: will be announced in 1st introduction lecture

Course introduction lecture: May 26 (14.00 - 16.00, Cartesium, Level 3)

Format: One 2hr lecture per week, and reading assignments. Evaluation will be done in Seminar mode during early July.

Delivered by:

Hans W. Guesgen (Massey University, New Zealand), and Mehul Bhatt (University of Bremen)


by email: