论文信息 - A multi-agent supervising system for smart environments

A multi-agent supervising system for smart environments

This paper presents a multi-agent architecture for a supervising system which is part of a new intelligent ambient system, called AmIHomCare. The supervising system detects the context of the person (using a domain ontology): the person location in the room together with the surrounding objects and its body posture. A sequence of these contexts is assembled in a daily activity, based on a set of rules, described by a stochastic context free grammar with attributes. Also the system predicts the next context and the next activity in order to detect emergencies in the smart environment.

Adina Magda Florea | Irina Mocanu

[1] Etienne Corvée,et al. Body Parts Detection for People Tracking Using Trees of Histogram of Oriented Gradient Descriptors , 2010, 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance.

[2] Juan Carlos Augusto,et al. Ambient Intelligence—the Next Step for Artificial Intelligence , 2008, IEEE Intelligent Systems.

[3] Nikolaos I. Spanoudakis,et al. Agent-based Architecture in An Ambient Intelligence Context , 2006, EUMAS.

[4] Calin Munteanu,et al. AmIHomCare: a complex ambient intelligent system for home medical assistance , 2011 .

[5] Diane J. Cook,et al. Active Lezi: an Incremental Parsing Algorithm for Sequential Prediction , 2004, Int. J. Artif. Intell. Tools.

[6] Diane J. Cook,et al. Designing Smart Environments: A Paradigm Based on Learning and Prediction , 2005, PReMI.

[7] Irina Mocanu. From Content-Based Image Retrieval by Shape to Image Annotation , 2010 .

[8] Diane J. Cook,et al. Online Sequential Prediction via Incremental Parsing: The Active LeZi Algorithm , 2007, IEEE Intelligent Systems.

[9] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[10] Adina Magda Florea,et al. A Multi-agent System for Human Activity Recognition in Smart Environments , 2011, IDC.