DREAM Research team

Diagnosing, Recommending Actions and Modelling

Team presentation

The main research topics of the DREAM project-team are about aiding monitoring and diagnosis of time evolving systems. The main issue is to infer the state of a system from observations provided by sensors in order to detect and characterize potential anomalies or failures within the system. We use a model-based approach relying on normal and faulty behavioral models. These models are temporal qualitative discrete-event models such as temporal communicating automata, temporal causal graphs or sets of chronicles.

Research themes

  • Automatic model acquisition. We investigate symbolic machine learning techniques such as ILP (Inductive Logic Programming).
  • Diagnoser algorithm design and implementation.Relying on model inversion and compilation, these techniques aim at computing compact models which link directly observations to faults. More precisely, we focus on a decentralized and generic approach and on the use of model checking techniques.
  • Diagnosis and decision interaction in an uncertain context.

Application areas

  • Cardiac monitoring Electrocardiogram on-line analysis, "intelligent" cardiac devices investigation: pacemakers and defibrillators.
  • Environmental protection Improvement of land cover classification from remotely sensed images, qualitative modelling of pollutant (pesticides, nitrates) transfer in groundwater.
  • Industrial diagnosis Supervision of telecommunication networks and power distribution systems.

International and industrial relations

  • Participating in MONET2, the European Network of Excellence in Model-Based and Qualitative Reasoning Systems (BRIDGE working group).
  • Collaborating with ANU (the Australian National University, Canberra). Contact: Sylvie Thiébaux.
  • Collaborating with INRA (Institut National de la Recherche Agronomique - National Institute for Agricultural Research) in the Phyto project.
  • Participating in the IMALAIA working group.
  • Participating in the MAGDA2 project (with R&D/France-telecom, Alcatel, Ilog, university Paris-Nord and the SIGMA2 and TRISKELL projects from IRISA). The project aims at implemeting robust correlation and diagnosis algorithms for telecommunication networks.
  • Participating in the PISE project (with LTSI-University of Rennes 1, Rennes University Hospital and Ela Medical) on the design of "intelligent" cardiac devices.
  • Participating in the "Medical Advisor" project (with Integrative Biocomputing and the Rennes Medical Informatics Laboratory) on the design of an Intelligent Tutoring System for medical diagnosis in cardiology.
  • Collaborating with EDF on industrial prognosis for maintenance.
  • Participating in the PROCOPE project.

Research teams of the same theme :

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