Data driven conceptual structures for simultaneous activities

An activity is a chain of fuzzy events that occur in an environment caused by an intelligent system in order to achieve a goal. A goal may be achieved by effort of more than one individual. Regardless from the physical entity (modality and location) of the intelligence source and the quantity of individuals who perform the activities; per each possible goal or activity, we consider a source of intelligence who directs the order of fuzzy events that occur in the world. By frequently observation of the world, the plan behind world actuations is modeled applying extensions of the fuzzy logic. The main key point that we deal with is the analysis of the observations in order to make inferences about possible simultaneous activities that may be planned and realized by one or more individuals. A fuzzy conceptual structure for each individual and simultaneous activity is formalized; however, the model tolerates partial deviations from the activity structure.

[1]  Kevin Bouchard,et al.  Spatiotemporal knowledge representation and reasoning under uncertainty for action recognition in smart homes , 2011, MAICS.

[2]  Diane J. Cook,et al.  Discovering Temporal Features and Relations of Activity Patterns , 2010, 2010 IEEE International Conference on Data Mining Workshops.

[3]  Abdenour Bouzouane,et al.  A Possibilistic Approach for Activity Recognition in Smart Homes for Cognitive Assistance to Alzheimer’s Patients , 2011 .

[4]  Kevin Bouchard,et al.  Recognition of fuzzy contexts from temporal data under uncertainty case study: Activity recognition in smart homes , 2012, 2012 IEEE 13th International Conference on Information Reuse & Integration (IRI).

[5]  Stephen L. Chin An Efficient Method for Extracting Fuzzy Classification Rules from High Dimensional Data , 1997, J. Adv. Comput. Intell. Intell. Informatics.

[6]  Abdenour Bouzouane,et al.  Activity modeling under uncertainty by trace of objects in smart homes , 2014, J. Ambient Intell. Humaniz. Comput..

[7]  L. Zadeh Fuzzy sets as a basis for a theory of possibility , 1999 .

[8]  Abdenour Bouzouane,et al.  Intelligent temporal data driven world actuation in ambient environments: Case study: Anomaly recognition and assistance provision in smart home , 2013, 2013 IEEE/ACIS 12th International Conference on Computer and Information Science (ICIS).

[9]  Theophano Mitsa,et al.  Temporal Data Mining , 2010 .

[10]  John F. Sowa,et al.  Conceptual Structures: Information Processing in Mind and Machine , 1983 .

[11]  Diane J. Cook,et al.  Temporal pattern discovery for anomaly detection in a smart home , 2007 .

[12]  Abdenour Bouzouane,et al.  A KEYHOLE PLAN RECOGNITION MODEL FOR ALZHEIMER'S PATIENTS: FIRST RESULTS , 2007, Appl. Artif. Intell..