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Towards a System Architecture for Recognizing Domestic Activity by Leveraging a Naturalistic Human Activity Model M. Dominici, M. Frjus, J. Guibourdenche, B. Pietropaoli, F. Weis GAPRec 2011, June 12, Freiburg Outline Introduction and


  1. Towards a System Architecture for Recognizing Domestic Activity by Leveraging a Naturalistic Human Activity Model M. Dominici, M. Fréjus, J. Guibourdenche, B. Pietropaoli, F. Weis GAPRec 2011, June 12, Freiburg

  2. Outline  Introduction and basic assumptions  Research problem  Proposed approach M. Dominici - Recognizing domestic activity GAPRec 2011

  3. Smart Home  Promotes  Comfort  Security  Energy savings  …  Natural interaction  Context-aware services  Activity recognition is a fundamental feature M. Dominici - Recognizing domestic activity GAPRec 2011 1

  4. Smart Home project  Three-year academia-industry collaboration  Goal  Prevent energy waste and preserve inhabitants’ comfort  An interdisciplinary project  Ubiquitous computing + cognitive ergonomics  Challenge  Being aware of the unavoidable “gap” between activity recognition mechanisms and real-world activity (as seen by naturalistic human activity models)  Constraints  Design and experimentation of a prototype system using off-the-shelf non-invasive technologies M. Dominici - Recognizing domestic activity GAPRec 2011 2

  5. Physical approach  Local context + local processing local  Physical objects publication of “ presence “augmented” information ” heater 1  Bring pertinent information coordination local publication and context of “ temperature  Realize the application evaluation information ” logic in a distributed “augmented” fashion heater 2  “Augmented” appliances and sensors collected information M. Dominici - Recognizing domestic activity GAPRec 2011 3

  6. Four layers for context awareness 4. Contextual information for applications E.g., “a person is watching TV”, complex activities E.g., “presence in a room” or “TV is on” Raw data given by sensors Layered architecture suggested by J. Coutaz et al. in “Context is key”, 2005 M. Dominici - Recognizing domestic activity GAPRec 2011 4

  7. Four layers for context awareness 4. Contextual information for applications E.g., “a person is watching TV”, complex activities E.g., “presence in a room” or “TV is on” Raw data given by sensors Layered architecture suggested by J. Coutaz et al. in “Context is key”, 2005 M. Dominici - Recognizing domestic activity GAPRec 2011 4

  8. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence …  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 5

  9. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence …  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 5

  10. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 6

  11. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 6

  12. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 6

  13. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 6

  14. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 6

  15. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 6

  16. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 6

  17. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 6

  18. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 6

  19. Context and situation inference  Context Spaces Theory  Using geometrical metaphors to describe Context Attributes (dimension) context and situations  Input: Context Attributes  Presence, movement, equipment status, etc.  Output: Situation Spaces , modeling real-life situations with a measure of the confidence  Watching TV, ironing, etc. presence  Context State = current context attribute values at a given moment heater status M. Dominici - Recognizing domestic activity GAPRec 2011 6

  20. Outline  Introduction and basic assumptions  Research problem  Proposed approach M. Dominici - Recognizing domestic activity GAPRec 2011

  21. Overview of the architecture Dynamics recognition (???) Situation Spaces Situation recognition (Context Spaces ) Data fusion (BFT) Plug computer Sensor Node Augmented object M. Dominici - Recognizing domestic activity GAPRec 2011 7

  22. Activity VS Plan “The distinction to be made between activity recognition and plan recognition is the difference between recognizing a single (possibly complex) activity and recognizing the relationships between a set of such activities that result in a complete plan.” C. W. Geib & R. P. Goldman A probabilistic plan recognition algorithm based on plan tree grammars Artificial Intelligence, 2009 , 173 , 1101 - 1132 Either Activity or Plan… human stuff! M. Dominici - Recognizing domestic activity GAPRec 2011 8

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