Context-aware personal-attentive systems
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The document describes research on personal attentive systems (PAS) that aim to provide feedback to users at optimal times and through appropriate modalities based on their context. It outlines the conceptual architecture of a PAS including components for collecting raw context data, interpreting the data to infer the user's situation, modeling contextual domain knowledge, reasoning over the context to classify accessible devices, and making decisions about providing personalized and timed feedback. The goal is to evaluate PAS for helping users develop healthy habits by intervening at relevant moments and adapting the feedback based on the inferred context. Future work includes implementing and integrating the individual components and conducting field studies.
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Context-aware personal-attentive systems
- 1. Context-aware Personal Attentive Systems Tom Tourwé, Elena Tsiporkova (Sirris, BE) Ville Antila (VTT, FI) Monique Hendriks (Philips, NL) het collectief centrum van de Belgische technologische industrie
- 2. Smarcos – Goal & motivation • Smarcos aims to improve the interusability of interconnected embedded devices • Smarcos relies on the solid technological basis for system- level interoperability resulting from other EU R&D projects • Eg. ARTEMIS-Sofia and FP7-SmartProducts • Smarcos addresses challenges arising from user-level interaction of interconnected systems • Cross-platform interaction • Multi-user and multi-device collaboration • Synchronisation of system actions to maintain fluent task flow • Application and service adaptation to changing situational contexts
- 3. Smarcos - Research topics Design methods for embedded UIs Interface, interaction & context models (Distributed) Context processing Runtime UI & context composition UI migration Model-based UI generation Distributed functionality
- 4. Personal attentive systems • People have difficulty incorporating healthy habits into their daily life • Office workers: working on a computer, prolonged sitting, deadlines, meetings, travel by car • Diabetes type II patients: monitoring of glucose levels, effects of food, medicine adherence, physical activity, learning to cope with the disease • Doctors and lifestyle coaches can provide advice, but they cannot • Intervene at the right moment • Provide feedback on behaviour directly afterwards • Have intricate knowledge of people’s daily routine
- 6. Conceptual architecture Determine content, timing & Decision Engine modality of feedback Context Context Infer new knowledge from Reasoner Models information Transform raw data into infor- Context Interpreter mation about the user context Capture raw data from device Data Layer sensors
- 7. Data Layer Life-pattern detection through life logging • Low-power context logging software • Semantic location detection using cell-id (low power, always available) • Device usage detection (algorithms for mining location relative to smartphone application usage)
- 8. Context Interpreter Detecting important places and daily routines • Estimation of life patterns such as the semantic location of the user (e.g. “home”, “office”) • Detection of device usage in different locations • Detection of physical activity in different situations
- 9. Context Interpreter Can be used to … • Determine the devices that surround the user • e.g. at work, the user has access to his personal computer • Time and adapt system feedback based on the situation • e.g. time-shift notification to where user is more receptive • Log context changes and react appropriately • e.g. user entering an interesting location/situation such as ‘office’
- 10. Context Models Domain knowledge for PAS • Such domain knowledge is any factual information about persons, activities, locations and devices which influences the decision about at what time, on which device and through which modality feedback should be delivered to the user • Such domain knowledge is captured in a context model
- 11. Context Models Example domain knowledge • If the user is cycling then • available devices are mobile devices (phone & activity monitor) • availability for receiving messages is low • A pill reminder message is • an urgent message • best delivered through the audio modality
- 12. Context Reasoner Infer new knowledge from information • The goal of the reasoner is to classify devices as being ACCESSIBLE, AVAILABLE and/or USED • using the OWL reasoner and SWRL rules • ACCESSIBLE > AVAILABLE > USED • A device is an ACCESSIBLE_DEVICE if the user has access to it • A device is an AVAILABLE_DEVICE if it is an ACCESSIBLE_DEVICE which is ON • A device is a USED_DEVICE if it is being used by a user
- 13. Context Reasoner USER is_performed_by WATCHINGTELEVISION elena watching_television is_performed_on THING is_accessible_from THING elenas_television elenas_livingroom
- 14. Context Reasoner USER is_performed_by WATCHINGTELEVISION elena watching_television performs is_performed_on THING is_accessible_from THING elenas_television elenas_livingroom provides_access_to Inverse properties
- 15. Context Reasoner USER is_performed_by WATCHINGTELEVISION elena performs watching_television is_performed_on TELEVISION is_accessible_from THING elenas_television elenas_livingroom provides_access_to WATHINGTELEVISION is_performed_on only TELEVISION
- 16. Context Reasoner USER is_performed_by WATCHINGTELEVISION elena performs watching_television is_performed_on TELEVISION is_accessible_from HOME elenas_television elenas_livingroom provides_access_to TELEVISION is_accessible_from only HOME
- 17. Context Reasoner USER is_performed_by WATCHINGTELEVISION elena performs watching_television is_performed_on uses TELEVISION is_accessible_from HOME elenas_television elenas_livingroom provides_access_to performs o is_performed_on -> uses
- 18. Context Reasoner USER is_performed_by WATCHINGTELEVISION elena performs watching_television is_performed_on uses used_by TELEVISION is_accessible_from HOME elenas_television elenas_livingroom provides_access_to Inverse properties
- 19. Context Reasoner USER is_performed_by WATCHINGTELEVISION elena performs watching_television is_located_in is_performed_on uses used_by TELEVISION is_accessible_from HOME elenas_television elenas_livingroom provides_access_to uses o is_accessible_from -> is_located_in
- 20. Context Reasoner USER is_performed_by WATCHINGTELEVISION elena performs watching_television is_located_in is_performed_on is_location_of uses used_by TELEVISION is_accessible_from HOME elenas_television elenas_livingroom provides_access_to Inverse properties
- 21. Context Reasoner USER is_performed_by WATCHINGTELEVISION elena performs watching_television is_located_in is_performed_on is_location_of uses used_by USED_DEVICE is_accessible_from HOME elenas_television elenas_livingroom provides_access_to USED_DEVICE used_by min 1 USER
- 22. Context Reasoner USER is_performed_by WATCHINGTELEVISION elena performs watching_television is_located_in is_performed_on is_location_of uses used_by AVAILABLE_DEVICE is_accessible_from HOME elenas_television elenas_livingroom provides_access_to AVAILABLE_DEVICE is superclass of USED_DEVICE
- 23. Context Reasoner USER is_performed_by WATCHINGTELEVISION elena performs watching_television is_located_in is_performed_on is_location_of uses used_by ACCESSIBLE_DEVICE is_accessible_from HOME elenas_television elenas_livingroom provides_access_to ACCESSIBLE_DEVICE is superclass of AVAILABLE_DEVICE
- 24. Decision Engine Determine content, timing & modality of feedback • IF the situation is suitable, THEN send the message (as it is) as_is(Message, User, Device) :- send_message(User, Message), user_availability(User, high), has_access_to(User, Device), supports(Device, Modality), requires_modality(Message, Modality). • IF the situation is not suitable AND the message is not urgent, it should be time-shifted • IF the situation is not suitable AND the message is urgent, then the content should be adapted to the situation adapt(Message, User, Device, Alternate_Modality) :- send_message(User, Message), urgent(Message), has_access_to(User, Device), requires_modality(Message, Preferred_Modality), not(supports(Device, Preferred_Modality)), supports(Device, Alternate_Modality).
- 25. Conclusion • Presentation mainly reports on research results obtained by VTT and Sirris within the PAS use case defined by the Dutch consortium • Future research • Implementation of the decision engine in a Java-based logic engine • Integration of all individual components in a common prototype • Explore distributed context processing application • Carry out field studies to validate the effectiveness of timing and device choice • Deriving general statements regarding use case specific reasoning about context