1. There is more to Context than Location Albrecht Schmidt, Michael Beigl, and Hans-W. Gellersen Telecooperation Office (TecO), University of Karlsruhe, Elsevier, 1999 2008-09-24 Presentation by JongHeum Yeon, IDS Lab.

2. Copyright  2008 by CEBT Contents  Introduction  Related Work  A Working Model for Context-Aware Mobile Computing  Enhancing Ultra-Mobile Devices with Sensors  Sensor Fusion for Context Awareness  Discussion 2

3. Copyright  2008 by CEBT Introduction  Ultra-mobile devices computing devices which can be used while on the move Personal Digital Assistants (PDAs) Mobile phones Wearable computers  Context-awareness in mobile computing Awareness of the physical environment surrounding a user and their ultra-mobile devices  Aim of this paper Introduction of working model for context Sensor-based context-awareness Present a prototype that demonstrates the utility of sensor integration in ultra- mobile devices Integration of multiple sensors and sensor fusion to obtain context information 3

4. Copyright  2008 by CEBT Related Work  Active Badge Use only location as context GPS, GSM(cell information)  Stick-e-notes Documents tagged with location and time information  Cyberguide & GUIDE Location User preference with an awareness  Smith et al Integrating a few environmental sensors 4

5. Copyright  2008 by CEBT A Working Model for Context  In 1999, lack of generality of the concept and models  Propose a simple working model for context primarily as means to position their work on sensor-based context- awareness.  Model A context describes a situation and the environment a device or user is in. A context is identified by a unique name For each context a set of features is relevant For each relevant feature a range of values is determined (implicit or explicit) by the context. 5

6. Copyright  2008 by CEBT A Working Model for Context (cont’d) 6

7. Copyright  2008 by CEBT A Working Model for Context (cont’d)  Human Factors Information on the user – knowledge of habits/emotional state/biophysiological conditions/... User’s social environment – co-location of others/social interaction/group dynamics/… User’s tasks – spontaneous activity/engaged tasks/general goals/...  physical environment Location – absolute position/relative position/co-location/... Infrastructure – surrounding resources for computation/communication/task performance/... Physical conditions – noise/light/pressure/... 7

8. Copyright  2008 by CEBT Acquiring Context  Explicitly By requiring the user to specify e.g. Current Location  Implicitly By monitoring user and computer-based activity e.g. monitoring of user interaction to turn of a device after a period of inactivity e.g. monitoring of battery power for adaptation of power-intensive applications  Acquisition of context Smart environments Embed sensors in ultra-mobile devices 8

9. Copyright  2008 by CEBT Sensor Technology  Optical/Vision photo-diode, color sensor, IR and UV-sensor, etc. wavelength, sunlight, type of artificial light, main color, motion, detection of objects, landmarks, people, gestures, etc.  Audio microphone, etc. loudness, type of background noise, base frequency, speaker identification, etc.  Motion mercury switches, angular sensors, accelerometers moving the device, located on a table, driving in a car, etc. 9

10. Copyright  2008 by CEBT Sensor Technology (cont’d)  Location location sensor, GPS, cellular network, radio beacon, etc. position, location, co-location, proximity of users, devices, environment  Bio-Sensors pulse, skin resistance, and blood pressure, etc. emotional state, etc.  Specialized sensors touch, temperature, air pressure, gas concentration, radiation, etc. 10

11. Copyright  2008 by CEBT Sensor-based Context-Awareness for Adaptive PDA User Interfaces  Light-Sensitive Display Light sensor in a Palm Pilot Awareness of surrounding lighting conditions Control of its display’s backlight  Orientation-Sensitive User Interface PDA, a Newton MessagePad Awareness for its orientation by adding two mercury switches Switch display mode between portrait mode and landscape mode 11

12. Copyright  2008 by CEBT Sensor-based Context-Awareness for Adaptive PDA User Interfaces (cont’d) 12

13. Copyright  2008 by CEBT Architecture for Sensor Fusion 13 Cues Scripting Contexts Sensors While a context While a context Leaving a context Leaving a context Entering a context Entering a context Logical Physical Situation User

14. Copyright  2008 by CEBT Architecture for Sensor Fusion  Sensors Physical sensors – Electronic hardware components that measure physical parameters Logical sensors – Information gathered from the host of the awareness component  Cues Abstraction from physical and logical sensors Taking the values of a single sensor up to a certain time as input and providing a symbolic or sub-symbolic output 14

15. Copyright  2008 by CEBT Architecture for Sensor Fusion  Contexts Description of the current situation on an abstract level derived from the cues Two-dimensional vectors – symbolic value describing the situations – a number indicating the certainty that the user (or the device) is currently in this situation  Scripting provides mechanisms to include context information in application Entering a context – if a certain situation is indicated with a probability that is higher than a threshold an action is performed after a certain time# Leaving a context – if the probability for a certain situation is becoming less than a threshold an action is performed after a certain time. While in a context – if a certain situation is indicated with a probability higher than a threshold an action is performed every specified time interval. 15

16. Copyright  2008 by CEBT Deriving Context from Sensor Data  Sensor data is processed according to the architecture from sensor to cues and from cues to context 16 ContextCues In the officeArtificial light, stationary or walking, room temperature, dry JoggingNatural light (cloudy or sunny), walking or running, dry or raining, high pulse

17. Copyright  2008 by CEBT Discussion  Pros Real implementation with sensors Mapping raw data to abstract concepts as context  Cons Published in 1999 Not propose a general model Context data and processing are mixed in the architecture 17