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VUB AI-II Situated Computing Module 1: Context Awareness

VUB AI-II Situated Computing Module 1: Context Awareness. Walter Van de Velde wvdv@ping.be. What is Context Awareness?. History : Shilit et al. Context-Aware Computing Applications (1994) was primarily location based and use active badge technology (but user profiles in ITS go back a long way)

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VUB AI-II Situated Computing Module 1: Context Awareness

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  1. VUB AI-IISituated ComputingModule 1: Context Awareness Walter Van de Velde wvdv@ping.be

  2. What is Context Awareness? • History: Shilit et al. Context-Aware Computing Applications (1994) was primarily location based and use active badge technology(but user profiles in ITS go back a long way) • A rough definition: “The ability of a device or program to sense, react or adapt to its environment of use.” (Pascoe et al., HUC 99)

  3. Personal Augmentation (early 80’s) High Airplane Cockpit Situational Awareness Automobiles Pagers Walkman Watch Desktop PCs Pen-paper Eye-glasses Low Source: Nitin Sawhney, MIT Media Lab Passive Demand on User’s Attention Resources Active

  4. Personal Augmentation (early 90’s) High Airplane Cockpit HMD Wearables Automobiles Situational Awareness Newton Personal Organizers Mobile-Phones Virtual Reality Pagers Walkman Watch Network PCs Pen-paper Eye-glasses Low Source: Nitin Sawhney, MIT Media Lab Passive Demand on User’s Attention Resources Active

  5. Personal Augmentation (1997-future) Airplane Cockpit High COMRIS Nomadic Radio HMD Wearables Telematics Automobiles Audio-Aura Situational Awareness Newton Mobile Audio Speech Wear Smart-Phones Palm-Pilot Virtual Reality Pagers Walkman Watch Desktop PCs Pen-paper Eye-glasses Low Source: Nitin Sawhney, MIT Media Lab Passive Demand on User’s Attention Resources Active

  6. Why Context Awareness? • Improving interaction with a device • better defaults, automated choices,... • Improving quality of existing services • communication, information,... • Extended sensing and monitoring • security, health and safety,… • Enabling of new services • tourist services • health services ...

  7. Example artefacts • Active and smart badges • e-notes (and other GPS-based services) • Media Cups • Aware GSM • Memory aid camera • COMRIS • Intelligent Jogging Suite • ….

  8. Example Technology: TEA • TEA: Technology for Enabling Awareness • 2 year EU project, ending July 2000 • Starlab (B) • Omega Generation (I) • NOKIA (S) • TecO (Univesity of Karlsruhe) (G)

  9. TEA Objective “To produce an affordable add-on component to existing portable communication and computation devices that adds awareness of location and activity, and thus enables context sensitive device control.”

  10. Personal Augmentation (1997-future) Airplane Cockpit High COMRIS Nomadic Radio HMD Wearables Automobiles Audio-Aura TEA Situational Awareness Newton Mobile Audio Speech Wear Smart-Phones Palm-Pilot Virtual Reality Pagers Walkman Watch Desktop PCs Source: Nitin Sawhney, MIT Media Lab Pen-paper Eye-glasses Low Passive Demand on User’s Attention Resources Active

  11. TEA Objective

  12. The Essence of Mobility Environment Activity

  13. Context and location Context is much more than location

  14. The Context Space

  15. TEA Scenarios • GSM for a mobile journalist • GSM for school child • GSM for construction worker • PDA for business executive • PDA for university student • PDA for field engineer

  16. On the Nature of Context-Aware Applications • There are Many Classes of Context-Aware Applications • Context-Aware applications tend to be resource hungry • Context-Awareness has a high development cost • The computing environments are diverse • The greater the context, the greater the application • I.e., arguments for context services

  17. Sensors in Different Contexts

  18. Tracking context change

  19. The Kohonen Self-Organising Map (KSOM) • Intuition: mapping an n-dimensional data space to an m-dimensional one (m < n), with preservation of nearness • E.g., mapping a 8 dimensional data space to a 2-dimensional one.

  20. KSOM Input vector xk wk Output layer Wi+1 = Wi + A * F(Wi - Xi) Learning rate Neighboorhood function

  21. From Sensors to Scripts Sensors Cues Contexts Scripts

  22. Machine Learning Architecture • Sensors • Cues • Clusters • Classes • Contexts

  23. Comparative Study Clustering Algorithms • Focusing on scalability, on-line learning and stability: • Kohonen Self-Organizing Map • on-line K-Means • Sequential Leader Clustering • Neural Gas • Neural Gas with Hebbian Learning • Growing Neural Gas • Stable Growing Neural Gas • Recurrent Self-Organizing Map • ... with different metrics, parameters and adaptation rules • Results are accessible on internet

  24. Layered Model for Sensor based Context Awareness

  25. Sensor Layer • physical sensors • acceleration, light, temperature, audio, etc. • domain dependent • sensor placement matters • trade off, e.g power, price vs. added value • logical sensors • time, current application, phone number, memory available, etc. • modeled as time variant function

  26. amplitude standard deviation mean ... raw acceleration data Cue Layer • abstraction of raw sensor data • summary over time • extraction of features • reduce amount of data • one sensor can generate one or more cues • time window • sensor and cue dependent

  27. Fusion - Context Layer • description of the current situation on an abstract level • calculated from all cues available • predefined domain determined by application • context types • exclusive:in the office vs. at home • non-exclusive: walking, running, talking

  28. if enter(v, p, n) then perform action(i) if leave(v, p, n) then perform action(i) if in(v, p, m) then perform action(i) Applications and Scripting • application use contexts • supported by scripting primitives • enter a context • leave a context • while in a context

  29. Why makes it sense to use little processing power? • What is the vision? • Within a few years the context-awareness technologies we research here is applicable to nearly every artifact in our environment • Power will be one of the most critical issues for mobile artifacts!

  30. low processing power and little memory • Ubiquitous computing • cheap artifacts with computing power • very little power (power harvesting, ...) • what we can do today on microcontroller (~16Euro and 40x20mm) will be feasible in 9 year at 0.25 Euro and at a size 1x1mm … • Power is going down similar • -->make a pen context aware ....

  31. Aware GSM • Hardware Overview • 35 x 90 x 0.6 mm • Tailored for 6100 • 8 sensors + Processing • Serial Communication

  32. Aware GSM • Achievements • Integrated TEA component for GSM • Automatic profile changing • “In Hand” • “On Table • “In Pocket” • “Worn”

  33. Aware GSM • Problems • Battery Integration • Nokia Proprietary circuit • Extra Sensitive • Random Battery Failure • Software Integratrion • Phone Communication

  34. SMS sending • TEA SMS sending • Obsolete w/ 6100’s • Main Reasons • Phone is outdated • Intransigent Hardware vs. Flexible Software • Phone specific changes • Feasibility tests • Successful yet difficult • hard-coded changes - limited message-size

  35. SMS sending • Current Technology makes SMS possible • Phones now more flexible software than electronic equipment • AT Standard being widely used • old modem standard adapted for mobile phones • 10 bytes serially compared to kilobytes hard-coded

  36. WAP • Platform for new phone applications • we assumed that we have context knowledge (e.g. TEA, GPS, user) • can we enhance telephony?

  37. Communication in Context I • initiating face-to-face communication • social skill • trained from early childhood on • context matters - manly implicitly • how important is it for me? • how convenient seams it for the other person? • relation between the communication partners? • what type of conversation will it be? • is it socially acceptable (topic/situation)?

  38. Communication in Context II • initiating remote (tele)-communication • little knowledge about the called end • best guess approach • knowledge available • important to caller and called party • identity of communication partner • land line  location  situation • time  location/situation/activity

  39. Context-Call • novel phone interface • phone users can selectively share context • information about the situation • information about availability • … • caller can decided • knows her own constraints • has some information about the other side • can judge if the call will be appropriate

  40. Context-Call - Implementation I • WAP application • WML, WTAI, Apache, CGI • context-call application • context-selection page • server-backend

  41. Context-Call - Implementation II • context-call application • novel phone interface

  42. Context-Call - Implementation III • context-selection page • tell the system your context (similar to profiles) • using TEA for automation

  43. Hardware integration PIC PDA/GSM Sensors PIC CPU PDA/GSM Sensors

  44. Hybrid Algorithms .3 Supervision .3 .1 .6 Raw Sensor Data Clustering Sensor Cues

  45. Basic Hardware (March 00)

  46. Training and Testing (March 00)

  47. Contexts standing running outside Location stairs walking sitting kitchen talking Hardw Lab NN Lab Activity

  48. Context as a service • Context Toolkit (Georgia Tech) • SitComp (Device/person centric) • Technology for Enabling Awareness (Starlab et al).

  49. Context Awareness

  50. Enabling Technologies Overview

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