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A Survey of Context-Aware Mobile Computing Research

A Survey of Context-Aware Mobile Computing Research. Guanling Chen and David Kot Department of Computer Science Dartmouth College Dartmouth Computer Science Technical Report TR2000-381. Outline. About context Context-aware computing/application Context sensing Context modeling Issues.

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A Survey of Context-Aware Mobile Computing Research

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  1. A Survey of Context-Aware Mobile Computing Research Guanling Chen and David Kot Department of Computer Science Dartmouth College Dartmouth Computer Science Technical Report TR2000-381

  2. Outline • About context • Context-aware computing/application • Context sensing • Context modeling • Issues

  3. Example - Conference Assistant • Group: Future Computing Environments (FCE) at the Georgia Institute of Technology. • Passive context: current activity (presentation). • Active context: Attendee’s location, current time, schedule of presentations. • Description: Whenever a user enters a presentation room, the Conference Assistant automatically displays the information of the presentation, e.g. presenter, title of the presentation

  4. Definition & classification of context • the set of environmental states and settings that either • determines an application’s behavior  Active context • in which an application event occurs and is interesting to the user  Passive context • Low level context : e.g. time, location, pressure • High level context : e.g. current activity

  5. Context-aware computing • Active context awareness • an application automatically adapts to discovered context, by changing the application’s behavior. • Calm technology • Passive context awareness • an application presents the new or updated context to an interested user or makes the context persistent for the user to retrieve later.

  6. Context sensing • Low level context sensing • location : GPS, IR, etc… • orientation • time, temperature, pressure • etc… • High level context sensing • Activity • Machine vision based on camera tech & image processing • Combine several low-level context (AI)

  7. Context Sensing - Location • Outdoor • GPS (Global Positioning System) : accuracy of 10~20 meters • Indoor (GPS doesn’t work well) • Based on IR, RF, ultrasonic • Cellular approach • Non-cellular approach • Hybrid • Based on network domain • GUIDE • Use Mobile-IP protocol (Foreign Agent)

  8. Sensing context changes • Polling • How to decide polling rate ? • By people’s experience • Automatically sync with changes : saving the battery

  9. System infrastructure • Decouple the context sensing part and application • Message passing • Centralized architecture • The simplest way • Client and server : communicate by RPC • Scalability problem • Distributed architecture • Wireless communication • Wireless cellular networks • Wireless LAN • Wireless PAN or BAN

  10. Issues • Two approach of indoor location sensing • The system monitor beacons from mobile devices, and the mobile device queries a central database to get the current location • The mobile device passively listens to beacons from the cell base-station, and queries a local database for its current location. • Privacy issue in the two approaches

  11. Modeling the context • Why? • Location • Symbolic : abstract symbol • Geometric : coordinate • For general context • Key-value pairs • Tagged encoding : e.g. XML • Object-oriented model : often used in location • Logic based model : ER model by prolog

  12. My comments • Good for beginner to understand all about “context” • Widely introduce but not detailed

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