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User Aware Desktop

User Aware Desktop. CSE 591: Ubiquitous Computing. Syed Toufeeq Ali Ahmed Sandhya Durvasula Krishna Venkatasubramanian. Outline. The following topics are covered: Motivation. Project Definition Architecture of the system Design Application Prediction Results Conclusion Future Work.

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User Aware Desktop

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  1. User Aware Desktop CSE 591: Ubiquitous Computing Syed Toufeeq Ali Ahmed Sandhya Durvasula Krishna Venkatasubramanian

  2. Outline • The following topics are covered: • Motivation. • Project Definition • Architecture of the system • Design • Application Prediction • Results • Conclusion • Future Work

  3. Motivation • To explore the idea of context awareness. Specifically • Location context. • Functional context. • To solve certain privacy issues by being context aware. • To study the minimization of user distraction and develop a working model that demonstrates the aforesaid.

  4. Project Definition • To develop a “user aware desktop” that finds a users location using a system of sensors and performs appropriate functions. • The stress is on securing the system from malicious users. • To develop a system that knows which application the user is most likely to open, by being ‘proactive’.

  5. Architecture of the system User with a tag Desktop User with a tag Sensor System Desktop User with a tag Wireless link Desktop User with a tag

  6. System Design

  7. Region definition • Region R1 (‘activity’ region) • R1 is the region closest to the machine, which is the active area where the user can work on the system. • Region R2 (‘proximity’ region) • R2 is the passive region of the room with respect to any activity on a system. This is the regions of the room that is not in regions R1 of any other system.  • Region R3 (‘away’ region) • Region outside the room is considered as R3.

  8. Room Layout (grid not shown)

  9. Design Diagram Login Module Machine Lock Module Central Module User list Screen Saver Module Taskbar Module Receiver Module Named pipe Application Prediction Module Sensor System Application History

  10. User in Region Action taken R1 Log the user on to the machine User in Region Action taken R2 Start screen saver R3 User in Region Action taken R1 Unlock machine Event- Action tables Case 1: User is not logged onto any machine, then: Case 2: User logged into a system and moves away to: Lock the computer and start timeout Case 3: Machine is locked, user moves to:

  11. User in Region Action taken R3, R2, R1 User in Region Action taken R1 R1 Nothing (if no, keyboard/ mouse event) Display unlock screen (mouse or keyboard pressed) Event- Action tables (contd…) Case 4: Machine on screen saver mode, if Bob (wrong user) comes to: Nothing Case 5: Machine locked (Alice logged in), Bob (wrong user) comes to:

  12. Application prediction • How does it work ? • It keeps track of applications the user opens and the amount of time the user uses it. • The higher number of times an application is opened or the longer the application is running, the higher the probability that it will be used by the user. • The system prompts three application to the user, based on the criteria given above.

  13. Results • Keeping our motivation of • Location context awareness • Functional context awareness • Minimizing user distractions in mind we have developed a prototype of our “user aware desktop” system.

  14. Screen Shots

  15. User Login Screen with the sensor application screen.

  16. Taskbar Screen with the three applications and logoff button. (It is in auto-hide mode)

  17. Screensaver Screen with the sensor application window opened up

  18. Locked Screen, only when user is in region 1 can this screen be removed

  19. Conclusion • Context Awareness can be used to reduce many inherent privacy problems. • Desirable features for one person can be a distraction for another person. • User distraction can be minimized to only a certain extent.

  20. Future Work • The system could be extended by handling other forms of contexts (temporal context for example). • Extend the application prediction to all the applications on a machine and adjust automatically as applications are installed/removed. • Speech Recognition could be used to minimize user distraction even further.

  21. Thank You

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