Indoor Outdoor

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Indoor Outdoor

  1. 1. Indoor-Outdoor Positioning and Lifelog Experiment with Mobile Phones
  2. 2. Reference  Hiroshi Mizuno, Ken Sasaki, Hiroshi Hosaka “Indoor- Outdoor Positioning and Lifelog Experiment with Mobile Phones” Proceedings of the 2007 workshop on Multimodal interfaces in semantic interaction
  3. 3. Outline  Introduction  System Architecture  Lifelog Experiment  Conclusion
  4. 4. Introduction  With the rapid development of computers and networks, there are many projects on lifelog StartleCam: A Cybernetic Wearable Camera Time-machine Computing: a Time-centric Approach for the Information Environment MyLifeBits: Fulfilling the Memex Vision  Analysis on lifelog data and some useful parameters for predicting user’s next behavior are presented
  5. 5. System Architecture  Outdoor Positioning with GPS  Bluetooth Indoor Positioning System  Behavior Recording Software
  6. 6. Outdoor Positioning with GPS  Mobile phones’ GPS are used to track users’ positions in outdoors  A user starts to find his/her current location, the phone connects to a “recording server”, via the Internet  The recording server works as a web server ,it returns the time at which the phone should send the next positioning data
  7. 7. Outdoor Positioning with GPS
  8. 8. Bluetooth Indoor Positioning System  Personal computers (PCs) in rooms and offices will serve as base stations  When user’s Bluetooth signal from the mobile phone is detected, the base stations make connections with the user’s phone and measure the signal strength  Accuracy of positioning depends on how cluttered the environment is  In ordinary office buildings, this system can identify the room in which the user is present
  9. 9. Bluetooth Indoor Positioning System
  10. 10. Behavior Recording Software  Behavior Recording Software is a Java program that runs on mobile phones  Allows the user to record activities or input supplementary data  When a user pushes a button, a menu of common daily activities appears on the screen to prompt the user  History of the past inputs is shown at the bottom of the screen for check and correction
  11. 11. Behavior Recording Software
  12. 12. Lifelog Experiment (1/5)  76 consecutive days  A college student  User’s activities were classified into five categories: Sleeping Working on a PC Reading Taking a bath Went out  To analyze user’s lifestyle and to find parameters for predicting user’s next activity
  13. 13. Lifelog Experiment (2/5)
  14. 14. Lifelog Experiment (3/5)
  15. 15. Lifelog Experiment (4/5)  “Sleeping” and “Went out” are repetitive at period of 24 hours  “Working on PC”, “Reading”, and “Taking a bath” has no regular time interval  “Working on PC” is random and the time spent on this activity is relatively long  “Reading” is not a daily activity of this person  Interval of “Taking a bath” is longer than 12 hours  Finding: the activities are related with the following three factors:  Current time  Time from wake up  current activity
  16. 16. Lifelog Experiment (5/5)  Using a feature distance defined by equation (1) and applying k-nearest neighbor method, we were able to predict the user’s next activity with probability of 66%
  17. 17. Conclusion  Indoor-outdoor positioning system incorporating GPS and Bluetooth has been developed for lifelog system using mobile phones  Lifelog experiment of 76 days has proved the usability of the system

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