1. Indoor-Outdoor
Positioning and Lifelog
Experiment with
Mobile Phones

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. Outline
 Introduction
 System Architecture
 Lifelog Experiment
 Conclusion

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. System Architecture
 Outdoor Positioning with GPS
 Bluetooth Indoor Positioning System
 Behavior Recording Software

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. Outdoor Positioning with GPS

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. Bluetooth Indoor Positioning
System

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. Behavior Recording Software

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. Lifelog Experiment (2/5)

14. Lifelog Experiment (3/5)

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. 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. 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