Indoor-Outdoor

Positioning and Lifelog

Experiment with

Mobile Phones

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

Outline

Introduction

System Architecture

Lifelog Experiment

Conclusion

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

System Architecture

Outdoor Positioning with GPS

Bluetooth Indoor Positioning System

Behavior Recording Software

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

Outdoor Positioning with GPS

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

Bluetooth Indoor Positioning

System

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

Behavior Recording Software

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

Lifelog Experiment (2/5)

Lifelog Experiment (3/5)

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

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%

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