GPS MOBILE PHONE-BASED ACTIVITY DIARY SURVEY
Nobuaki OHMORI
Lecturer
Department of Urban Engineering
The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo,113-8656 Japan
Fax: +81-3-5841-8527
E-mail: nobuaki@ut.t.u-tokyo.ac.jp

Morimichi NAKAZATO
Graduate Student
Institute of Environmental Studies
The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo,113-8656 Japan
Fax: +81-3-5841-8527
E-mail: nakazato@ut.t.u-tokyo.ac.jp

Noboru HARATA
Professor
Department of Urban Engineering
The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo,113-8656 Japan
Fax: +81-3-5841-8527
E-mail: nhara@ut.t.u-tokyo.ac.jp
Abstract: Activity diary is necessary information to investigate the relationships between
individual travel behavior and activity engagement. A GPS mobile phone-based activity diarysurvey system is developed in this study. The software programmed in Java works on mobile
phone devices for entering information on activity diary. Positional data are automaticallycollected at regular intervals by GPS-equipped mobile phones. Two pilot surveys are
conducted for a total about 50 participants to examine the advantages of the survey system.
By comparing activity data collected by the software with the data collected by conventional
paper-based activity diary surveys, it is found that the system developed in this study is usefulin terms of reducing “time lag” in data entry and mitigation of spatial constraints for data
entry. However, the respondent’s burden depends on the characteristics of the respondents.
Key Words: GPS, mobile phone, activity diary survey
1. INTRODUCTION
Travel is considered a demand, derived from the desire to engage in activities at certain
locations. Hence, activity diary data are necessary information to analyze individual
activity-travel patterns and to investigate the relationships between individual travel behavior
and activity engagement. Recently, the importance and effectiveness of activity diary data has
been recognized again for evaluating the effects of policy options on individual quality of life
in urban space and time. The most common survey method of collecting activity diary data
has been a paper-and-pencil interviewing (PAPI). Respondents are asked to fill paper-based
activity diary questionnaire sheets for a day or some successive days (two days, one week,etc.). However, there are several problems with this traditional survey method. First, becauseof the great amount of time it takes for respondents to fill in the activity diary sheet, therespondents’ burden is considerably large to record all of the activities in the questionnaire
survey sheet. Since most respondents tend to record the activities engaged in for the survey
day after going back home at night, data accuracy about activity type, start/end time andlocation, depends mostly on their memory retention. As for the surveyors, it takes

considerable time and money for distributing and collecting survey materials and for editing
and inputting collected data. For the innovation of survey methods for activity data collection,a lot of researchers are trying to reinvestigate the existing technologies and to develop new
survey methods (Stopher and Jones, 2003).
In recent years, people can make decisions on activity scheduling and travel behavior more
dynamically than before, by acquiring information on transport systems and activity
opportunities both pre-trip and en-route from various media. Consequently, not only revealed
activity-travel patterns but also activity scheduling process has been an interest oftransportation researchers. Some researchers have been doing research on the development ofcomputer software for data collection of activity patterns and scheduling process, e.g. CHASE(Doherty and Miller, 2000) and React! (Lee and McNally, 2001). CHASE and React! arecomputer-assisted self-interviewing (CASI) systems working on PC. Personal digitalassistants (PDA) and mobile phone can be also used as a device for data collection (Zhou andGolledge, 2004; Doherty and Papinski, 2004). On the other hand, the use of
telecommunications such as mobile phone, e-mail and the Internet, affects individual travel
behavior. To analyze interaction between telecommunications and activity-travel
scheduling/patterns, information not only on activity diary but also on the use of
telecommunications is required. However, methods applied for collecting effectively suchkind of data remain uninvestigated research topics. Recently, in the field of activity-travel
surveys, positioning technologies such as global positioning system (GPS) and global system
for mobile communications (GSM) have been widely applied to collect detailed information
on travel trajectory. The technologies make it possible to automatically collect position(longitude and latitude) and time (and speed for GPS) at a specific interval. To collectpositional data using GPS and GSM, respondents are just required to carry the device. There
has been a lot of research on travel data collection using GPS and GSM (e.g., Murakami et al.,
1999; Draijer et al., 2000; Ohmori et al., 2000; Asakura and Hato, 2004; Arimura, 2004). GPS
can be attached to PDA and recently is installed also inside the mobile phone device (seeKDDI website). PDA and mobile phone have been also used for data collection as CASI in awide variety of survey field. Especially, most of the younger people are routinely using
mobile phone for voice and e-mail communications, and they have less difficulty in operating
the devices than elder people. Investigating possibilities of the survey system combined
positioning technologies and mobile device for activity diary data collection could be
important in terms of mitigating the problems in activity diary surveys.
The objectives of this study are to develop GPS mobile phone-based activity diary survey
system, and to examine its advantages and disadvantages over conventional surveys, bycomparing data collected by the mobile phone survey with those collected by theconventional paper-based survey, and by analyzing participants’ preferences in between two
survey methods.
2. DEVELOPMENT OF GPS MOBILE PHONE-BASED ACTIVITY DIARY SURVEYSYSTEM
2.1 Selection of the System Platform for Data Collection
The requirements of the survey system in this study are as follows:- to directly collect electronic data on activity diary and to transmit the data through awireless network (GSM network and the Internet);-to use a mobile device which people can easily carry in their daily life, so that they canenter information on activity diary into the device at anytime and anyplace without spatial
and temporal constraints;
to automatically collect positional data at a regular time interval to specify activity
locations and travel routes; andto reduce survey cost of time and money both for distribution and collection of survey
materials, and for transmitting, editing and inputting the collected data.

Table 1 summarizes comparison among system development platforms. Mobile phone, PDA
and laptop PC are possible options of mobile electronic devices for data collection. The
monetary cost for data transmission from the device to the surveyor (or a dedicated server) is
cheaper for a laptop PC with Internet access than mobile phone and PDA with a mobile
connection. The laptop PC is the best for respondents to enter activity information in terms of
the size of monitor display. However, it would be less convenient for respondents both tocarry and to enter activity information anytime and anyplace. Mobile phone and PDA are
smaller devices and easier to be carried. The mobile phone has a smaller monitor and lessflexibility for the design of data entry form than PDA, but the number of mobile phone users
is much higher than that of PDA users in Japan – the number of subscribers is about 90
million for mobile phones including PHS, but the number of PDA users would be less than 10
million. From the above reasons, we applied mobile phone for the platform of systemdevelopment.
Table 1. Comparison among Devices for Activity Diary Data Collection
Mobile phone
PDA
Laptop PC
Monetary cost for data
dependent onHigh
Lowtransmission
attached media
Size of monitor display
Small
MediumLarge
Easiness to be carried
Easy
MediumDifficultSpatial constraints for data
Low
Low
High
entering
Flexibility for the design of
Low
MediumHighdata entry form
The dissemination in people
High
Low
High
There are 4 mobile phone carriers in Japan; NTT DoCoMo, Inc., KDDI Corporation, TU-KA
Cellular Inc. and Vodaphone K. K. At the time this research was launched into, the only
carrier, “au” by KDDI Corporation, that provided mobile phone devices with GPS installed.
The “au” employs “gpsOne” which is called the Assisted GPS (see SnapTrack website). It
calculates the current position using not only GPS but also information on received signal
from multiple base stations to which the mobile phone device is connected. Therefore,
positional data can be collected even if GPS was not available because of obstructed view ofGPS satellites (e.g. inside buildings, at underground stations, etc.) or carried along in coat orjacket pockets. Furthermore, end users can develop original Java application working in the“au” mobile phone device and distribute it without getting permission from KDDI
Corporation. Therefore, we employed the “au” mobile phone system among the four carriers.
2.2 Development of GPS Mobile Phone-Based Data Collection System
We developed software in the Java language so that respondents can download the software

via web and install it in their own mobile phone. This freed the surveyor from having tocontact the respondents to distribute the software. Also the respondents did not need to carry
two mobile phone devices; one for the survey and another for their own use. When starting
the software, information on position specified by GPS and ID number is transmitted
automatically to a dedicated server at regular time intervals and stored. The time interval canbe set in the sauce file arbitrarily. For entering information on activity diary (activity type,start/end time, location, travel mode and accompanied persons) and telephone use (time,
media, partner, send/receive and the contents for communications), data entry form wasprogrammed as shown in Figure 1.
Respondents enter start/end time directly by pushing dial buttons (see Figure 1). Informationon activity type, location, travel mode and accompanied persons is selected from thepredefined list. If appropriate alternative does not exist in the predefined list, respondents
directly enter their response in the blank cell. As soon as the respondent finishes entering
information on an activity, the time is also automatically recorded to analyze “time lag”
between activity implementation and activity recorded. The end time of the previous activity
is automatically set as the start time of the next activity. Error checking functions test thevalidity of the start/end time (e.g. whether the characters are number and between 3:00 to
27:00 (3:00 a.m. on the following day), whether the start time is earlier than the end time).
When the entered information is not correct, it displays a warning message. Respondents canconfirm the entered information at anytime, and they can modify the data if they found somemistakes. The diary data is temporarily stored in the mobile phone. When the capacity of themobile phone’s built-in memory reaches full, by pushing two buttons, the data is transmitted
via e-mail to the surveyor’s e-mail address. The surveyor can identify the data by accessing
the server computer through the Internet in real time.
Since positional data is transmitted only while the software is running, respondents must
always keep the software running during the survey period. When the respondents use theirown mobile phone for the survey, they can receive phone call and e-mail while the software is
running. However, they need to end the software to make phone calls and send e-mail, andrestart the software after finishing it. When the battery level goes below a specific level, thesoftware automatically exits. This function can avoid data deletion stored in the mobile phonedevice if power suddenly runs out.
The 1st survey was conducted using this software as described in the next chapter. After the 1st
survey, we improved the software for some functions. The 1st version of the software required
respondents to select one activity type from 16 alternatives (or enter the name of activity only
when select “others”), whereas in the 2nd version, the name of concrete activity type wasentered directly from dial buttons. Activity data was transmitted by HTTP in the 2nd version,
so respondents’ operation to send data became easier (from pushing two buttons in the 1stversion to one button in the 2nd version). In the 1st version, the surveyor needed to manuallycombine the activity data of each respondent sent by e-mail, because the respondent must
send the data two or three times in a day. On the other hand, in the 2nd version, transmitted
data are automatically added to one data file in the server computer. Outline of the datacollection system is shown in Figure 2.

Start time
End time
Activity type

Scroll button

Dial buttons
Figure 1. Snapshot of Data Entry Screen in the 1st Version of the System“au” mobile phone
network and the Internet
Transmission of
positional data andactivity diary data

Server computer

GPS satellites“au” GPS mobile phone device

Figure 2. Outline of the Data Collection System

3. ACTIVITY DIARY SURVEY USING THE GPS MOBILE PHONE DEVICE
To examine the advantages and disadvantages of the mobile phone-based activity diary survey

over the conventional paper-based activity diary survey, two pilot surveys were conducted in
January and April 2004 for a total about 50 participants living in Tokyo.
As the 1st survey, in January 2004, two-day activity diaries were collected. The number of the
respondents of the survey was 38. Thirty three of them were 20’s years old and 3 of themwere 30’s. Thirty one respondents were male. All the respondents were daily using a mobile
phone. The average history of mobile phone use was 4.9 years. The respondents were asked tostart the software when they wake up and to exit it when they go to sleep in order to save GPS
tracking costs. They were asked to record activity diaries both in the mobile phone softwareand in the conventional paper-based questionnaire sheet on the same day. For the paper-based
survey sheet, they were also required to record the date and time when they recorded activities
in the survey sheet. This information was used for analysis of “time lag” between activity end
time and data entry time. Total 8 of 38 respondents were daily using “au” mobile phone inwhich the survey software was able to work (type A5xxx or W1x). They were asked to use
their own mobile phone and to download the survey software from the survey website (“auusers” in this study). Then, a survey manual and a paper-based questionnaire sheet were
mailed to them. The “au users” were not contacted by the surveyor in face-to-face. On theother hand, the “au” mobile phone (type A5402) with pre-installed survey software wasprovided to the respondents who were not using “au” mobile phones (“au non-users”). The“au non-users” were asked to carry it in addition to the mobile phone they were personallyusing. They were instructed by the surveyor how to use the device in face-to-face. On the 1stday, the respondents were asked to record their activity diary, whereas on the 2nd day, they
were asked to record not only their activity diary but also their telephone use diary.
The 2nd survey was conducted using the 2nd version of the system in April 2004 for 13
participants who were all graduate students in The University of Tokyo. The authors had
developed a GIS-based activity-travel simulator, SMAP-E, and applied to a graduate course
for the purpose of instructing students to better understand activity-travel behavior under
spatio-temporal constraints (Ohmori et al., 2003; Ohmori et al., 2004). One-week activity
diary data required for input to SMAP-E had been collected by conventional paper-based
surveys. This 2nd survey was also a trial to collect activity diary data by mobile phone for
input to SMAP-E. All the 13 respondents were “au non-users,” so the “au” mobile phonewhich the surveyor prepared was provided to them during the survey period. The respondents
were asked to record activity diary in the mobile phone for three days and in the paper-basedquestionnaire sheet for the remaining four days. Telephone use diary was not recorded in the
2nd survey.
Time interval of GPS tracking was set at 10 minutes. Battery can keep the mobile phone
working for 5 to 6 hours under this setting. It took about 900 yen for one day data collection
for one respondent, including costs for both transmitting the data and GPS tracking. After thediary survey, the respondents were asked to answer some questions regarding comparison
between the mobile phone-based survey and the paper-based survey. The survey description issummarized in Table 2.

Number of respondents
Information collected
Survey media

Mobile phone software

Table 2. Survey Description
1st survey
2nd survey
38
13
1st day: activity diary
One week: activity diary
2nd day: activity diary andtelephone use diary
2nd day-4th day: mobile phone
1st day and 2nd day: mobile
phone software & paper-based software
survey sheet
1st and 5th-7th day: paper-based
survey sheet
1st version
2nd version

4. COMPARISON BETWEEN MOBILE PHONE AND PAPER-BASED SURVEY
METHODS
4.1 Comparison of Diary Data between Mobile Phone Survey and Paper-Based Survey
Data handling time of the surveyor
Data handling time to complete an electronic database was much less in the mobile phonesurvey than in the paper-based survey. In the 1st survey, it took about 3 minutes at minimum
for the surveyor to input two-day activity diary data of one respondent, from the paper-based
survey sheet into an Excel sheet. Whereas, it took only 30 seconds to combine two-day
activity diary data sent by e-mail from the mobile phone device and to make an Excel sheet
for one respondent. It was found that time required for editing and inputting the data wasconsiderably reduced in the mobile phone survey, comparing with the conventional
paper-based activity diary survey. In the 2nd survey, the respondents themselves input four-day
activity diary from the paper-based survey sheet into an Excel sheet. The instructor of thegraduate course managed the data handling of three-day activity diary data collected by themobile phone system and sent the data to the respondents.
Characteristics of the recorded data
In the 1st survey, the average number of the recorded activities in the mobile phone was
15.0/day and that of trips was 2.8/day. There was not significant difference in the number ofrecorded activities and trips between the mobile phone and the paper-based diary. However,there were some problems in the data collected by the mobile phone as:- two consecutive activities overlapped in timing;- existence of blank time period; and- not recorded several in-home activities.
Total 69 activities recorded in the paper-based diary were not recorded in the mobile phone.
Twenty-seven of them were “sleep” activities. For the remaining 42 activities, 24 of themwere in-home activities and 21 of them were activities engaged in midnight. On the other
hand, total 35 activities recorded in the mobile phone were not recorded in the paper-based
diary. Most of the activities were relatively short-time activities. In the 2nd survey, the average
number of the recorded activities in the mobile phone was 12.1/day and that of trips was
3.7/day.
Frequency of data entry
Frequencies that the respondents entered information on activities were compared in between
the mobile phone and the paper-based diary. In the 1st survey, the average number for thepaper-based diary was 2.1/day and that for the mobile phone was 8.1/day. There was no
respondent who recorded data more frequently in the paper-based diary than in the mobile
phone. This means the respondents recorded activities more frequently in the mobile phonethan in the paper-based diary. This could be due to the higher flexibility in space and time forrecording data in the mobile phone survey. In the 2nd survey, the average number of thefrequency of data entry was 3.7/day for the mobile phone. The respondents were not required
to record data entry time for the paper-based diary in the 2nd survey.

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

mobile phone,
1st survey
paper-based,
1st survey

601<

481-600

361-480301-360

241-300

181-240

91-120121-180

61-90

46-60

31-45

26-30

21-25

16-20

11-15

6-10

0-5

mobile phone,
2nd survey<0% of cumulative number ofrecorded activities“Time lag” between activity implementation and data entry
Figure 3 shows cumulative distribution of “time lag” from the end time of an activity (activity
implementation) and the time when the activity was recorded. As shown in the figure, “timelag” was shortest in the mobile phone of the 1st survey and largest in the paper-based diary of
the 1st survey. The averages of the mobile phone of the 1st survey, mobile phone of the 2nd
survey and paper-based diary of the 1st survey were 87 minutes, 179 minutes and 445 minutes,
respectively. In the mobile phone of the 1st survey, 39.6% of the total activities were recorded
within 5 minutes after the activity implementation, whereas 26.6% of the total activities wererecorded after 600 minutes (10 hours) in the paper-based diary of the 1st survey. Higher
frequency and shorter “time lag” suggests that respondents can enter activity information into
the mobile phone software at anytime and anywhere, and from clearer memory, so data
accuracy could be higher than traditional paper-based survey. Intriguing result is that about
10% of the activities in the mobile phone of the 1st and 2nd surveys were recorded before theactivity was finished. But in terms of inter-personal variability, the average, minimum,
maximum of each respondent’s average “time lag” was 105 minutes, -12 minutes and 895
minutes, respectively, and the standard deviation of all the respondents’ average “time lag”
was 153 minutes. Thus, the “time lag” was much dependent on individuals. In the 2nd survey,
the average, minimum, maximum of each respondent’s average “time lag” was 200 minutes,
13 minutes and 524 minutes, respectively. Difference of “time lag” between the mobile phone
diaries of the 1st and 2nd surveys could be due to difference in survey method and software,
but we cannot know the specific reason from this study.

time lag (min.)Figure 3. Time Lag between Activity Implementation and Data Entry
Locations where data were recorded
As shown is Figure 4, in terms of locations where activities were recorded, in the paper-based
diary of the 1st survey, 67% of the activities was recorded in their home and 32% was in theirwork or school place. Only 1% of the activities in the paper-based diary was recorded whiletraveling. On the other hand, 47% of activities in the mobile phone of the 1st survey wasrecorded in their home, 22% was in their work or school place and 11% was in other locations.
About 20% of the activities was recorded while traveling, of which, 10% was traveling bytrain, 5% was walking and 1.5% was while riding bicycle. In the mobile phone of the 2nd
survey, 35% of the activities was recorded in their home, 35% was in their school place and
20% was in other locations. 35% was recorded while traveling of which 21% was traveling bytrain, 7.5% was walking and 2% was while riding bicycle. The results show that the mobile
phone makes it possible for the respondents to enter activity diary information without spatial
and temporal constraints.

mobile-phone,
2nd survey

homework orschool placeotherlocationswhile travelingmobile-phone,
1st survey

paper-based,
1st survey
0%

20%

40%

60%

80%

100%

Figure 4. Locations Where Data Were Recorded
4.2 Respondents’ Preference in Different Survey Methods
This section presents the analysis of the respondents’ answers for the survey methods after theactivity diary survey was finished.
Effects of the Mobile Phone Survey on the Respondents’ Behavior
Three respondents in the 1st survey answered that they were conscious of being positioned
automatically by GPS. Fifteen of them answered that their activity-travel behavior and mobile
phone use were at least affected by participating in the survey. Some respondents took into
consideration the battery capacity of the mobile phone device, so they did not travel further
than usual from their home and office or school. For the participants who used their own
mobile phone, since they had to stop the system to make a phone call or to send e-mail, they
communicated less with the mobile phone than normal usage. Automatic positioning andbattery problems could cause a little different activity-travel behavior from the normal pattern.
Perceived time to complete data entry
To investigate respondent burden, the respondents were asked which survey method, mobile
phone or paper-based diary, took longer time to complete data entry of the activity diary.
Table 3 shows the result. For the “au non-users” of the 1st survey, although 30% of the
respondents answered that it took shorter time in the mobile phone to complete data entry,
40% of them felt that it took longer time in the mobile phone survey. It was found that
respondent burden would depend on each respondent’s characteristic and her/his mobile
phone literacy. For the 2nd day which required to record telephone use diary, more respondents
felt time longer in the mobile phone.

Table 3. Respondents’ Perceived Time to Complete Data Entry (the Number of the
Respondents)“au non-users”“au users”
stnd
st
1 day 2 day 1 day 2nd day
Shorter in the mobile phone
9
7
3
3
Same
10
9
0
0
Longer in the mobile phone
11
14
2
3
N/A
0
0
1
0
5. CONCLUSION
GPS mobile phone-based activity diary survey system was developed as an intelligent survey
method for collecting activity diary data. Pilot studies were conducted to compare datacollected by the mobile phone software with data collected by the conventional paper-basedquestionnaire survey. From the comparative analyses, the following results were found:- Data handling time of the surveyor for data analysis was considerably reduced in themobile phone survey comparing with the conventional paper-based activity diary survey.
- Frequency of data entry was larger in the mobile phone survey than the conventional
survey and “time lag” between activity implementation and data entry was shorter in themobile phone. This could be the advantages from flexibility in space and time forrecording data.
- Battery consumption in the mobile phone software affected the respondents’
activity-travel behavior. The use of telecommunications by mobile phone was also
affected for own mobile phone users.
- Respondents’ burden would depend on their characteristics and mobile phone literacy inthe mobile phone survey.
The authors have been developing an integrated system for data collection, analysis andevaluation of individual/household activity-travel patterns using information andcommunications technologies, and GIS (Urban Transportation Research Unit, 2004). In thissystem, activity diary and travel trajectory are the input data for the GIS-based activity-travel
simulator. There remain more improvements in the software developed in this study towards
more user friendly system and more accurate data collection. In the near future, GPS mobile
phone-based survey could be used to complement or substitute the conventional paper-basedor PC-based activity diary survey methods. Complementation means to use mobile device as amemory jogger for recording out-of-home activities and travels. Substitution means no needof paper-based questionnaire survey sheet. Graphical representation of the current position
and travel trajectory on the mobile phone monitor display using GIS map could contribute toincreasing respondents’ interest, motivation and willingness to participate in the survey.
ACKNOWLEDGEMENTS
The authors gratefully thank to Dr. Yusuke Konishi of Center for Spatial Information Sciences(CSIS) in the University of Tokyo, who developed the original Java program of automatic
GPS data collection for “au” mobile phone system, and KDDI Corporation for supporting thesurveys.

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