Mobile Phone Networks and the Physical World - Making Things Talk - page 401

Project 31

Personal Mobile Datalogger

One popular reason to develop native
applications on a mobile phone is to use
the phone's Bluetooth radio as a serial
connection to other devices. In this way,
your phone can become a mobile data-
logger , or a conduit to send the data to a
database on the Internet. In this project,
you'll sense your Galvanic skin response
using an Arduino, send the data via
Bluetooth to your Android phone, and log
the result to a file on the Internet.

MATERIALS

» Android device
» LilyPad Arduino Simple
» bluetooth Mate
» Lithium Polymer Ion battery
» 1 resistor, 270-kilohm
» Conductive ribbon
» Conductive thread
» Shieldit Super 14” fabric
» Velcro
» Hoodie
» Embroidery thread

A growing number of personal data enthusiasts are
gathering personal biometric data for many different
purposes, from visualizing their activity patterns in
order to improve exercise habits, to tracking sleep
patterns in order to find solutions to insomnia. Quan-
tified Self meetups ( http://quantifiedself.com ) are
popping up around the world for people to share tips
and tricks on how to do this, and devices like the
FitBit ( www.fitbit.com ) and the Zeo ( www.myzeo.
com ) have come on the market to make biometric
tracking easier.

Feel free to change the sensor for whatever you want to
track yourself.

Figure 10-17 shows the system for this project. A micro-
controller reads the analog voltage from the sensor and
sends it serially to a Bluetooth Mate. The data is then
transmitted over Bluetooth to a mobile phone using the
Serial Port Profile , or SPP , that you used in other Bluetooth
projects in this topic. The phone then makes an HTTP GET
request to a PHP script on a web server. The script saves
the incoming data to a file. What you do with the data from
there is up to you.

This project is based on the work of ITP alumnus
Mustafa Ba ğ datlı, shown in Figure 10-15. Mustafa
wanted to track his Galvanic skin response (GSR) and
heart rate against his calendar, so he could see when
his mood—as reflected in his heart rate and GSR—
were affected by the events of the day. His project,
Poker Face, tracked the two biometric characteristics
on a LilyPad Arduino, transmitted them via Bluetooth
to a mobile phone, and logged the result on the Web.
You can find more on Poker Face at http://musta-
fabagdatli.com In this project, you'll build the same,
but without the heart rate sensor to keep it simple.

Figure 10-16
Mustafa Ba ğ datlı wearing Poker Face, a biometric
datalogger linked to a mobile phone. Photo
courtesy of Mustafa Ba ğ datlı.