IM Power Project Summer 2007 Raye Gomez April Wensel Heather Tomko Jen Mankoff (mentor) Anind Dey.
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Transcript of IM Power Project Summer 2007 Raye Gomez April Wensel Heather Tomko Jen Mankoff (mentor) Anind Dey.
![Page 1: IM Power Project Summer 2007 Raye Gomez April Wensel Heather Tomko Jen Mankoff (mentor) Anind Dey.](https://reader036.fdocuments.us/reader036/viewer/2022070605/5a4d1aea7f8b9ab05997a7cf/html5/thumbnails/1.jpg)
IM Power ProjectIM Power ProjectSummer 2007Summer 2007
Raye GomezApril WenselHeather TomkoJen Mankoff (mentor)Anind Dey
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GoalsGoals
Motivation reduce the amount of idle time to
decrease carbon emissions (i.e. ecological footprint)
Determine Average user idle time Reasons for idle time How to cause user reduce idle time
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Set-UpSet-Up
Subjects Completed two week monitoring: 50 Laptop users: 40 Desktop users: 10 Completed study:
~30 laptop users desktop users TBA
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Set-Up (cont.)Set-Up (cont.)
Randomly chosen for interview: 15 so far: 8 laptop users, desktop users TBA
8 laptop interviewees also gave preliminary opinions on feedback devices
All subjects Bot diary on last day Daily survey each night before logging off
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Daily SurveyDaily Survey
Were you logged onto primary your computer while online today? If not, at what times?
How many hours did you spend using the computer?
What was the shortest/longest amount of time that you stayed online?
How long was your computer performing assigned tasks requiring no input (i.e. virus scan)? How long was it not?
What power mode was your computer in today? Describe all the times that you went idle and why. What programs were you running today?
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Bot DiaryBot Diary
Every time a user came back from idle on last day:
Hello, it looks like you just returned from being idle. What were you just doing just now? What was your computer doing this
time?
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Information We Were Looking ForInformation We Were Looking For
Time of status changes Frequency and duration of idle times User awareness
when they were idle what their power settings were what programs they were running.
Interviews to get more in-depth information about reasons for idle time
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Our Findings - General SurveysOur Findings - General Surveys
95% of users run their computer on AC.
Biggest motivators for energy saving Money Altruism
About half of users use automatic standby/sleep setting
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Our Findings - Interviews Our Findings - Interviews (Daily Surveys and Logs)(Daily Surveys and Logs)
Most idle time for short periods (i.e. eating, cooking, bathroom, phone, etc.)
The average user believes turning the computer off extends
the life of the machine leaves their computer on for easy access
Most common running programs: web browser, followed by the email client
Most users run a screen saver, but only about half run anti-virus software
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SuggestionsSuggestions
For those running nothing while idle: roughly 85% "Consider turning your computer off when you
won't be using it for 30 minutes or more." (roughly 50%)
"Turn off your computer when you go to sleep." (less than 5%)
"Program your settings to automatically put your computer to sleep after 10 minutes of being idle." (roughly 10%)
**The percentage of users in this category that ALWAYS leave their computer in full power mode is about 60%.
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Initial TechnologyInitial Technology
AIM bot Built with AIM SDK in Java Keeps subjects in Buddy List Records status changes of all subjects Accepts commands from experimenter
diary study survey reminders
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Additional TechnologyAdditional Technology
Sensor In Java Records processes, CPU usage, TCP usage Updates database every minute
Logger In Ruby Provides access to database through URL, e.g.
http://impowerwebsite.org/log/:datatype/:userid/ :timestamp/:eventid/:eventname/:notes
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables Modalities Content
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables guilt vs. reward awareness vs. suggestions frequency of feedback historic vs. real time information
Modalities Content
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables guilt vs. reward awareness vs. suggestions frequency of feedback historic vs. real time information
Modalities Content
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables Modalities
window (constant or pop-up) instant message tray icon cell phone text message audio screen saver
Content
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables Modalities
window (constant or pop-up) instant message tray icon cell phone text message audio screen saver
Content
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables Modalities Content
kwh of energy dollars pounds of co2 trees hours
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables Modalities Content
kwh of energy dollars pounds of co2 trees hours
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables Modalities Content
kwh of energy dollars pounds of co2 trees hours
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables Modalities Content
kwh of energy dollars pounds of co2 trees hours
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables Modalities Content
kwh of energy dollars pounds of co2 trees hours
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables Modalities Content
kwh of energy dollars pounds of co2 trees hours
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Phase II – Behavior Change ChoicesPhase II – Behavior Change Choices
Variables Modalities Content
kwh of energy dollars pounds of co2 trees hours
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Tentative PlansTentative Plans
Study effect of personalized suggestions on behavior change
Hypothesis Personalized suggestions will cause greater
change than awareness alone Measure
Energy saving attitudes Surveys, interviews
Idle behavior Bot, sensor
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Tentative PlansTentative Plans
60 participants 1 week baseline 2 weeks with feedback 3 groups
Idle cost Idle cost + generic suggestions Idle cost + personalized updates +
opportunity
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Three Feedback TypesThree Feedback Types
Group 1 No suggestions.
Group 2 Turn your computer off at night.
Group 3 Instead of downloading at night,
download over lunch and turn your computer off at night.
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ComponentsComponents
AIM bot Sends info to logger about user status
changes whenever they happen Sends suggestion to database when
user comes off of idle Feedback program Logger Database
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ComponentsComponents
AIM bot Feedback program
Installed on client machines Sends CPU/TCP usage Retrieves idle time, suggestions, status Window
Logger Database
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ComponentsComponents
AIM bot Feedback program Logger
Provides access to database via URLs as before
Database
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ComponentsComponents
AIM bot Feedback program Logger Database
Stores AIM status and CPU/TCP data
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SuggestionsSuggestions
Hand generated for each user after baseline
AIM bot chooses best Priority during current time period When same suggestion was last sent
Displayed in window
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WindowWindow
Projected annual cost based on today Change from baseline projection Change from yesterday’s projection Suggestion when user comes
back from being idle