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Office Activity Awareness. Ian Li Machine Perception Spring 2005. Activity awareness can be good. Awareness of how one uses time in the office can be useful Manage activities, coordinate interaction with others, and assess your own productivity
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Office Activity Awareness Ian Li Machine Perception Spring 2005
Activity awareness can be good • Awareness of how one uses time in the office can be useful • Manage activities, coordinate interaction with others, and assess your own productivity • But, too much to remember and recording can be tedious
Computers can help • Delegate recording of activity to computers • Can monitor daily • Can store activity for months and years • User can focus on analyzing the information at the end of the day or week
What did I do? • System for office activity detection • Applied system for “productivity” assessment
What is the result? • System can reliably detect activity in the office environment (87%-93%) • System can somewhat match the users’ measurements of their own “productivity” (up to 74%)
The rest of the talk… • System: activity detection • Application: “productivity” assessment • Future work
Sensors for detecting activity Sensors Extracted Features Amount of motion Sound level Using mouse or keyboard? Activities detected Walking Sitting/standing Sitting & talking Not in space Talking Not talking Using mouse Pressing keys Not using computer
Ground truth for activity detection • Took snapshot every half minute sitting not in space walking sitting & talking? sitting & talking
Activity can be detected accurately • Using microphone and camera features
Applying to productivity awareness • Can we measure productivity by looking at activities? • How aware are people of their own productivity?
Recording productivity • Measurement of productivity • What percentage of the past 15 minutes did you spend actively engaged in a work-related task? • “Experience sampling” technique • Every 15 minutes the timer plays a bird sound Bird sound
Using knowledge of activity is okay for detecting productivity
Using raw features is slightly better for detecting productivity!
Future work • Longer deployment of the system • How many features are sufficient to predict productivity? • Use temporal model (e.g., HMMs) • Activity-oriented vs. task-oriented measurement of productivity • Other applications of activity awareness • Setting goals and monitoring completion of goals
Office Activity Awareness http://www.cs.cmu.edu/~ianl/16899/ will be up by March 13th for more details or contact me at ianli@cmu.edu Ian Li Machine Perception Spring 2005
Acknowledgements • Software development help from Bilge Mutlu and James Fogarty • System deployment participants: Anind Dey, Jason Hong, Bilge Mutlu, and Pedram Keyani