MP16-899 Office Activity Awareness

Ian LiMachine PerceptionSpring 2005

MP16-899 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

MP16-899 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

MP16-899 What did I do?

• System for office activity detection

• Applied system for “productivity” assessment

MP16-899 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%)

MP16-899 The rest of the talk…

• System: activity detection• Application: “productivity” assessment• Future work

MP16-899 Sensors for detecting activity

Walking

Sitting/standing

Sitting & talking

Not in space

Activities detected

Amount of motion

Extracted Features

Sensors

Using mouse

Pressing keys

Not using computer

Using mouse or keyboard?

Talking

Not talking

Sound level

MP16-899 Data collection tool

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

MP16-899 Ground truth for activity detection

• Took snapshot every half minute

not in space walking

sitting & talking

sitting & talking?

sitting

MP16-899 Activity can be detected accurately

• Using microphone and camera features Recall

Accuracy Classifier Outside Sitting Sit&Talk Walking

Prof 1 Day 1 88.0412 Bagging (REPTrees) 0.944 0.877 0.948 0

Prof 1 Day 2 92.8571 Bayes Net 0.657 0.97 0.986 0

Prof 2 Day 1 90.0322 Bagging (REPTrees) 0.829 0.931 0.923 0.381

Prof 2 Day 2 87.6202 Bagging (REPTrees) 0.886 0.898 0.227

Student 1 90.849 Bayes Net 0.723 0.972 0.867 0

Student 2 93.0769 Bagging (REPTrees) 0.88 0.976 0 0

MP16-899 Applying to productivity awareness

• Can we measure productivity by looking at activities?

• How aware are people of their own productivity?

MP16-899 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

MP16-899

Using knowledge of activity is okay for detecting productivity

Recall

Classifier Accuracy Productive Not productive

All Logistic Regression 62.1053 0.792 0.447

Profs only Logistic Regression 64.6154 0.788 0.5

Students only Logistic Regression 56.6667 0.533 0.6

w/o student 1 Logistic Regression 65.7895 0.795 0.514

w/o student 2 Logistic Regression 63.0952 0.857 0.405

w/o prof 1 Logistic Regression 68.1818 0 0.978

w/o prof 2 Logistic Regression 76.2712 0.93 0.313

MP16-899

Using raw features is slightly better for detecting productivity!

Recall

Classifier Accuracy

Accuracy using activity labels Productive Not productive

All Logistic Regression 65.7658 62.1053 0.642 0.672

Profs only Logistic Regression 73.9726 64.6154 0.697 0.775

Students only Decision Tree 63.1579 56.6667 0.65 0.611

w/o student 1 Naïve Bayes Tree 65.2174 65.7895 0.955 0.375

w/o student 2 Logistic Regression 71.7391 63.0952 0.714 0.72

w/o prof 1 Logistic Regression 68.2927 68.1818 0.32 0.842

w/o prof 2 Decision Tree 73.1343 76.2712 0.833 0.474

MP16-899 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

MP16-899 Office Activity Awareness

Ian LiMachine PerceptionSpring 2005

http://www.cs.cmu.edu/~ianl/16899/ will be up by March 13th for more details or contact me at ianli@cmu.edu

MP16-899 Acknowledgements

• Software development help from Bilge Mutlu and James Fogarty

• System deployment participants: Anind Dey, Jason Hong, Bilge Mutlu, and Pedram Keyani