Paper Title Presenter: Advocate: Devil’s Advocate: NAME Date

Paper Title

Presenter:Advocate:

Devil’s Advocate:

NAMENAMENAME

Date

Context

• XX% of office buildings have coffee makers in the kitchen

Motivation / Problem Statement

• YY hours of productive work are lost due to sleepiness

• Studies show that proper caffeine levels can improve productivity in sleepy people

Prior Art

• Today, people adjust their own caffeine levels by adding more/less coffee beans

• However:– People cannot precisely regulate caffeine levels– Sleepy people are the least precise– Recent trends in pre-packaged coffee make

regulation even less likely

Claim

A coffee maker that detects sleepiness levels through voice analysis

and precisely optimizes coffee strength will increase productivity

in office environments over manual coffee making

Approach

• Voice sensors• Tiredness detection• Coffee optimizer

Experimental Setup

• Dependent variable• Independent variable• Baseline• Ground truth• Bounds• Analysis

Results

• In the study, people in the test group had ZZ% more productivity

Conclusion

• If adopted in all office buildings in the US, the smart coffee maker would recover AA productive work hours and save BB billions of dollars for industry