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

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