As computing becomes more ubiquitous in our objects, designers need to be more aware of how to design meaningful interactions into electronically enhanced objects. At the University of Washington, a class of junior Interaction Design majors is exploring this question. These pages chronicle their efforts.

Thursday, April 18, 2013

Drunk Walking Dangers Avoidance — M. Simone, S. Churng


Over 1/3 of pedestrian fatalities involve alcohol. 

According to the National Center for Statistics and Analysis, 
13% of drivers
involved in traffic accidents involving fatal injuries
in 2012
had a blood alcohol concentration of .08 g/dL. Of pedestrians involved in fatal crashes with automobiles, 35%—almost twice the amount—
had at least .08 g/dL BAC. This number does not include injuries incurred from non-vehicle-related situations such as crimes involving others or self-endangering circumstances.



http://www-nrd.nhtsa.dot.gov/Pubs/811394.pdf



Reality of situation

We are interested in a solution that detects stages of drunkenness, and prevents people from walking in traffic, by creating a signal feedback and/or notifying others such as friends or taxi companies via mobile messaging.

Symptoms/Signs:
alcohol breath
alcohol sweat
swaying steps
swayed incline
slurred speech
louder speech
rambling
aggression
glassy/bloodshot and dilated eyes

Dangers:
stumbling, swaying, 
bumping into things, dropping things
trying to navigate through streets, falling, tripping
walking into cars, pits, people, dangerous alleys

Alternatives:
calling/notifying friends
calling/hailing a cab


Sensors

The sensors below all relate to ways of detecting the signs of high alcohol-induced impairment. We have included links to the ones that are available as electric sensors.

breath sensor

rhythm detection (of steps)

sweat odor sensor

sound fluctuation detection

eye dilation detector

blood-alcohol level detector

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