- An algorithm based on sensors data combined with the time of day and day of the week was right nine out of ten times
- The most important features were sensors tracking movements, GPS location
- Current marijuana tests have a three-day window and are difficult to administer in the field
- The algorithm could ‘deliver a brief intervention when and where it might have the most impact to reduce cannabis-related harm’
Sensors on a person’s smartphone can be used to determine if they’re high with uncanny precision, according to a new study out of Rutgers University
Researchers at the school’s Institute for Health, Health Care Policy and Aging Research found that an algorithm that combined sensors tracking movements and GPS location with data on the time of day and day of the week had a 90 percent accuracy rate in determining if someone was stoned.
The algorithm could help law enforcement and health professionals more accurately predict if an individual is currently experiencing ‘cannabis intoxication,’ according to a release.
‘We might be able to detect when a person might be experiencing cannabis intoxication and deliver a brief intervention when and where it might have the most impact to reduce cannabis-related harm,’ said co-author Tammy Chung, director of the Institute’s Center for Population Behavioral Health in the statement.