Christopher Feng¹ and Soroush Mirzaee², ¹USA, ²California State Polytechnic University, USA

This project presents a sobriety detection system aimed at preventing drunk driving through a combination of image recognition, alcohol sensing, and speech evaluation tests. This project uses a Raspberry Pi device, equipped with an alcohol sensor and a camera to assess a user’s sobriety by analyzing facial expressions and blood alcohol content (BAC) [9][10]. Additionally, a vocal test is conducted using the user’s smartphone, with results processed and stored in a cloud database for further analysis. The system offers an affordable, reliable, and user-friendly alternative to traditional methods, such as breathalyzers, by detecting both alcohol and drug impairment. Through a series of experiments, the system demonstrated high accuracy, achieving a 97% success rate when combining all tests, highlighting its potential to reduce driving under the influence of incidents.

Drunk Driving, Sobriety, Raspberry Pi, Flutter