If you are a car manufacturer dealing with road safety risks where alcohol and drugs cause 30% of all road deaths — this project developed AI software that integrates into vehicles to detect impairment before the car starts.
AI Eye-Scanning Software for Non-Invasive Digital Drug and Alcohol Detection
Imagine a camera that can tell if someone is under the influence of drugs or alcohol just by looking at their eyes. Instead of using breathalyzers or blood tests, this software analyzes images of the eye area to spot impairment. It works using a standard smartphone or a car's built-in camera, making it as easy as taking a selfie to check for sobriety.
What needed solving
Traditional drug testing is invasive, slow, or impossible to implement in real-time environments like cars or e-scooters. This leads to high accident rates caused by impaired operators.
What was built
A production-ready AI software that detects drug and alcohol influence via eye-area image analysis, including secure data acquisition and integration guides for vehicles.
Who needs this
Who can put this to work
If you are an e-scooter operator dealing with high accident rates where over 54% of e-scooter accidents involve drugs or alcohol — this project developed a digital tool for apps that prevents impaired riding.
If you are a site manager dealing with workplace safety where drugs and alcohol cause 25% of all fatal workplace accidents — this project developed a non-invasive eye-scanning tool for rapid sobriety checks.
Quick answers
What is the cost or pricing model for the software?
Based on available project data, specific pricing or cost structures are not disclosed.
Can this be scaled for industrial use?
Yes, the project developed a production version of the software and tested it in real-life scenarios for the automotive and micro-mobility sectors.
How is the intellectual property or licensing handled?
Based on available project data, specific IP or licensing terms are not mentioned.
How is the software integrated into existing hardware?
The tool is designed to use existing infrastructure such as smartphones, integrated car systems, and hospital equipment.
What is the timeline for deployment?
The project ran from April 2023 to March 2025, concluding with the finalization of the software and demonstration in various scenarios.
Who built it
The project is led by a single Swedish SME, Sightic Analytics AB. This lean structure indicates a highly focused development cycle where 100% of the project is industry-driven, accelerating the path from software development to commercial pilot testing.
Contact Sightic Analytics AB in Sweden
Talk to the team behind this work.
Contact us to explore licensing or integration of EYESCANNER AI into your safety hardware.