Problem

Our client, a security company, was struggling with identifying individuals entering their premises. They had a manual system in place that required security personnel to visually identify each person and match them against a database of known individuals. This process was time-consuming and prone to errors.

We were tasked with finding a solution that would automate the identification process and provide real-time alerts when an unknown individual entered the premises.

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Solution

We developed a face detection system that utilized machine learning algorithms to identify individuals based on facial features. The system used cameras placed at strategic locations around the premises to capture images of individuals entering and exiting the building.

The captured images were then processed by our system, which compared them against a database of known individuals. If an unknown individual was detected, an alert was sent to the security personnel in real-time, allowing them to take appropriate action.

Impact

Reduced identification time by X%
Improved accuracy of identification by X%

Quote of how incredible of an impact this had.

Team

Team Member #1 - Machine Learning Engineer
- Built and trained the machine learning models used for face detection
- Oversaw integration of the models into the overall system architecture
Team Member #2 - Software Developer
- Developed the software that processed the images captured by the cameras
- Built the real-time alert system used to notify security personnel of unknown individuals

Automating Security with Face Detection System