COVID-19 Safety Control System
Due to the pandemic, social distancing and face mask-wearing have become mandatory in many public places, including airports. Today, airports are required to monitor the implementation of these preventive measures to minimize the spread of COVID-19 and ensure the safety of passengers and employees. However, manual monitoring of all passengers and airport workers is a time-consuming and cumbersome task that requires engaging a lot of additional staff.
Challenge
Solution
The software reviews the video streams generated by CCTV cameras across the airport, identifies humans in the footage, and measures the distance between them. If it is less than 6 feet or 1.5 m, the system sends a notification to the responsible staff.
Then it classifies humans into two categories: people with face masks on and violators. In case a violator is detected, the system triggers alerts and builds a roadmap of a violator to help airport operators minimize contacts between those who abide by COVID-19 mask-wearing and those who don’t.
Apart from that, the software counts the number of people entering the airport and informs visitors whether they are allowed to enter or not. Then it builds an online density map of crowds at an airport and creates reports on a building’s daily footfall.
Data about all mask-wearing and social distancing violations are recorded and stored on the cloud for future analysis.
Project Results
- Fully automated mask-wearing and social distancing compliance monitoring;
- 80% reduction in the number of violations;
- Optimized staff and resource allocation;
- Optimized flow of passengers entering an airport.
Technical challenges
- Real-time processing of computer vision data from multiple cameras.
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Maxim
System Architect and Delivery Manager
In over 10 years of my professional career, I have developed, architected, and managed dozens of projects for the Manufacturing & Energy, Restaurant & Hospitality, Aviation, and IT industries. I have hands-on experience with Mobile technology, Computer vision, Machine learning, Predictive modeling, Cloud computing, and SaaS.
I managed the development of a Computer vision-based kitchen management system for a large restaurant chain. We did a great job on this project, and I consider it the highlight of my career.