During the past years, we all have experienced in the most explicit way the importance of social and professional behaviour in the modern era, where the actions of even a single company or individual might affect the global population and economics. Social distancing has been one of the most prominent measures of public safety against COVID-19 pandemic spread. However, it is heavily dependent of individual responsibility and self-discipline, while the sense of “distance estimation” can be subjective without the use of necessary tools.
Some of the main challenges of tracking people movement and interactions using Computer Vision are:
“SafeDistance analytics tool” employs cutting-edge machine learning and computer vision techniques to calculate the physical social distance for every person detected in a scene, be it an industrial or working environment, a train station or a public road, and generates an easy to comprehend analytics report.
With all the processing performed at the edge and completely avoiding unnecessary sensitive data transfers to the cloud, you can rest assured that private data remain private.
In addition to that, the integrated people blurring / anonymizing technology ensures identity safety and guarantees GDPR compliancy.
This application is powered by PerCV.ai end-to-end Vision AI Software & Services platform, detecting people, objects and vehicles using depth-only information, achieving remarkable levels of accuracy and robustness. Our goal is to provide an easily scalable and cost-efficient solution, that can be implemented in a wide variety of real-life scenarios.
SafeDistance analytics tool can be utilised both in indoor and outdoor spaces, regardless of the surroundings, environmental or light conditions. The application scenarios are limitless: Warehouses, constructions sites, transportation lounges, retail shops, public areas, etc.
Get a collection of Sample Reports and Videos provided by “SafeDistance analytics tool”. Find out how our embedded computer vision technology is utilised at the new social landscape, where visualization tools become more critical than ever in helping create responsible social patterns, without putting public privacy at stake.
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