The client needed to create an enterprise-grade solution able to count the number of employees in every particular area as well as identify whether people wear masks correctly and observe social distancing rules.
To meet this business need, we used our computer vision and deep learning competence. The SCRUM methodology was chosen to easily adapt to constantly changing requirements and innovative project nature, while ensuring full process transparency.
“Project complexity required a highly competent, cross-functional team. We assembled frontend and backend engineers, DL experts, Python developers, and QA specialists with 50+ years of cumulative team experience.”
— Anatoliy, Project Manager
Leverage our computer vision knowledge to build a custom solution from scratch or enhance an existing one with cutting-edge functionality like face identification, object tracking, behavior analysis, and more. Contact us describing your requirements, and we’ll help you find the balance between cost, performance, and business value.
To scale the solution’s capacity on Nvidia Jetson edge devices, we leveraged the C++ programming language. This allowed us to easily handle the streams from multiple cameras and smoothly perform all detections and calculations.
Depending on modules used, every edge device was connected to up to seven cameras. And the number of edge devices used in one tenant (web application) was unlimited.