In modern industrial environments, daily interaction with machines poses risks of different kinds. The current safety measures, such as warning signs and barriers, are often insufficient in a dynamic environment; there is a need for a proactive and adaptive safety solution that can identify hazards in real-time and provide immediate feedback to workers.
Siemens Safe Guard is a robust solution that leverages computer vision and machine learning to enhance safety in industrial environments. It is already deployed in production facilities and is used to monitor the safety of workers in real-time, tracking the worker’s location, the machines workflows, and currently defined policies. Other features include the ability to detect and classify hazards, provide alerts and notifications, and generate hazard dashboards.
Team members: Matthias Linhuber (Team Lead), Maximilian Rapp (Coach), Shuaiwei Yu, Josef Schmid, Mersudin Corbic, Liam Berger, Fangxing Liu, Pao Xin Tan, Yichen Fu, Tobias Klingenberg,
Customers: Jochen Nickles, Jan Philip Bernius