Project Summary
This project utilizes AI-based video analysis to detect cobbles and people in danger zones. It monitors all CCTV cameras in real-time, allowing for the setting and storing of danger zones. The system issues real-time alarms during danger situations and communicates with the video surveillance PC and factory PLC. The PLC and network are also integrated to control equipment operations in case of cobble occurrences.
My Contribution
I contributed to the development and maintenance of the Video Safety Solution. My tasks included AI-based video abnomaly detection, real-time monitoring, and integrating PostgreSQL and Python for data processing and analysis.
Video Monitoring
Facilitates real-time monitoring of live video streams from surveillance cameras. Object detection algorithms are used to identify and track person in the video streams.
Area Settings
Allows for the configuration of specific dangerous areas. It triggers alarms when people enter these areas while machinery is operating.
Device Information
Provides detailed information on video monitoring devices.
History
Allows viewing of historical data and events related to video monitoring.
Video Safety Settings
Manage settings and configurations of video safety components.
