Vision Secure AI Smart Surveillance
Year: 2026
Type: article
Abstract: Traditional industrial surveillance systems mostly rely on video recording and human monitoring. This approach does not work well in identifying problems. Is expensive to maintain.These systems usually do not provide information on worker activities, product movement and workplace safety. This paper discusses Vision Secure, a surveillance system that utilizes Edge AI, computer vision, Internet of Things and real-time analytics to monitor industries. The system employs YOLOv8 for object detection. Byte Track for object tracking. This allows for monitoring of workers and products using cameras and Internet-connected devices. A specialized engine analyzes worker activities, movement, productivity and detects any events. The data is then sent to cloud-based dashboards through Flask and Django services enabling decision-making.Our trial of this system revealed that it reduces the need for intervention and provides greater transparency. Vision Secure is suitable, for factories, warehouses, logistics centers and Industry 4.0 environments.The integration of Edge AI and analytics enhances the performance of surveillance systems while reducing costs. The combination of YOLOv8 and Byte Track is commonly used for object detection and tracking in surveillance applications..
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7166329912