Machine Learning for Engineers

Area intrusion detection systems are crucial in industrial safety, preventing unauthorized access to hazardous areas. This technology is used to enhance safety measures around machinery, such as rotating or electrically energized equipment, which can be dangerous if accessed during operation.

Objective: Develop a system using computer vision to detect people entering restricted areas near dangerous machinery. Record the entry and exit times of each person into a database. Alert system operators when a person enters the restricted area during machinery operation.

Person Detection

Process a real-time video stream to detect any unauthorized access. Store relevant information such as the timestamp of entry and exit in a database for later review.

Implement person detection using pre-trained models capable of recognizing human figures in various postures and conditions. Suggested tools include MediaPipe Pose or YOLO (You Only Look Once) Tracking frameworks that offer real-time detection capabilities suitable for monitoring areas with potentially hazardous equipment. Example code is available for Object Detection, Pose Tracking, and Hand Tracking.

Safety Monitoring

The system should monitor the operational status of the machinery, using input from control systems to determine when the equipment is active. During these times, the area around the machinery is considered restricted. The Temperature Control Lab can be used for real-time testing. Shut off the heaters if a person enters the restricted area around the TCLab when the heater is above a certain level, such as 50°C.

Database Integration

Implement a database to record entries and exits from the restricted area. This includes timestamps and possibly identification details if individual tracking is enabled.

Example Solution

Below is a sample with 50 seconds of video detection from a webcam. Database entries are added each time a unique ID is created for a person when they enter or leave the video frame.

  row  id           entry_time            exit_time
    0   1  2024-04-19 10:32:43  2024-04-19 10:32:57
    1   2  2024-04-19 10:33:02  2024-04-19 10:33:08
    2   5  2024-04-19 10:33:12  2024-04-19 10:33:12
    3   6  2024-04-19 10:33:12  2024-04-19 10:33:13
    4   8  2024-04-19 10:33:13                 None

The video frame is given a red tint when an intrusion is detected and a unique ID is assigned when the person enters the video frame. The unique ID is assigned to the person until they leave the frame and the exit time is recorded. The camera could be positioned to monitor only the restricted area or a subset of the frame could be selected as the restricted area.

References

• MediaPipe, an open-source library for building multimodal applied machine learning pipelines
• Ultralytics YOLO (You Only Look Once), a state-of-the-art, real-time object detection system