The multi-functional intelligent detection and alarm system based on YOLOv8 provides a variety of detection and alarm functions, and uses image processing and deep learning technology for data analysis and judgment. The system mainly includes the following parts: -Fire monitoring module: This module uses image recognition algorithms to monitor the fire situation in the scene in real time, and immediately issue an alarm when a fire is found. -Personnel intrusion monitoring module: Using the target detection algorithm, this module can detect that unauthorized personnel enter the restricted area and trigger an alarm in time. -People flow monitoring module: Through image analysis and counting algorithms, this module can monitor the number of people in the scene in real time and provide statistical data. -Mask monitoring module: This module uses image recognition algorithms to monitor whether people in the scene are wearing masks in real time, and triggers an alarm when it is found that people are not wearing masks. Technical Details -Image acquisition and processing: Obtain the scene image through the camera, and preprocess the image, including image denoising, enhancement and edge detection, to improve the accuracy and efficiency of the subsequent algorithm. -Fire monitoring algorithm: A flame recognition model was built and trained using deep learning techniques. The model can accurately detect open flames in images and sound an alarm when a fire is detected. -Human intrusion detection algorithm: Using the target detection algorithm, a human body detection model is trained. The model can monitor in real time whether there is a personnel intrusion in the key area delineated by the monitoring equipment, and if a personnel intrusion is detected, an alarm will be issued immediately. -People flow monitoring algorithm: Combining computer vision and image processing technology, real-time monitoring and statistics of the number of people flow are realized. By tracking and counting the human body in the image, accurate human flow information can be provided. -Mask monitoring algorithm: a method of using deep learning technology to determine whether a person is wearing a mask through training. It can quickly and accurately detect the wearing of masks by feature extraction and mask recognition of face images.