CafeteriaCrowdMonitor is a real-time cafeteria crowd monitoring system designed to alleviate congestion and long queues during peak meal times. It utilizes a Raspberry Pi camera to capture footage of the cafeteria, processes the images with TensorFlow, and shares the live crowd count with users through an MQTT broker and a WeChat Mini Program.
- Real-time crowd monitoring using a Raspberry Pi camera
- Image processing with TensorFlow for accurate person counting
- MQTT communication for fast and efficient data sharing
- WeChat Mini Program for easy access by students and teachers
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
I often found myself running down from the fourth floor, only to be greeted by a 20-minute queue in the cafeteria. I found this situation unbearable and decided to create this solution to help both students and teachers better manage their time during peak meal hours. I hope this project can alleviate the congestion and make the dining experience more enjoyable for everyone at our school.
A special shoutout to Pinghe students—Be the change that you wish to see in the school.