This project uses real-time object detection to optimize elevator usage in buildings. CCTV footage analyzes waiting crowds to decide if the elevator should stop, reducing wait times and improving efficiency.
Fig. 1. Figure 1: Flow diagram of the model
The proposed flow of the model for the Lift Efficiency
Development project is as follows:
- CCTV cameras capture images of passengers on the floor.
- The images are sent to the control center.
- The control center defines the region of interest (ROI) in the images, which is a sub-region that contains the relevant information for elevator management.
- The control center uses YOLOv8, a real-time object detection algorithm, to detect the number and location of passengers in the images.
- Based on whether there is a passenger or not in the defined region, the control center decides whether to stop the lift or not.
- The control center communicates these decisions to the lift carrier, which is the module that controls the movement and operation of the elevator.
- The lift carrier executes the commands from the control center and provides the status of the elevator.