ELEvent: An Abnormal Event Detection System in Elevator Cars

The less developed sensor technologies of traditional civil elevators, particularly in older districts, have long impeded the construction of smart cities. By using surveillance cameras, we can intelligently identify the abnormal events in elevator, but there is currently a lack of relevant datasets. For this purpose, we curate a visual elevator anomalous events dataset that serves as a benchmark for evaluating the performance of state-of-the-art detection models like YOLOv8. Then we improved YOLOv8 via adding coordinate attention and optimizing loss functions and activation functions, resulting in a notable enhancement in its performance for elevator abnormal detection. Furthermore, based on the improved model we implement a system called ELEvent in a real residential community and proved effective in practice.