Massimo: Public Queue Monitoring and Management using Mass-Spring Model
This addresses queue management issues for public spaces, but appears incremental as it combines existing technologies without specifying novel breakthroughs.
The paper tackles the problem of queue control and regulation in public spaces to avoid traffic jams and improve customer satisfaction, resulting in a system that provides accurate information about crowd levels and necessary actions using technologies like computer vision and machine learning.
An efficient system of a queue control and regulation in public spaces is very important in order to avoid the traffic jams and to improve the customer satisfaction. This article offers a detailed road map based on a merger of intelligent systems and creating an efficient systems of queues in public places. Through the utilization of different technologies i.e. computer vision, machine learning algorithms, deep learning our system provide accurate information about the place is crowded or not and the necessary efforts to be taken.