Author(s)

Jupiter Ndiaye¹, Ousmane Sow², Oumar Diallo², Ababacar Sadikh Faye¹, Youssou Traore², Mame Andallah Diop², Abdoulaye Diop¹

¹ED2DS, Iba Der Thiam University, Thies, Senegal.
²University Institute of Technology, Iba Der Thiam University, Thies, Senegal.

Virus prevention has been considered central to the fight against the COVID- 19 coronavirus pandemic. To limit the spread of the virus in public places, several measures have been taken, in particular respect for barrier gestures. This work is part of this dynamic and sets up a new wireless version of an electronic and nominative queue manager using artificial intelligence for more equity, inclusion and solidarity. This system, named Gifa is developed in our laboratory. The first prototype, whose connections are largely provided by a wired system with an artisanal acquisition module, is difficult to deploy for general public use, especially in buildings already built. This article deals with an artificial intelligence queue management system, presenting more functionalities, whose access to the service is ensured in very large part by wireless exchanges with a modern acquisition module realized by 3D printing. The flexible and autonomous design of this device makes it particularly easy to deploy on premises open to the public without having to modify the existing installation for commissioning. The manager is equipped with a configuration terminal, and at the counters the call is made by a cashier also equipped with a tablet connected to the wifi network. Its display screen shows certain information relating to the identity of the customer such as his face, his order number, his first name and last name. This reduces the authentication time of the person at the checkout, queue bypasses for more fairness and less stress. This work has resulted in the improvement of queue management systems by giving them more flexibility to make them more adaptable in several types of environments and other contexts.

GiFa, Public Health, Wireless, Node Red, Arduino, Cloud and AI, 3D Printing

Ndiaye, J. , Sow, O. , Diallo, O. , Faye, A. , Traore, Y. , Diop, M. and Diop, A. (2023) Development of an Intelligent Queue Manager That Takes Account of the Social and Health Context. Engineering, 15, 561-579. doi: 10.4236/eng.2023.159040.