An Improved IoT-Based System for Detecting the Number of People and Their Distribution in a Classroom

Slavomir Matuska; Juraj Machaj; Robert Hudec; Patrik Kamencay

doi:10.3390/s22207912

An Improved IoT-Based System for Detecting the Number of People and Their Distribution in a Classroom

Sensors (Basel). 2022 Oct 18;22(20):7912. doi: 10.3390/s22207912.

Authors

Slavomir Matuska¹, Juraj Machaj¹, Robert Hudec¹, Patrik Kamencay¹

Affiliation

¹ Faculty of Electrical Engineering and Information Technology, University of Zilina, 010 26 Zilina, Slovakia.

Abstract

This paper presents an improved IoT-based system designed to help teachers handle lessons in the classroom in line with COVID-19 restrictions. The system counts the number of people in the classroom as well as their distribution within the classroom. The proposed IoT system consists of three parts: a Gate node, IoT nodes, and server. The Gate node, installed at the door, can provide information about the number of persons entering or leaving the room using door crossing detection. The Arduino-based module NodeMCU was used as an IoT node and sets of ultrasonic distance sensors were used to obtain information about seat occupancy. The system server runs locally on a Raspberry Pi and the teacher can connect to it using a web application from the computer in the classroom or a smartphone. The teacher is able to set up and change the settings of the system through its GUI. A simple algorithm was designed to check the distance between occupied seats and evaluate the accordance with imposed restrictions. This system can provide high privacy, unlike camera-based systems.

Keywords: Arduino-based module; COVID-19; IoT nodes; IoT-based system; Raspberry Pi.

MeSH terms

Algorithms
COVID-19*
Humans
Privacy
Smartphone
Software

Grants and funding

This paper was supported by the project of Operational Programme Integrated Infrastructure: Independent research and development of technological kits based on wearable electronics products, as tools for raising hygienic standards in a society exposed to the virus causing the COVID-19 disease, ITMS2014+ code 313011ASK8 and by European Regional Development Fund and by Slovak Research and Development Agency under contract no. PP-COVID-20-0100: DOLORES.AI: The pandemic guard system.