Social Distancing in Indoor Spaces: An Intelligent Guide Based on the Internet of Things: COVID-19 as a Case Study

Social Distancing in Indoor Spaces: An Intelligent Guide Based on the Internet of Things: COVID-19 as a Case Study

Malek Alrashidi

Using Internet of Things (IoT) solutions is a promising way to ensure that social distancing is respected, especially in common indoor spaces. This paper proposes a system of placement and relocation of people within an indoor space, using an intelligent method based on two optimizers (ant colony and particle swarm) to find the optimal relocation of a set of people equipped with IoT devices to control their locations and movements. As a real-world test, an amphitheater with students was used, and the algorithms guided students toward correct, safe positions. Two evolutionary algorithms are proposed to resolve the studied problem, ant colony optimization and particle swarm optimization. Then, a comparative analysis was performed between these two algorithms and a genetic algorithm, using different evaluation metrics to assess the behavior of the proposed system. The results show the efficiency of the proposed intelligent IoT system.

2020

PSO, social distance, IoT, ACO, learning systems, indoor placement

10.3390/computers9040091

Epidemiology and Health

Korean Society of Epidemiology

Electronic computers. Computer science