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

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 an...

Full description

Saved in:
Bibliographic Details
Published in:Computers (Basel) 2020-12, Vol.9 (4), p.91
Main Author: Alrashidi, Malek
Format: Article
Language:English
Subjects:
ACO
Ant colony optimization
Contact tracing
Coronaviruses
COVID-19 vaccines
Disease transmission
Efficiency
Energy consumption
Evolutionary algorithms
Genetic algorithms
indoor placement
Internet of Things
IoT
learning systems
Localization
Optimization algorithms
Pandemics
Particle swarm optimization
PSO
Public transportation
Relocation
Sensors
Simulation
social distance
Social distancing
Students
Wireless networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2073-431X
2073-431X
DOI:10.3390/computers9040091