Cargando…

A methodology for optimal placement of sensors in enclosed environments: A dynamical systems approach

Air quality has been an important issue in public health for many years. Sensing the level and distributions of impurities help in the control of building systems and mitigate long term health risks. Rapid detection of infectious diseases in large public areas like airports and train stations may he...

Descripción completa

Detalles Bibliográficos
Autores principales: Fontanini, Anthony D., Vaidya, Umesh, Ganapathysubramanian, Baskar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126557/
https://www.ncbi.nlm.nih.gov/pubmed/32287963
http://dx.doi.org/10.1016/j.buildenv.2016.02.003
_version_ 1783516172127305728
author Fontanini, Anthony D.
Vaidya, Umesh
Ganapathysubramanian, Baskar
author_facet Fontanini, Anthony D.
Vaidya, Umesh
Ganapathysubramanian, Baskar
author_sort Fontanini, Anthony D.
collection PubMed
description Air quality has been an important issue in public health for many years. Sensing the level and distributions of impurities help in the control of building systems and mitigate long term health risks. Rapid detection of infectious diseases in large public areas like airports and train stations may help limit exposure and aid in reducing the spread of the disease. Complete coverage by sensors to account for any release scenario of chemical or biological warfare agents may provide the opportunity to develop isolation and evacuation plans that mitigate the impact of the attack. All these scenarios involve strategic placement of sensors to promptly detect and rapidly respond. This paper presents a data driven sensor placement algorithm based on a dynamical systems approach. The approach utilizes the finite dimensional Perron-Frobenius (PF) concept. The PF operator (or the Markov matrix) is used to construct an observability gramian that naturally incorporates sensor accuracy, location constraints, and sensing constraints. The algorithm determines the response times, sensor coverage maps, and the number of sensors needed. The utility of the procedure is illustrated using four examples: a literature example of the flow field inside an aircraft cabin and three air flow fields in different geometries. The effect of the constraints on the response times for different sensor placement scenarios is investigated. Knowledge of the response time and coverage of the multiple sensors aides in the design of mechanical systems and response mechanisms. The methodology provides a simple process for place sensors in a building, analyze the sensor coverage maps and response time necessary during extreme events, as well as evaluate indoor air quality. The theory established in this paper also allows for future work in topics related to construction of classical estimator problems for the sensors, real-time contaminant transport, and development of agent dispersion, contaminant isolation/removal, and evacuation strategies.
format Online
Article
Text
id pubmed-7126557
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Elsevier Ltd.
record_format MEDLINE/PubMed
spelling pubmed-71265572020-04-08 A methodology for optimal placement of sensors in enclosed environments: A dynamical systems approach Fontanini, Anthony D. Vaidya, Umesh Ganapathysubramanian, Baskar Build Environ Article Air quality has been an important issue in public health for many years. Sensing the level and distributions of impurities help in the control of building systems and mitigate long term health risks. Rapid detection of infectious diseases in large public areas like airports and train stations may help limit exposure and aid in reducing the spread of the disease. Complete coverage by sensors to account for any release scenario of chemical or biological warfare agents may provide the opportunity to develop isolation and evacuation plans that mitigate the impact of the attack. All these scenarios involve strategic placement of sensors to promptly detect and rapidly respond. This paper presents a data driven sensor placement algorithm based on a dynamical systems approach. The approach utilizes the finite dimensional Perron-Frobenius (PF) concept. The PF operator (or the Markov matrix) is used to construct an observability gramian that naturally incorporates sensor accuracy, location constraints, and sensing constraints. The algorithm determines the response times, sensor coverage maps, and the number of sensors needed. The utility of the procedure is illustrated using four examples: a literature example of the flow field inside an aircraft cabin and three air flow fields in different geometries. The effect of the constraints on the response times for different sensor placement scenarios is investigated. Knowledge of the response time and coverage of the multiple sensors aides in the design of mechanical systems and response mechanisms. The methodology provides a simple process for place sensors in a building, analyze the sensor coverage maps and response time necessary during extreme events, as well as evaluate indoor air quality. The theory established in this paper also allows for future work in topics related to construction of classical estimator problems for the sensors, real-time contaminant transport, and development of agent dispersion, contaminant isolation/removal, and evacuation strategies. Elsevier Ltd. 2016-05-01 2016-02-09 /pmc/articles/PMC7126557/ /pubmed/32287963 http://dx.doi.org/10.1016/j.buildenv.2016.02.003 Text en Copyright © 2016 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Fontanini, Anthony D.
Vaidya, Umesh
Ganapathysubramanian, Baskar
A methodology for optimal placement of sensors in enclosed environments: A dynamical systems approach
title A methodology for optimal placement of sensors in enclosed environments: A dynamical systems approach
title_full A methodology for optimal placement of sensors in enclosed environments: A dynamical systems approach
title_fullStr A methodology for optimal placement of sensors in enclosed environments: A dynamical systems approach
title_full_unstemmed A methodology for optimal placement of sensors in enclosed environments: A dynamical systems approach
title_short A methodology for optimal placement of sensors in enclosed environments: A dynamical systems approach
title_sort methodology for optimal placement of sensors in enclosed environments: a dynamical systems approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126557/
https://www.ncbi.nlm.nih.gov/pubmed/32287963
http://dx.doi.org/10.1016/j.buildenv.2016.02.003
work_keys_str_mv AT fontaninianthonyd amethodologyforoptimalplacementofsensorsinenclosedenvironmentsadynamicalsystemsapproach
AT vaidyaumesh amethodologyforoptimalplacementofsensorsinenclosedenvironmentsadynamicalsystemsapproach
AT ganapathysubramanianbaskar amethodologyforoptimalplacementofsensorsinenclosedenvironmentsadynamicalsystemsapproach
AT fontaninianthonyd methodologyforoptimalplacementofsensorsinenclosedenvironmentsadynamicalsystemsapproach
AT vaidyaumesh methodologyforoptimalplacementofsensorsinenclosedenvironmentsadynamicalsystemsapproach
AT ganapathysubramanianbaskar methodologyforoptimalplacementofsensorsinenclosedenvironmentsadynamicalsystemsapproach