Cargando…

AlphaMobileSensing: A virtual testbed for mobile environmental monitoring

Environmental monitoring plays a critical role in creating and maintaining a comfortable, productive, and healthy environment. Built upon the advancements of robotics and data processing, mobile sensing demonstrates its potential to address problems regarding cost, deployment, and resolution that st...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhou, Qi, Zhong, Haoran, Li, Linyan, Wang, Zhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tsinghua University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9971688/
https://www.ncbi.nlm.nih.gov/pubmed/37359829
http://dx.doi.org/10.1007/s12273-023-1001-9
_version_ 1784898151601143808
author Zhou, Qi
Zhong, Haoran
Li, Linyan
Wang, Zhe
author_facet Zhou, Qi
Zhong, Haoran
Li, Linyan
Wang, Zhe
author_sort Zhou, Qi
collection PubMed
description Environmental monitoring plays a critical role in creating and maintaining a comfortable, productive, and healthy environment. Built upon the advancements of robotics and data processing, mobile sensing demonstrates its potential to address problems regarding cost, deployment, and resolution that stationary monitoring encounters, which therefore has attracted increasing research attentions recently. To facilitate mobile sensing, two key algorithms are needed: the field reconstruction algorithm and the route planning algorithm. The field reconstruction algorithm is to reconstruct the entire environment field from spatially- and temporally-discrete measurements collected by the mobile sensors. The route planning algorithm is to instruct the mobile sensors where the mobile sensor needs to move to for the next measurements. The performance of mobile sensors highly depends on these two algorithms. However, developing and testing those algorithms in the real world is expensive, challenging, and time-consuming. To address these issues, we proposed and implemented an open-source virtual testbed, AlphaMobileSensing, that can be used to develop, test, and benchmark mobile sensing algorithms. AlphaMobileSensing aims to help users more easily develop and test the field reconstruction and route planning algorithms for mobile sensing solutions, without worrying about hardware fault, test accidents (such as collision during the test), etc. The separation of concerns can significantly reduce the cost of developing software solutions for mobile sensing. For versatility and flexibility, AlphaMobileSensing was wrapped up using the standardized interface of OpenAI Gym, and it also provides an interface for loading physical fields that were generated by numerical simulations as virtual test sites to perform mobile sensing and retrieving monitoring data. We demonstrated applications of the virtual testbed by implementing and testing algorithms for physical field reconstruction in both static and dynamic indoor thermal environments. AlphaMobileSensing provides a novel and flexible platform to develop, test, and benchmark mobile sensing algorithms more easily, conveniently, and efficiently. AlphaMobileSensing is open sourced at https://github.com/kishuqizhou/AlphaMobileSensing. ELECTRONIC SUPPLEMENTARY MATERIAL (ESM): the Appendix is available in the online version of this article at 10.1007/s12273-023-1001-9.
format Online
Article
Text
id pubmed-9971688
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Tsinghua University Press
record_format MEDLINE/PubMed
spelling pubmed-99716882023-02-28 AlphaMobileSensing: A virtual testbed for mobile environmental monitoring Zhou, Qi Zhong, Haoran Li, Linyan Wang, Zhe Build Simul Research Article Environmental monitoring plays a critical role in creating and maintaining a comfortable, productive, and healthy environment. Built upon the advancements of robotics and data processing, mobile sensing demonstrates its potential to address problems regarding cost, deployment, and resolution that stationary monitoring encounters, which therefore has attracted increasing research attentions recently. To facilitate mobile sensing, two key algorithms are needed: the field reconstruction algorithm and the route planning algorithm. The field reconstruction algorithm is to reconstruct the entire environment field from spatially- and temporally-discrete measurements collected by the mobile sensors. The route planning algorithm is to instruct the mobile sensors where the mobile sensor needs to move to for the next measurements. The performance of mobile sensors highly depends on these two algorithms. However, developing and testing those algorithms in the real world is expensive, challenging, and time-consuming. To address these issues, we proposed and implemented an open-source virtual testbed, AlphaMobileSensing, that can be used to develop, test, and benchmark mobile sensing algorithms. AlphaMobileSensing aims to help users more easily develop and test the field reconstruction and route planning algorithms for mobile sensing solutions, without worrying about hardware fault, test accidents (such as collision during the test), etc. The separation of concerns can significantly reduce the cost of developing software solutions for mobile sensing. For versatility and flexibility, AlphaMobileSensing was wrapped up using the standardized interface of OpenAI Gym, and it also provides an interface for loading physical fields that were generated by numerical simulations as virtual test sites to perform mobile sensing and retrieving monitoring data. We demonstrated applications of the virtual testbed by implementing and testing algorithms for physical field reconstruction in both static and dynamic indoor thermal environments. AlphaMobileSensing provides a novel and flexible platform to develop, test, and benchmark mobile sensing algorithms more easily, conveniently, and efficiently. AlphaMobileSensing is open sourced at https://github.com/kishuqizhou/AlphaMobileSensing. ELECTRONIC SUPPLEMENTARY MATERIAL (ESM): the Appendix is available in the online version of this article at 10.1007/s12273-023-1001-9. Tsinghua University Press 2023-02-28 /pmc/articles/PMC9971688/ /pubmed/37359829 http://dx.doi.org/10.1007/s12273-023-1001-9 Text en © Tsinghua University Press 2023 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Research Article
Zhou, Qi
Zhong, Haoran
Li, Linyan
Wang, Zhe
AlphaMobileSensing: A virtual testbed for mobile environmental monitoring
title AlphaMobileSensing: A virtual testbed for mobile environmental monitoring
title_full AlphaMobileSensing: A virtual testbed for mobile environmental monitoring
title_fullStr AlphaMobileSensing: A virtual testbed for mobile environmental monitoring
title_full_unstemmed AlphaMobileSensing: A virtual testbed for mobile environmental monitoring
title_short AlphaMobileSensing: A virtual testbed for mobile environmental monitoring
title_sort alphamobilesensing: a virtual testbed for mobile environmental monitoring
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9971688/
https://www.ncbi.nlm.nih.gov/pubmed/37359829
http://dx.doi.org/10.1007/s12273-023-1001-9
work_keys_str_mv AT zhouqi alphamobilesensingavirtualtestbedformobileenvironmentalmonitoring
AT zhonghaoran alphamobilesensingavirtualtestbedformobileenvironmentalmonitoring
AT lilinyan alphamobilesensingavirtualtestbedformobileenvironmentalmonitoring
AT wangzhe alphamobilesensingavirtualtestbedformobileenvironmentalmonitoring