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Conference Paper: Indoor Air Monitoring Platform and Personal Health Reporting System: Big Data Analytics for Public Health Research

TitleIndoor Air Monitoring Platform and Personal Health Reporting System: Big Data Analytics for Public Health Research
Authors
KeywordsAir Pollution
Data Mining
Date Capturing Platform
Personal Heath
Issue Date2015
Citation
Proceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015, 2015, p. 309-312 How to Cite?
Abstract© 2015 IEEE. Air pollution poses an increased risk for respiratory infections and lung cancer. Monitoring systems on air pollution are common for outdoor environment. In this study, our focus is on the air monitoring in household environment and connects it to a personal health reporting system through a mobile APP. Data will be captured and stored in the cloud so as to improve computational efficiency and enhance data storage capacity. Pollution data can be captured hourly year round, hence a sizeable data storage is needed in the cloud. Health statuses can be uploaded through a self-reporting system, so the data can supply useful information for other healthcare studies, and related urban planning in the future. Furthermore, data analytics based on pollution data can help identify highly polluted areas at different time points. These data are useful for the development of alert systems that can remind individuals to take personal precautions to avoid inhaling pollutants. Such alert systems are applicable to households, commercial buildings and public areas. Accumulated data on this cloud platform can support data mining in search of connections between air pollution and health outcomes, which can fuel research studies in the field of public health.
Persistent Identifierhttp://hdl.handle.net/10722/246833
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHo, Kin Fai-
dc.contributor.authorHirai, Hoyee W.-
dc.contributor.authorKuo, Yong Hong-
dc.contributor.authorMeng, Helen M.-
dc.contributor.authorTsoi, Kelvin K.F.-
dc.date.accessioned2017-09-26T04:28:07Z-
dc.date.available2017-09-26T04:28:07Z-
dc.date.issued2015-
dc.identifier.citationProceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015, 2015, p. 309-312-
dc.identifier.urihttp://hdl.handle.net/10722/246833-
dc.description.abstract© 2015 IEEE. Air pollution poses an increased risk for respiratory infections and lung cancer. Monitoring systems on air pollution are common for outdoor environment. In this study, our focus is on the air monitoring in household environment and connects it to a personal health reporting system through a mobile APP. Data will be captured and stored in the cloud so as to improve computational efficiency and enhance data storage capacity. Pollution data can be captured hourly year round, hence a sizeable data storage is needed in the cloud. Health statuses can be uploaded through a self-reporting system, so the data can supply useful information for other healthcare studies, and related urban planning in the future. Furthermore, data analytics based on pollution data can help identify highly polluted areas at different time points. These data are useful for the development of alert systems that can remind individuals to take personal precautions to avoid inhaling pollutants. Such alert systems are applicable to households, commercial buildings and public areas. Accumulated data on this cloud platform can support data mining in search of connections between air pollution and health outcomes, which can fuel research studies in the field of public health.-
dc.languageeng-
dc.relation.ispartofProceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015-
dc.subjectAir Pollution-
dc.subjectData Mining-
dc.subjectDate Capturing Platform-
dc.subjectPersonal Heath-
dc.titleIndoor Air Monitoring Platform and Personal Health Reporting System: Big Data Analytics for Public Health Research-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/BigDataCongress.2015.51-
dc.identifier.scopuseid_2-s2.0-84959536415-
dc.identifier.spage309-
dc.identifier.epage312-
dc.identifier.isiWOS:000380443700041-

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