{"title":"海报摘要:PiMi空气社区:通过分享数据和技术诀窍获得更新鲜的室内空气","authors":"Yixin Zheng, Linglong Li, Lin Zhang","doi":"10.1109/IPSN.2014.6846764","DOIUrl":null,"url":null,"abstract":"PiMiair.org is a participatory indoor air quality data sharing project we launched in January 2014. Over 200 PiMi air boxes, a low-cost indoor air quality monitor, were given out to volunteer users across China. The PiMi air boxes measure the approximate indoor particulate matter concentration, and the ambient temperate and humidity. When a user accesses the PiMi air box for his personal air quality data on his smartphone, the data is relayed to the backend PiMi cloud server for analysis. Accumulating large amount of indoor air quality data under different circumstances, the PiMi cloud server is able to use statistical learning methodologies to detect point of interests (POIs) in the data series, and asks users to label their activities or events at the POIs. Together with the user-reported physicality information on the indoor environments, PiMiair.org is able to quantitatively evaluate the impacts of the environment physicality and human behaviors on the indoor air quality, and mine the knowledges on how to alleviate indoor air pollution. We believe that by sharing these knowledge among the community, healthier breathing environments could be nurtured for the well-being of the public.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Poster abstract: PiMi air community: Getting fresher indoor air by sharing data and know-hows\",\"authors\":\"Yixin Zheng, Linglong Li, Lin Zhang\",\"doi\":\"10.1109/IPSN.2014.6846764\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"PiMiair.org is a participatory indoor air quality data sharing project we launched in January 2014. Over 200 PiMi air boxes, a low-cost indoor air quality monitor, were given out to volunteer users across China. The PiMi air boxes measure the approximate indoor particulate matter concentration, and the ambient temperate and humidity. When a user accesses the PiMi air box for his personal air quality data on his smartphone, the data is relayed to the backend PiMi cloud server for analysis. Accumulating large amount of indoor air quality data under different circumstances, the PiMi cloud server is able to use statistical learning methodologies to detect point of interests (POIs) in the data series, and asks users to label their activities or events at the POIs. Together with the user-reported physicality information on the indoor environments, PiMiair.org is able to quantitatively evaluate the impacts of the environment physicality and human behaviors on the indoor air quality, and mine the knowledges on how to alleviate indoor air pollution. We believe that by sharing these knowledge among the community, healthier breathing environments could be nurtured for the well-being of the public.\",\"PeriodicalId\":297218,\"journal\":{\"name\":\"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPSN.2014.6846764\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPSN.2014.6846764","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Poster abstract: PiMi air community: Getting fresher indoor air by sharing data and know-hows
PiMiair.org is a participatory indoor air quality data sharing project we launched in January 2014. Over 200 PiMi air boxes, a low-cost indoor air quality monitor, were given out to volunteer users across China. The PiMi air boxes measure the approximate indoor particulate matter concentration, and the ambient temperate and humidity. When a user accesses the PiMi air box for his personal air quality data on his smartphone, the data is relayed to the backend PiMi cloud server for analysis. Accumulating large amount of indoor air quality data under different circumstances, the PiMi cloud server is able to use statistical learning methodologies to detect point of interests (POIs) in the data series, and asks users to label their activities or events at the POIs. Together with the user-reported physicality information on the indoor environments, PiMiair.org is able to quantitatively evaluate the impacts of the environment physicality and human behaviors on the indoor air quality, and mine the knowledges on how to alleviate indoor air pollution. We believe that by sharing these knowledge among the community, healthier breathing environments could be nurtured for the well-being of the public.