A. A. Bezerra, Davi H. dos Santos, L. M. Gonçalves
{"title":"Real-Time Air Quality Monitoring Using Sensors to Prevent Severe Acute Respiratory Syndromes (SARS)","authors":"A. A. Bezerra, Davi H. dos Santos, L. M. Gonçalves","doi":"10.5753/sibgrapi.est.2022.23281","DOIUrl":null,"url":null,"abstract":"This work presents the development, calibration, and validation of a device capable of actively capturing data related to the measurement of air quality for future prevention. This data can then be compared with pandemic/endemic data indices by location using PM2.5, temperature, and humidity sensors, along with a microcontroller capable of sending all necessary information to a database. As it is a project that needs a large scale so that it is possible to capture air quality indices in as many points as possible in order to obtain data with very high granularity, the development is always being thought of, always viewing the cost-effectiveness of the components used for replicating is possible, and also the development is part of a larger project, which should provide the community with a complete platform capable of providing real-time air quality data.","PeriodicalId":182158,"journal":{"name":"Anais Estendidos do XXXV Conference on Graphics, Patterns and Images (SIBGRAPI Estendido 2022)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anais Estendidos do XXXV Conference on Graphics, Patterns and Images (SIBGRAPI Estendido 2022)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5753/sibgrapi.est.2022.23281","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This work presents the development, calibration, and validation of a device capable of actively capturing data related to the measurement of air quality for future prevention. This data can then be compared with pandemic/endemic data indices by location using PM2.5, temperature, and humidity sensors, along with a microcontroller capable of sending all necessary information to a database. As it is a project that needs a large scale so that it is possible to capture air quality indices in as many points as possible in order to obtain data with very high granularity, the development is always being thought of, always viewing the cost-effectiveness of the components used for replicating is possible, and also the development is part of a larger project, which should provide the community with a complete platform capable of providing real-time air quality data.