Monitoring and Prediction of Indoor Air Quality for Enhanced Occupational Health
نویسندگان
چکیده
The amount of moisture in the air is represented by relative humidity (RH); an ideal level interior environment between 40% and 60% at temperatures 18° 20° Celsius. When RH falls below this level, becomes dry, which can cause skin dryness, irritation, discomfort low temperatures. rises above 60%, a wet atmosphere develops, encourages growth mold mites. Asthma allergy symptoms may occur as result. Human health harmed excessive or lack thereof. Dehumidifiers be used to provide optimal stable pleasant atmosphere; certain models disinfect purify water, reducing spread bacteria. design implementation client-server indoor outdoor quality monitoring application are presented paper. Netatmo station was acquire data needed application. client Android that allows user monitor over period their choosing. For good process, modules were collect from both environments (indoor: temperature (T), RH, carbon dioxide (CO2), atmospheric pressure (Pa), noise outdoor: T RH). stored database, using MySQL. view evolution measured parameters form graphs. Also, paper presents prediction model Azure Machine Learning Studio (Azure ML Studio). evaluated metrics: Mean Absolute Error (MAE), Root Squared (RMSE), Relative (RAE), (RSE) Coefficient Determination (CoD).
منابع مشابه
Monitoring Indoor Air Quality to Improve Occupational Health
Indoor environments are characterized by several pollutant sources. As people typically spend more than 90% of their time in indoor environments. Thus, indoor air quality (iAQ) is recognized as an important factor to be controlled for the occupants’ health and comfort. The majority of the monitoring systems presently available is very expensive and only allow to collect random samples. This wor...
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ژورنال
عنوان ژورنال: Intelligent Automation and Soft Computing
سال: 2023
ISSN: ['2326-005X', '1079-8587']
DOI: https://doi.org/10.32604/iasc.2023.025069