An integrated indoor air quality monitoring system with pollutants recognition and enhanced indoor air quality index
Poor indoor air quality (IAQ) may pose threats to human’s health. The concentration level of harmful gases and contaminants in polluted indoor air is up to five times higher than in normal indoor air. In order to ensure that people breathe-in safe air comfortably in the indoor air environments, cont...
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| Format: | Thesis |
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| Language: | English |
| Subjects: | |
| Online Access: | http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/75761/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/75761/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/75761/3/Declaration%20Form.pdf |
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| Summary: | Poor indoor air quality (IAQ) may pose threats to human’s health. The concentration level of harmful gases and contaminants in polluted indoor air is up to five times higher than in normal indoor air. In order to ensure that people breathe-in safe air comfortably in the indoor air environments, continuous IAQ monitoring is deemed important. The main objective of this study is to develop an integrated indoor air quality monitoring system (IAQMS) with pollutants recognition and Enhanced Indoor Air Quality Index (EIAQI). The wireless IAQMS adopts an array of sensors including gas sensors, particle sensors and thermal sensors to detect multiple pollutant parameters at a relatively low cost as compared to the professional sensing devices. Overall, this study uses eight sensors to measure nine indoor air pollutants which are Oxygen (O2), Carbon Dioxide (CO2), Carbon Monoxide (CO), Ozone (O3), Nitrogen Dioxide (NO2), Volatile Organic Compounds (VOCs), Particulate Matter (PM), Temperature (Temp) and Relative Humidity (RH). This IAQMS has successfully recognized five sources of indoor air pollution with classification rate of 100%. These five sources of indoor air pollution are: ambient air, human activity, presence of chemical, presence of fragrance and presence of food and beverage, are successfully classified by Multilayer Perceptron (MLP) and KNearest Neighbour (KNN) using Vector Array Normalization (VAN) before Principle Component Analysis (PCA) feature. Finally, the last objective of this study is to integrate the IAQMS with EIAQI. This study proposes an EIAQI which comprises of three different indices: Indoor Air Quality Index (IAQI), Thermal Comfort Index (TCI) and Smell Index (SI). IAQI utilized the seven air parameters to measure the quality of indoor
air and shows the status of IAQ whether it is “Good”, “Moderate”, “Unhealthy” or “Hazardous”. This IAQI is developed using Air Quality Index (AQI) from the United States Environmental Protection Agency (US EPA) as its main reference. TCI applied the
same principle with IAQI. The TCI used Temp and RH to indicate the thermal comfort level of a room. Therefore, TCI status is shown either as “Most Comfort”, “Comfort”, “Less Comfort” or “Least Comfort”. In contrast with the IAQI and TCI which generate
their index based on single pollutant parameter, SI is generated based on an array of pollutant parameters. For example, IAQI is determined based on single pollutant that gives the lowest rate. SI on the other hand, generates the smell perceptions based on all nine pollutants input. The final result would be classified as either the smell is “Neutral”, “Pleasant” or “Unpleasant”. After all individual index has been obtained, an EIAQI is formulated which combines all the previous three indices. This EIAQI informs the users about the overall comfort status in the room. |
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