An Intelligent Wireless Sensing and Control System to Improve Indoor Air Quality: Monitoring, Prediction, and Preaction
The aim of this study is to construct an intelligent wireless sensing and control system to address health issues. We combine three technologies including (1) wireless sensing technology to develop an extendable system for monitoring environmental indicators such as temperature, humidity and CO 2 co...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-08-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/140978 |
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| _version_ | 1832547215894118400 |
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| author | Tsang-Chu Yu Chung-Chih Lin |
| author_facet | Tsang-Chu Yu Chung-Chih Lin |
| author_sort | Tsang-Chu Yu |
| collection | DOAJ |
| description | The aim of this study is to construct an intelligent wireless sensing and control system to address health issues. We combine three technologies including (1) wireless sensing technology to develop an extendable system for monitoring environmental indicators such as temperature, humidity and CO 2 concentration, (2) ARIMA (autoregressive integrated moving average) to predict air quality trends and take action before air quality worsens, and (3) fuzzy theory which is applied to build an energy-saving mechanism for feedback control. Experimental results show the following. (1) A longer historical data collected time interval will reduce the effects of abnormal surges on prediction results. We find the ARIMA prediction model accuracy improving from 3.19 ± 3.47% for a time interval of 10 minutes to 1.71 ± 1.45% for a time interval of 50 minutes. (2) The stability experiment shows that the error rate of prediction model is also less than 7.5%. (3) In the energy-saving experiment, fuzzy logic-based decision model can reduce the 55% energy while maintaining adequate air quality. |
| format | Article |
| id | doaj-art-467484fdab6148618056477be9ce5921 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-467484fdab6148618056477be9ce59212025-02-03T06:45:30ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-08-011110.1155/2015/140978140978An Intelligent Wireless Sensing and Control System to Improve Indoor Air Quality: Monitoring, Prediction, and PreactionTsang-Chu YuChung-Chih LinThe aim of this study is to construct an intelligent wireless sensing and control system to address health issues. We combine three technologies including (1) wireless sensing technology to develop an extendable system for monitoring environmental indicators such as temperature, humidity and CO 2 concentration, (2) ARIMA (autoregressive integrated moving average) to predict air quality trends and take action before air quality worsens, and (3) fuzzy theory which is applied to build an energy-saving mechanism for feedback control. Experimental results show the following. (1) A longer historical data collected time interval will reduce the effects of abnormal surges on prediction results. We find the ARIMA prediction model accuracy improving from 3.19 ± 3.47% for a time interval of 10 minutes to 1.71 ± 1.45% for a time interval of 50 minutes. (2) The stability experiment shows that the error rate of prediction model is also less than 7.5%. (3) In the energy-saving experiment, fuzzy logic-based decision model can reduce the 55% energy while maintaining adequate air quality.https://doi.org/10.1155/2015/140978 |
| spellingShingle | Tsang-Chu Yu Chung-Chih Lin An Intelligent Wireless Sensing and Control System to Improve Indoor Air Quality: Monitoring, Prediction, and Preaction International Journal of Distributed Sensor Networks |
| title | An Intelligent Wireless Sensing and Control System to Improve Indoor Air Quality: Monitoring, Prediction, and Preaction |
| title_full | An Intelligent Wireless Sensing and Control System to Improve Indoor Air Quality: Monitoring, Prediction, and Preaction |
| title_fullStr | An Intelligent Wireless Sensing and Control System to Improve Indoor Air Quality: Monitoring, Prediction, and Preaction |
| title_full_unstemmed | An Intelligent Wireless Sensing and Control System to Improve Indoor Air Quality: Monitoring, Prediction, and Preaction |
| title_short | An Intelligent Wireless Sensing and Control System to Improve Indoor Air Quality: Monitoring, Prediction, and Preaction |
| title_sort | intelligent wireless sensing and control system to improve indoor air quality monitoring prediction and preaction |
| url | https://doi.org/10.1155/2015/140978 |
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