Abstract
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 CO2 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.
Highlights
Most people spend approximately 80% to 90% of their time indoors; indoor air quality has a large impact on health and work efficiency [1]
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
Experimental results show the following: (i) the combination of the prediction module and the fuzzy logic-based model can control the CO2 concentration effectively; the results show that the CO2 concentration is controlled below the defined 1,000 ppm threshold. (ii) During lunch, as the workers are absent and most machines are in sleep mode, there is a sudden drop in CO2 concentration
Summary
Most people spend approximately 80% to 90% of their time indoors; indoor air quality has a large impact on health and work efficiency [1]. The research has shown that the use of air conditioners increases the amount of pollution in the air in closed spaces because of a lack of air exchange between indoors and outdoors, presenting a significant threat to our health [3]. Exposure to air that contains elevated levels of CO2 can lead to hyperventilation, increased heart rate, headaches, and vascular constriction. Sensing technology has progressed in recent years [5], so more researchers use the technology to monitor and assist individuals who live and work in these spaces [6,7,8,9]. The relevant components of this system, which involves hardware architecture, software architecture, system framework, and equations, are detailed
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