# Real-Time Monitoring of Indoor Air Quality with Internet of Things-Based E-Nose
## 4 Results and Discussion
As a result of natural ventilation, the indoor concentration of CO is seen to fall from 6.51 mg m\({}^{-3}\) to 0.4 mg m\({}^{-3}\), NO\({}_{2}\) concentration from 54.7 \(\upmu\)g m\({}^{-3}\) to 38.6 \(\upmu\)g m\({}^{-3}\) and CO\({}_{2}\) concentration from 608 \(\upmu\)g m\({}^{-3}\) to 282 \(\upmu\)g m\({}^{-3}\). As a result of one hour of natural ventilation, the increased gas concentrations in the closed and unventilated environment resulted in a significant decrease of 93.8% in CO, 29.4% in NO\({}_{2}\) and 53.6% in CO\({}_{2}\). Figure 7 shows the minimum, maximum and average values of daily gas concentrations. When the values given in Figure 7 are examined, it is seen that the largest variance is observed in the CO concentration. The CO values increased by nine times on day 1 and 16 times on day 3. Similarly, CO\({}_{2}\) concentration increased by 1.36 times on day 2. NO\({}_{2}\), with a lower change, increased by half on day 4 and PM\({}_{10}\) concentration increased by half on day 2. Figure 5: Daily changes of PM and gases, (**a**) PM\({}_{10}\), (**b**) CO\({}_{2}\), (**c**) CO, (**d**) NO\({}_{2}\). Figure 6: Hourly changes of climate parameters and gases values of day 3, (**a**) PM\({}_{10}\) - CO\({}_{2}\), (**b**) NO\({}_{2}\)-CO, (**c**) temperature, (**d**) humidity. The daily average concentration values of indoor CO gas are as follows: 3.21, 2.75, 2.65 and 3.40 mg m\({}^{-3}\), daily concentrations of NO\({}_{2}\), 47.9, 49.2, 45.6 and 42.8 \(\upmu\)g m\({}^{-3}\), CO\({}_{2}\), with mean values of 500, 426, 394 and 424 \(\upmu\)g m\({}^{-3}\) and PM\({}_{10}\) 30.2, 31.1, 28.8 and 30.1 \(\upmu\)g m\({}^{-3}\). The correlation relationships between air quality dates have been estimated by the Konstanz Information Miner (KNIME) \"Linear Correlation\" algorithms. Figure 8 shows the linear correlation workflow of KNIME. Tables 3-5 demonstrate the period 3 linear correlation matrices on 22.03.2019. Table 3 demonstrates the period 1 linear correlation matrix. There was a positive correlation between CO-CO\({}_{2}\), NO\({}_{2}\)-humidity and NO\({}_{2}\)-temperature at values of 0.943, 0.871, 0.755, respectively, during the period when the household was asleep. In addition, there were 0.979, 0.911 positive and 0.941 negative correlations between time-CO, time-CO\({}_{2}\) and time-NO\({}_{2}\), respectively. There was a strong negative correlation between climate parameters and values of CO and CO\({}_{2}\) and a strong positive correlation between climate parameters and values of NO\({}_{2}\). On the other hand, the correlation between PM10 and gas concentrations and climate parameters were minuscule. The findings indicate that in period 1 there was an elevated positive and negative correlation between gas concentrations and climatic parameters, which represents sleep hours. Figure 8: Workflow of Linear Correlation in KNIME application. Figure 7: Minimum, maximum and average values of daily gas concentrations and PM, (**a**) PM\({}_{10}\), (**b**) CO\({}_{2}\), (**c**) CO, (**d**) NO\({}_{2}\)  
Table 4 demonstrates the period 2 linear correlation matrix. There was a positive correlation between CO-CO\({}_{2}\). CO-NO\({}_{2}\) and NO\({}_{2}\)-CO\({}_{2}\) at values of 0.966, 0.881, 0.861, respectively, and a negative correlation of 0.915 for temperature-humidity during this period, in which households are undertaking domestic activities (cooking, cleaning, washing, etc.). There were strong negative correlations between time, CO, CO\({}_{2}\), humidity and NO\({}_{2}\) at \(-0.844\), \(-0.752\), \(-0.735\) and \(-0.669\) during this period. In addition, this period's correlations between PM\({}_{10}\) value and gas levels and climate parameters were very low. The linear correlation matrix provided in Table 5 belongs to period 3, in which families carry out activities such as eating and resting. There was a positive correlation between CO-NO\({}_{2}\) and CO-CO\({}_{2}\) at 0.833, 0.671, respectively, during this period.