## 3 Results
### In Situ Monitoring Results  
In order to double-check the accuracy, confidence, and reliability of the proposed wireless DYU Air Box for monitoring environmental conditions of the classroom, the multi-sensor module including the BME680, PMS7003T, SCD30, and BH1750 sensors was evaluated using the above measurement instruments in the H708 teaching classroom from 1-31 October 2023. The observation data of in situ monitoring were forwarded to the public ThingSpeak IoT platform through the 802.1X Wi-Fi network. Therefore, the observation data of the IAQ value and IAQ level, PM\({}_{1.0}\)/PM\({}_{2.5}\)/CO\({}_{2}\) concentrations, brightness, ambient temperature, and humidity in the H708 classroom could be easily accessed in the environment of the ThingSpeak IoT platform. All on-site observations of sensing parameters were carried out at 1 min intervals in a 30-consecutive-day in situ experiment and then forwarded to the ThingSpeak IoT platform (channel ID: 1408273, available online: [[https://thingspeak.com/channels/1408273](https://thingspeak.com/channels/1408273)]([https://thingspeak.com/channels/1408273](https://thingspeak.com/channels/1408273)), accessed on 15 December 2023) [29] through the built-in 802.1X Wi-Fi network on campus. The proposed multi-sensor module was set up to monitor the environmental conditions in the classroom including IAQ index/level, PM\({}_{1.0/2.5}\) concentration, CO\({}_{2}\) concentration, brightness, temperature, and humidity. A screenshot of the ThingSpeak public channel for the environment-monitoring IoT system of the proposed DYU Air Box is shown in Figure 6. The observation data can be downloaded and further analyzed using MATLAB 2019b software or other big data analytics software packages. Taking the study case on 16 October 2023 as an example, the IAQ index and IAQ level, PM\({}_{1.0/2.5}\) and CO\({}_{2}\) concentration, brightness, temperature, and humidity were well exported and reconstructed using MATLAB 2019b software in a 24 h time frame in the H708 classroom in which the light intensity was almost synchronized with the sunrise at about 06:00 a.m., increased to the maximal brightness until 13:00 p.m. with east-south exposure, and became dark near 17:00 p.m. after work ended. The light was kept turned off until dawn next day and only at 17:35 did the security guard on campus turn on the light for a check. It should be noted that the brightness in the classroom is the combination of man-made illumination and solar irradiance; therefore, the brightness over 1000 lux between 10:10 and 14:00 partly came from the contribution of solar irradiation. The inlet of  
Figure 5: Photographs of the proposed wireless heterogeneous multi-sensor module: **(a)** TTGO ESP32 Wi-Fi module, BH1750 light sensor, BME680 AQI sensor, SCD30 CO\({}_{2}\) sensor, and PMS7003T dust sensor; **(b)** demo DYU Air Box for environmental monitoring of classroom. sunlight could increase the indoor temperature. As shown in Figure 7g, the indoor temperature started to soar after sunrise. The temperature was preset at 28 \({}^{\circ}\)C and controlled near 28 \({}^{\circ}\)C. Figure 7g further reveals the indoor temperature increased a little over the preset one and reached up to 29.4 \({}^{\circ}\)C, caused by the incoming solar irradiation. In addition, there is a 30 min time-delay response between brightness and ambient temperature which was caused by the thermal mass in the indoor thermodynamics. The humidity parameters shown in Figure 7h approximately reveal a close inverse proportion in contrast to the ambient temperature. The humidity reached the lowest level at 13:00 p.m. as the ambient temperature simultaneously rose up to 29.4 \({}^{\circ}\)C. The information of brightness, temperature, and humidity as shown in Figure 7f-h distinctly illustrates the comfort level in the H708 classroom under control and surveillance. Figure 6: Screenshot of the ThingSpeak public channel for the proposed DYU Air Box. Figure 7: _Cont._  
Figure 7: _Cont_.