# System for Indoor Comfort and Health Monitoring Tested in Office Building Environment
## 6 Conclusions  
IoT-based smart sensor systems have significant potential for sensitive housing-related aspects of comfort, health, productivity and energy efficiency in buildings. The IoT system for indoor comfort and health monitoring developed and presented within this article has focused on the following parameters' variation: temperature, relative humidity, CO2, TVOC, HCHO and PM. Additionally, \({}^{222}\)Rn has been monitored using an independent sensor. The testing of the monitoring system over a one-week period showed that the proposed solution operated adequately, representing a reliable tool for data acquisition via the Arduino IoT Cloud. Generally, for the preliminary testing period, the registered values using the IoT system fell within the recommended values mentioned in the paper. However, the analysis of the recorded data showed that thermal comfort was low for more than 90% of the working time in the two office spaces and for more than 80% in the PV-testing laboratory, respectively. Still, the relative humidity values were below 60%. Also, some increased values were observed in the case of CO2, TVOC, HCHO and PM. Up to 1500 ppm CO2 values were measured in the late afternoon when the spaces became unventilated, given the fact that the doors and windows were not opened. Thus, special attention must be paid to natural ventilation or to the improvement of building characteristics, as well as to increasing the cleaning frequency of the premises. The measured data showed that the current weekly cleaning interval is not sufficient, leading to high indoor PM accumulation. Also, the time intervals when experiments in the Chemical Analysis and Testing Laboratory are carried out should be communicated to other personnel from the nearest offices. Significant variation in TVOCs was registered when experiments were carried out, leading to a peak of 1000 ppb. As regards the HCHO parameters, formaldehyde-releasing equipment led to a temporary increase to 0.07 ppm. Therefore, more appropriate ventilation or better isolation between the office spaces and the laboratory must be considered. It is worth recalling that the monitored spaces are located in a relatively old building with reduced retrofitting over time. The results show the need for new and improved retrofitting actions in order to eliminate the spreading of volatile pollutants and increase the occupants' comfort. A holistic approach that takes into account the human factor, the particular needs of the occupants, their behaviour and the integration of the developed system into the inhabited built space can lead to sustainable results. In terms of scientific impact, it is noted that the program running on Arduino MKR WiFi 1010 was custom-made for the specific application envisaged within our work. It can be easily upgraded in order to control HVAC devices, such as heat recovery fans or air-conditioning systems, when the quality of the indoor air is below the set thresholds. Energy parameters are also taken into account for further monitoring using the same code in order to establish a correlation between energy demand and air quality. In this way, the system will determine how much energy is needed to maintain optimal living and working conditions in the monitored environment. Furthermore, the measured parameters were analysed and discussed when certain values fell outside the comfort and health ranges. Moreover, there were proposed measures to be taken to reestablish the indoor air quality, and there were identified causes leading to some values of the monitored parameters exceeding thresholds. In the future, the IoT system will be improved either by adding other sensors for monitoring parameters and correlating them with occupancy levels or by setting thresholds for certain values of the parameters. Sensors for occupancy and open/closed doors and windows can be integrated, leading to better data correlations and local pattern prediction.