# Influence of Particulate Matter and Carbon Dioxide on Students' Emotions in a Smart Classroom
## 2 Materials and Methods
### Environmental Kit Data Collection  
To obtain environmental data for the present study, a custom-designed device was used. It is labeled ACTUA-096 kit and belongs to the ACTUA Project [34]. The project was started during the COVID-19 pandemic in May 2021. The project applies technology and data analysis to investigate the transmission of respiratory viruses, such as SARS-CoV-2, the virus causing COVID-19, in school classrooms. Identical devices to the ACTUA-096 kit (Universitat Rovira i Virgili (URV), Tarragona, Spain) were mainly placed in kindergarten and elementary school classrooms, but in our case, the device was placed in a secondary school as well. This project also includes the development of a monitoring tool that tracks various contextual variables, as well as a data analysis infrastructure to process the collected information.  
The environmental monitoring kit (Figure 1) is a 20 \(\times\) 20 \(\times\) 10 cm box enclosed by a wooden base and perforated sheet, which contains a single-board computer, a Raspberry Pi, and a range of sensors that capture the contextual variables of this study, among others to measure CO\({}_{2}\) concentration and PM. These sensors are connected to the Raspberry Pi through cables inside the kit itself [34]. The specific relevant sensors for the present study are a Sensirion SCD30 (Sensirion AG, Stafa, Switzerland) for the CO\({}_{2}\) concentration, and a Plantower PMS5003 (Shenzhen Planck Technology Co., Ltd. (Plantower), Shenzhen, China) for the PM. The SCD30 is a calibrated and linearized sensor module that uses NDIR technology for detecting CO\({}_{2}\). The PMS5003 is a particle concentration sensor based on laser-scattering of the airborne particles, from which equivalent particle diameter and the number of particles within size ranges per unit volume are calculated in situ based on MIE theory. Each environmental kit in the ACTUA Project (over 130 kits) was tested after assembly under different ambient conditions by comparing the outputs from the sensors of our kit to those of a reference kit that had previously been tested extensively against factory-calibrated instruments. The temperature and humidity outputs from the SCD30 sensor of the reference kit were compared against those from a Vaisala HM41 m (Vaisala Oyj, Vantaa, Finland), while its CO\({}_{2}\) values against those of a Vaisala GM70 carbon dioxide meter with a GMP222 probe (Vaisala Oyj, Vantaa, Finland) (with VSL traceable calibration). The PM\({}_{\rm x}\) values of the reference kit from the PMS5003 sensor were compared against those obtained with a TSI AeroTrak 9306 (TSI Incorporated, Shoreview, MN, USA) optical particle counter (with NIST traceable calibration). More than 130 kits were tested in this way in the ACTUA Project, including the kit used in this study (096).  
To control the parameters and monitor the environmental parameters as efficiently as possible, the kit was placed at a strategic point, near the classroom entrance door to be able to connect it to an external sensor that detects whether the door is open or closed. See Table 2 for the technical specifications and precision of the sensors.  
The kit measures every 10 min a range of variables to monitor conditions inside the classroom, such as temperature, ambient humidity, CO\({}_{2}\) concentration, and various PM concentrations, among others. To measure classroom conditions (see Table 2), the ACTUA Project has developed an IoT-based contextual variable monitoring platform that facilitates the achievement and deployment of sensory systems with network connectivity capabilities. This device sends data collected every 8 h to the ACTUA Project server via the Internet. The server stores all the information in a single database and provides a web application capable of managing and visualizing all the system data.