## 1 Introduction
### Background and Related Works
#### 1.1.1 Physical Environment and Smart Classrooms  
Some research works focus on taking a smart classroom as a tool to measure lecture quality. In [8], authors use sensors to retrieve features, such as noise level, CO\({}_{2}\) level, temperature, humidity, lecturers' voice, and lecturers' motion, in smart classrooms. Collected data are evaluated by various classification algorithms. The result shows that CO\({}_{2}\) level, temperature, humidity, and noise level are the main environmental factors that affect lecture quality. The relationship between physical environment and students' focus during lectures was analyzed in [9]. The level of CO\({}_{2}\), temperature, air pressure, humidity, noise, and lecturer's voice were collected with IoT devices. The analysis shows that the level of CO\({}_{2}\), the average value of the absolute deviations of the received noise, and the combination of temperature and humidity have a significant impact on students' focus. In Reference [10], the relationship between students' perceived effectiveness of educational technologies, learning motivation, participation, and learning outcome was discussed. The analysis shows that, in the smart classroom, the relationship between students' learning outcome and participation was positive while motivation and perceived effectiveness of technologies were not related to students' learning outcome. Responses from students related to cold temperature, seat number, classroom location, chair design, relaxing atmosphere reflected that physical environment was an important factor to be considered in smart classroom design [10]. In Reference [11], history changes in classroom design were reviewed and various kinds of new classroom design projects in higher education institutes in the US, such as Student-Centered Active Learning Environment for Undergraduate Programs (SCALE-UP) of the North Carolina State University, Technology Enabled Active Learning (TEAL) of the Massachusetts Institute of Technology, Active Learning Classrooms (ALC) of the University of Minnesota, were also reviewed. Questionnaire surveys about the effects of ALC were conducted in Reference [11]. The result shows that in traditional classroom seating positions discriminate students' learning experiences, and ALC did not produce positional discrimination. In Reference [12], a web survey about the Future Classroom Lab (FCL) [13] by European Schoolnet [14] was applied. Learning zones [15], such as interact, present, develop, investigate, create, and exchange, were designed in FCLs for different kinds of goals. The result shows that the physical space of the FCL is perceived as positive. In Reference [16], a teaching model based on smart classroom for financial accounting courses was proposed. Five dimensions, including showing, manageable, accessible, real-time interactive, and testing, of smart classrooms are summarized. Environment factors, such as air, sound, color, smell, light, temperature, humidity, attendance, monitoring, were also summarized in Reference [16].  
As a summary, classroom design, such as seat arrangement, and environmental factors, such as CO\({}_{2}\) level and temperature, were related to teaching and learning quality. Therefore, classroom seat design and environment factors were taken as essential elements of the proposed smart classroom architecture.