# Design and Implementation of an IoT-Based Smart Classroom Incubator
## 4 Discussion  
In this study, research on the measurement and control of the physical conditions of learning environments in the literature was reviewed, and the result of a comparison between previous research and this study is given in Table 4. As can be seen, previous research has rather focused on the measurement of parameters in learning environments; the number of the measured parameters was usually 1, and a maximum of 3 parameters were measured in two studies. In experimental studies, only 1 parameter was measured with a standard measuring instrument in general. In few studies, 3 parameters were only measured but not controlled. As seen in Table 4, the number of studies involving automation and control processes on this subject, in other words, applications, is quite limited in the literature. In this limited number of studies, only one parameter was usually measured and controlled. Furthermore, the number of studies in which more than one parameter was controlled simultaneously is 2. The number of studies on temperature control is only 2. The number of model studies is also limited. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Classification** & **Classification** & **Classification** & **Classification** & **Classification** & **Classification** & **Classification** & **Classification** & **Classification** & **Classification** & **Classification** \\ \hline Physical Conditions & 2 & & & & & & & & & & \\ Physical Conditions & 3 & & & & & & & & & \\ Physical Conditions & 4 & & & & & & & & & \\ Physical Conditions & 5 & & & & & & & & & \\ Physical Conditions & 6 & & & & & & & & & \\ Physical Conditions & 7 & & & & & & & & & \\ Physical Conditions & 8 & & & & & & & & & \\ Physical Conditions & 9 & & & & & & & & & \\ Physical Conditions & 10 & & & & & & & & & \\ Physical Conditions & 11 & & & & & & & & & \\ Physical Conditions & 12 & & & & & & & & & \\ Physical Conditions & 13 & & & & & & & & & \\ Physical Conditions & 14 & & & & & & & & & \\ Physical Conditions & 15 & & & & & & & & & \\ Physical Conditions & 16 & & & & & & & & & \\ Physical Conditions & 17 & & & & & & & & & \\ Physical Conditions & 18 & & & & & & & & & \\ Physical Conditions & 19 & & & & & & & & & \\ Physical Conditions & 20 & & & & & & & & & \\ Physical Conditions & 21 & & & & & & & & & \\ Physical Conditions & 22 & & & & & & & & & \\ Physical Conditions & 23 & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Work comparison. Figure 15: Average score chart of the five tests applied in classical and smart classrooms. Since all parameters of the learning environment affect learning efficiency, the subject was approached holistically from two aspects in this study. First, this study incorporates hardware, software, experimental studies, case studies, and survey studies. Second, a higher number of necessary parameters were measured and controlled. For this reason and other reasons mentioned in this study, the system and the environment in which it was installed were called a smart classroom incubator (SCI). Unlike previous studies, not only methods used in educational sciences and social sciences but also engineering techniques and methods were employed effectively and in depth in the system design. The parameters measured in this study were sound intensity, temperature, relative humidity rate, light intensity, air quality, and ambient pollution. The parameters to be controlled were temperature, automatically controlled position-based lighting, improved air quality, and ambient cleanliness. As can be seen, more parameters were measured and controlled. Moreover, temperature control, one of the most variable parameters in the environment and therefore one of the most effective parameters on human comfort, convenience, and thus performance, was studied, and control processes were individualized as the temperature level preference changes more from person to person.