# Temperature Estimation Adaptive to Variables over Distance Using Infrared-LiDAR
## 4 Experimental Results
### Experiment: Performance of the Proposed Method  
In this section, temperature estimation for a specific distance is compared through three methods. The first method is the estimation result before temperature correction with a single mapping function at a close distance, the second method is the result of temperature correction through various variables provided by FLIR, and the third is the result through the proposed method. Temperature correction via variables provided by FLIR can be done in FLIR Tools [33] with temperature correction via emissivity, distance, atmospheric temprature, relative humidity, etc. Figure 15 can be obtained through the Tables 4-6, which are the results of temperature estimation through each method. It can be seen that the temperature estimation result before correction in Table 4 decreases as the distance increases due to the variable according to the distance. Furthermore, with the FLIR correction in Table 5, it is difficult to estimate the exact temperature because values of various variables are required. It can be seen from Table 6 that the proposed method of obtaining the distance through LiDAR and redefining the mapping function for each distance can accurately estimate the temperature at most distances.  
Table 7 shows the estimated results for each temperature at a distance (3.5 m, 7.5 m) not previously measured. In the proposed method, for distances not measured in advance, the temperature is estimated by obtaining a digital count using interpolation and defining a new mapping function. In particular, in this result, it can be seen that the temperature estimation error of the proposed method is low through Mean Square Error (MSE).  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & **0.3 m** & **1 m** & **2 m** & **3 m** & **4 m** & **5 m** & **6 m** & **7 m** & **8 m** & **9 m** & **10 m** \\ \hline
**30 °C** & 30.0 °C & 30.0 °C & 30.0 °C & 30.2 °C & 30.5 °C & 30.1 °C & 30.3 °C & 30.1 °C & 29.9 °C \\
**35 °C** & 35.1 °C & 35.0 °C & 35.0 °C & 35.2 °C & 35.1 °C & 35.2 °C & 35.0 °C & 35.1 °C & 35.1 °C & 34.9 °C \\
**40 °C** & 40.1 °C & 40.0 °C & 40.0 °C & 40.1 °C & 40.0 °C & 40.0 °C & 40.1 °C & 40.0 °C & 39.9 °C & 40.0 °C & 39.9 °C \\ \hline \hline \end{tabular}
\end{table}
Table 6: The temperature estimation result from the proposed method.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & **0.3 m** & **1 m** & **2 m** & **3 m** & **4 m** & **5 m** & **6 m** & **7 m** & **8 m** & **9 m** & **10 m** \\ \hline
**30 °C** & 30.0 °C & 29.3 °C & 28.9 °C & 28.6 °C & 28.4 °C & 28.7 °C & 28.0 °C & 28.1 °C & 27.9 °C & 27.5 °C & 27.5 °C \\
**35 °C** & 35.1 °C & 34.2 °C & 33.7 °C & 33.3 °C & 33.2 °C & 33.0 °C & 32.7 °C & 32.6 °C & 32.5 °C & 32.4 °C & 32.2 °C \\
**40 °C** & 40.1 °C & 39.1 °C & 38.5 °C & 38.1 °C & 37.9 °C & 37.6 °C & 37.5 °C & 37.3 °C & 37.0 °C & 36.9 °C & 36.8 °C \\ \hline \hline \end{tabular}
\end{table}
Table 4: The temperature estimation result from mapping function at a close distance (before correction).  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & **0.3 m** & **1 m** & **2 m** & **3 m** & **4 m** & **5 m** & **6 m** & **7 m** & **8 m** & **9 m** & **10 m** \\ \hline
**30 °C** & 32.2 °C & 31.5 °C & 31.0 °C & 30.7 °C & 30.6 °C & 31.0 °C & 30.1 °C & 30.3 °C & 30.0 °C & 29.6 °C & 29.9 °C \\
**35 °C** & 37.5 °C & 36.6 °C & 36.0 °C & 35.7 °C & 35.5 °C & 35.4 °C & 35.0 °C & 34.9 °C & 34.8 °C & 34.7 °C & 34.4 °C \\
**40 °C** & 42.7 °C & 41.7 °C & 41.1 °C & 40.6 °C & 40.3 °C & 40.1 °C & 40.0 °C & 39.9 °C & 39.9 °C & 39.9 °C \\ \hline \hline \end{tabular}
\end{table}
Table 5: The temperature estimation result from FLIR Tools + (FLIR correction).