# Automatic Mobile Warning System against People with Elevated Body Temperature
## 4 Conclusions  
The presented method, due to its effectiveness and speed of object detection, can be used as an element of a warning system against people with elevated body temperature with generally available mobile devices. The detection of people with elevated body temperature (above 35 \({}^{\circ}\)C) was carried out with 100% efficiency, whereas the classification of the range of distance to warm objects (head area) had 73-100% efficiency. The algorithm was tested on a set of 4233 images containing cases with different clothing, visibility of \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Distance** & **Accuracy** & **Accuracy** & **Number of Test Images** \\
**to Person** & \(\mathbf{\Delta_{AP}>0}\) & \(\mathbf{\Delta_{AP}>3}\) & **4233** \\ \hline Sequence 1—Figure 7 (All ranges) & 88\% & 98\% & 468 \\  
\hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of effectiveness of distance-detection methods with proposed solution. different body parts (neck, forearms), different head positions relative to the camera, and one or two people while maintaining the initial assumptions. The most important features of the proposed solution are the use of a single thermal camera for distance assessment, a fully automatic detection and distance classification block, and high-speed operation. The cases of one or two people were considered. To recognize people on the images, we used the embedded in OpenCV face detector (based on Haar Cascade). This detector was trained in over 1000 (face/nonface) thermovision images, as was conducted in [22], and was effective because the facial areas were initially selected on the basis of facial temperature. Given that the detection of a person with elevated temperature was carried out with 100% efficiency, a person using the system would be warned sufficiently early about an existing threat, and additional information about the distance (with 73-100% efficiency) would only increase their vigilance. Therefore, the possibility of contact with a potentially sick person is signalled much earlier than the system user approaching that person. A mobile thermal camera with a frequency of 8 fps and \(320\times\ 240\) resolution (upscaled) was used for determining the distance, which significantly limited the accuracy of distance measurements. The use of a better camera would increase precision, which allows for developing the system so that it can determine distances with accuracy of 0.5 or 0.25 m. The research results obtained at this stage show that the effective monitoring of and protection against sick people is possible using the described devices and solutions. The function of detecting an approaching person (with temperature above 35 \({}^{\circ}\)C ) was tested on a mobile device in the form of a smartphone with the following hardware configuration: 8-core processor clocked at 2.2 GHz and 6 GB RAM). The hardware capabilities and reserves offered by this type of devices allow for further expansion by implementing more advanced methods of thermal-image analysis. When developing the presented method to further improve its efficiency, it is worth considering the use of information from the mobile device's motion sensors (which enriches the application with absolute data describing the camera movement) or the use of a thermal camera with higher optical resolution. It is also important to develop the method to be able to track and detect more than one object, but this may need more advanced methods of locating and tracking faces. Conceptualization, methodology, and software: M.M. ; validation, M.M. and S.W. ; formal analysis, M.M. ; investigation: M.M. and S.W. ; resources and data curation, M.M. ; writing--original draft preparation: M.M. and S.W. ; writing--review and editing, visualization, supervision, and project administration, M.M. ; funding acquisition, M.M. and S.W. Both authors have read and agreed to the published version of the manuscript.