# Smart Helmet-Based Personnel Proximity Warning System for Improving Underground Mine Safety
## 4 Results  
Figure 9a shows the worker wearing a smart helmet when a BLE signal is not received, and Figure 9b shows the worker wearing a smart helmet when a BLE signal is received. The MAC address of the Bluetooth beacons to be attached to the mining equipment was stored in a personal PWS application program, and the smart helmet PWS was designed to provide visual alerts through LEDs when the BLE signals were received. Through the visual alarm, through LEDs, both the worker and driver can recognize the danger in advance and prevent accidents. Table 4 shows the statistics of the detection distance measurement when a proximity alarm was provided according to the change in the Tx power of the Bluetooth beacon, and Figure 10 shows the average detection distance per Tx power as a graph. The average detection distance is 2.9 m at \(-\)12 dBm, 6.0 m at \(-\)8 dBm, 27.1 m at \(-\)4 dBm, 62.7 m at 0 dBm, and 66.9m at 4 dBm. As the Tx power increased, the smart helmet's BLE signal detection distance also increased. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**BLE Signal Recognition Distance (m)**} & \multicolumn{5}{c}{**Signal Transmission Strength of Bluetooth Beacon**} \\ \cline{2-6}  & \(-\)**12 dBm** & \(-\)**8 dBm** & \(-\)**4 dBm** & **0 dBm** & **4 dBm** \\ \hline Mean & 2.9 & 6.0 & 27.1 & 62.7 & 66.9 \\ STD 1 & 1.4 & 3.8 & 3.0 & 11.5 & 8.7 \\ Max 2 & 6.0 & 12.0 & 30.0 & 74.0 & 79.0 \\ Min 3 & 1.0 & 3.0 & 22.0 & 35.0 & 50.0 \\ \hline \hline \end{tabular} \({}^{1}\) Standard deviation 2 Maximum value 3 Minimum value.  
\end{table} 
Table 4: Statistical analysis results of BLE signal detection distance (m) of the smart helmet according to the Tx power of Bluetooth beacon. Figure 9: Experimental results showing the performance of the smart-helmet based PWS. (**a**) Worker wearing the smart helmet when no BLE signal is received; (**b**) worker wearing the smart helmet when a BLE signal is received. Table 5 shows the statistics of the sensing distance measurement when a proximity alarm was provided according to the facing angle between the smart helmet and the Bluetooth beacon, and Figure 11 shows the average sensing distance per angle. The average sensing distance was measured to be over 20 m for angles of 0\({}^{\circ}\), 45\({}^{\circ}\) and 90\({}^{\circ}\), approximately 20 m for an angle of 135\({}^{\circ}\), and 10 m for an angle of 180\({}^{\circ}\). Therefore, it was confirmed that the average BLE signal detection distance was at least 10 m, regardless of the facing angle between the smart helmet and Bluetooth beacon. Figure 12 is a radial plot of the average value of the scores of the six workload parameters evaluated in three experiments for four types on 10 subjects. When the subjects used a smartphone-based personal PWS, scores on mental demand, time demand, physical demand, frustration, effort, and overall performance were all higher than when using a smart helmet-based personal PWS. This may be due to the fact that when a subject used a smartphone-based personal PWS while driving, they had to repeatedly check the smartphone screen to check whether the worker was approaching the vehicle and felt apprehensive due to increased eye movement. Conversely, when using a smart helmet-based personal PWS, the subjects could concentrate only on driving and receive a visual alert through the LED light of the smart helmet worn by the worker; therefore, both hands were relatively free compared to when using a smartphone-based personal PWS. Consequently, less workload is required to perform the task. Similar to using a smartphone-based personal PWS, when workers wore smart glasses-based personal PWS, mental, physical, and frustration scores were higher than when wearing smart helmet-based  
Figure 10: Average BLE signal detection distance of smart helmet according to Tx power of Bluetooth beacon (m).