# Smart Helmet-Based Personnel Proximity Warning System for Improving Underground Mine Safety
## 6 Conclusions  
In this study, we developed a personal PWS that uses a smart helmet to receive BLE signals from Bluetooth beacons and provides visual proximity alerts to pedestrians and equipment operators. The smart helmet-based PWS could provide bidirectional proximity warnings to equipment operators and pedestrians in mines. A performance evaluation was conducted at an actual underground mine site to evaluate the performance of the personal PWS developed in this study. The BLE signal detection distance of the smart helmet was measured according to the Tx power of the Bluetooth beacon and the facing angle between the Bluetooth beacon and the smart helmet. The average BLE signal recognition distance was 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 66.9 m at 4 dBm. As the Tx power of the Bluetooth beacon increased, the BLE signal recognition distance of the smart helmet increased. In addition, when considering the facing angle between the smart helmet and Bluetooth beacon with a Tx power of \(-\)4 dBm, it was confirmed that the average BLE signal detection distance was at least 10 m regardless of the facing angle. The workload of the individual PWS for 10 subjects was quantitatively analyzed using the NASA-TLX evaluation method. The use of smart helmets to provide visual proximity alerts reduced mental effort and stress, and freed the hands of workers to maintain work efficiency. The overall workload score calculated when using the smart helmet was lower than when using the smart phone-based PWS and the smart glass-based PWS. Therefore, a smart helmet is suitable for implementing personal PWSs at the mining site.  
In future work, smart helmet-based personal PWS can be expanded by adding sensors to the Arduino board. For example, a heart rate sensor or an alcohol sensor can be added to check the condition of the worker. Furthermore, by adding a temperature, humidity, methane gas, and carbon monoxide sensor, the environment at the mine site can be monitored, and when a high concentration of harmful gases is detected, the pedestrian worker can be warned of danger. The worker could then follow appropriate protocols to ensure safety.  
Conceptualization, Y.C.; methodology, Y.C., J.B. and Y.K.; software, Y.C.; validation, J.B. and Y.K.; formal analysis, J.B. and Y.K.; investigation, Y.C.; resources, Y.C.; data curation, Y.K.; writing--original draft preparation, Y.C., J.B. and Y.K.; writing--review and editing, Y.C.; visualization, J.B. and Y.K.; supervision, Y.C.; project administration, Y.C.; funding acquisition, Y.C. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2021R1A2C1011216).  
This study was approved by IRB of Pukyong National University (1041386-202102-HR-4-02).  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
Data Availability Statement: Not applicable.  
Acknowledgments: [PERSON] and [PERSON] contributed equally as co-first authors.  
Conflicts of Interest: The authors declare no conflict of interest.