Journal of Convergence for Information Technology (융합정보논문지)

Convergence Society for SMB (중소기업융합학회)
권호 표지
DOI QR코드

DOI QR Code

A Study on Real-Time Detection of Physical Abnormalities of Forestry Worker and Establishment of Disaster Early Warning IOT

임업인의 신체 이상 징후 실시간 감지 및 재해 조기경보 사물인터넷 구축에 관한 연구

  • Received : 2021.04.09
  • Accepted : 2021.05.20
  • Published : 2021.05.28
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we propose the construction of an IOT that monitors foresters' physical abnormalities in real time, performs emergency measures, and provides alarms for natural disasters or heatstroke such as a nearby forest fire or landslide. Nodes provided to foresters include 6-axis sensors, temperature sensors, GPS, and LoRa, and transmit the measured data to the network server through the gateway using LoRa communication. The network server uses 6-axis sensor data to determine whether or not a forester has any signs of abnormal body, and performs emergency measures by tracking GPS location. After analyzing the temperature data, it provides an alarm when there is a possibility of heat stroke or when a forest fire or landslide occurs in the vicinity. In this paper, it was confirmed that the real-time detection of physical abnormalities of foresters and the establishment of disaster early warning IOT is possible by analyzing the data obtained by constructing a node and a gateway and constructing a network server.

본 논문에서는 임업인의 신체 이상 징후를 실시간 모니터링하여 응급 조치를 수행함과 동시에 인근의 산불이나 산사태와 같은 자연재해 또는 열사병에 대한 알람을 제공하는 IOT 구축을 제안한다. 임업인에게 제공되는 노드에 6축 센서, 온도 센서, GPS, LoRa를 포함하도록 하고, LoRa 통신을 이용하여 측정된 데이터를 게이트웨이를 통해 네트워크 서버에 송신한다. 네트워크 서버는 6축 센서 데이터로 임업인의 신체 이상 징후 여부를 판단한 후 GPS 위치를 추적하여 응급 조치를 수행한다. 온도 데이터를 분석한 후 열사병 가능성이 있는 경우 또는 인근에서 산불 및 산사태가 발생했을 경우에 알람을 제공한다. 본 논문에서는 노드 및 게이트웨이를 제작하고, 네트워크 서버를 구축하여 얻은 데이터를 분석하여 임업인의 신체 이상 징후 실시간 감지 및 재해조기경보 IOT 구축이 가능함을 확인하였다.

Keywords

References

  1. KOSTAT. (2019). 2019 Agriculture, Forestry and Fisheries Survey Results : Statistics Korea, (Online). http:kostat.go.kr
  2. Korea Forest Service. (2019). 2019 Forestry Management Survey. : Korea Forest Service. (Online). https://www.forest.go.kr
  3. Ministry of Employment and Labor. (2020). 2020 Industrial Accident Status Statistical Information Report. : Ministry of Employment and Labor. (Online). http://www.moel.go.kr
  4. Korea Forest Service. (2020). 2020 Forest Fire Statistical Yearbook. : Korea Forest Service. (Online). https://www.forest.go.kr
  5. T. J Sheng et al. (2020). An Internet of Things Based Smart Waste Management System Using LoRa and Tensorflow Deep Learning Model. IEEE Access, 8, 148793-148811. DOI : 10.1109/ACCESS.2020.3016255
  6. J. H. Seo, N. H. Kim & S. Y. Hong. (2019). Implementation of the Industrial Hazard Detection System using LoRa Network. Journal of Information Technology Services, 18(1), 141-151. DOI : 10.9716/KITS.2019.18.1.141
  7. S. H. Park & M. S. Park. (2020). Measuring Inner or Outer Position of Ship Passenger and Detection of Dangerous Situations based LoRa WAN Communication. Journal of Korea Multimedia Society, 23(2), 282-292. DOI : 10.9717/kmms.2020.23.2.282
  8. S. J. Lee, J. H. Choi, C. S. Seo, B. K. Park & B. Y. Choi. (2020). Implementation of Smart Shoes for Dementia Patients using Embedded Board and Low Power Wide Area Technology. Journal of the Korea Institute of Information and Communication Engineering, 24(1), 100-106. DOI : 10.6109/jkiice.2020.24.1.100
  9. H. V. Kim et al. (2018). A Wearable Wrist Band-Type System for Multimodal Biometrics Integrated with Multispectral Skin Photomatrix and Electrocardiogram Sensors. Sensors, 18(8), 2738. DOI : 10.3390/s18082738
  10. J. S. Park. (2020). Development of LoRaWAN IoT Automatic Meter Reading Systems. Journal of the KIECS, 15(5), 913-922. DOI : 10.13067/JKIECS.2020.15.5.913
  11. J. O. Park, S. H. Park, K. S. Kim, W. J. Park & J. H. Kim. (2020). Bridge Monitoring System based on LoRa Sensor Network. Computational Structural Engineering Institute of Korea, 33(2), 113-119. DOI : 10.7734/COSEIK.2020.33.2.113