TY - JOUR
T1 - A Novel Distributed Linear-Spatial-Array Sensing System Based on Multichannel LPWAN for Large-Scale Blast Wave Monitoring
AU - Gao, Shang
AU - Tian, Gui Yun
AU - Dai, Xuewu
AU - Fan, Mengbao
AU - Shi, Xingjuan
AU - Zhu, Jinjie
AU - Li, Kongjing
N1 - Funding Information:
This work was supported in part by the Nanjing University of Science and Technology through Research Start-Up Funds under Grant AE89991/032, in part by the Fundamental Research Funds for the Central Universities under Grant 309181A8804, in part by the Short-Term Visiting Exchange Funds in the Nanjing University of Science and Technology, and in part by the Natural Science Foundation of Jiangsu Province, China, under Grant BK20190464.
PY - 2019/12/11
Y1 - 2019/12/11
N2 - Traditional wired monitoring systems exhibit huge limitations in blast wave monitoring. To meet the requirements of long range, low cost, weight reduction, increased ease of installation maintenance, and big-data transmission in blast wave monitoring, a new distributed linear-spatial-array (D-LSA) sensing system based on low-power wide-area network (LPWAN) is proposed in this paper. This approach adopts a multichannel LoRa and NB-IoT air-blast gateway (M-CLNAG) and multiple FPGA-based wireless pressure LoRa nodes (FWPLNs) to construct a large-scale LPWAN for blast wave monitoring. The empirical models of dynamic parameter calculation (peak overpressure, duration of the positive phase and impulse) on the basis of D-LSA sensing system are redesigned for blast wave monitoring as well. Furthermore, we have evaluated the errors between the measured data from D-LSA sensing system and data from the redesigned empirical models. Finally, the wireless quality performance in terms of received signal strength indication (RSSI) and packet receive rate (PDR) for blast wave monitoring is also verified. This paper is conducted to provide new insights into how a sensing system integrating with LPWAN is designed in blast wave monitoring for acquiring dynamic parameters accurately and carrying out remote network communication efficiently, and further opening a door for wireless sensor network (WSN) in more blast wave monitoring scenarios.
AB - Traditional wired monitoring systems exhibit huge limitations in blast wave monitoring. To meet the requirements of long range, low cost, weight reduction, increased ease of installation maintenance, and big-data transmission in blast wave monitoring, a new distributed linear-spatial-array (D-LSA) sensing system based on low-power wide-area network (LPWAN) is proposed in this paper. This approach adopts a multichannel LoRa and NB-IoT air-blast gateway (M-CLNAG) and multiple FPGA-based wireless pressure LoRa nodes (FWPLNs) to construct a large-scale LPWAN for blast wave monitoring. The empirical models of dynamic parameter calculation (peak overpressure, duration of the positive phase and impulse) on the basis of D-LSA sensing system are redesigned for blast wave monitoring as well. Furthermore, we have evaluated the errors between the measured data from D-LSA sensing system and data from the redesigned empirical models. Finally, the wireless quality performance in terms of received signal strength indication (RSSI) and packet receive rate (PDR) for blast wave monitoring is also verified. This paper is conducted to provide new insights into how a sensing system integrating with LPWAN is designed in blast wave monitoring for acquiring dynamic parameters accurately and carrying out remote network communication efficiently, and further opening a door for wireless sensor network (WSN) in more blast wave monitoring scenarios.
KW - LoRa
KW - low-power wide-area network (LPWAN)
KW - NB-IoT
KW - overpressure
KW - sensing system
KW - wireless sensor network (WSN)
UR - http://www.scopus.com/inward/record.url?scp=85076787588&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2019.2930472
DO - 10.1109/JIOT.2019.2930472
M3 - Article
AN - SCOPUS:85076787588
SN - 2327-4662
VL - 6
SP - 9679
EP - 9688
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 6
M1 - 8844741
ER -