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A Novel Distributed Linear-Spatial-Array Sensing System Based on Multichannel LPWAN for Large-Scale Blast Wave Monitoring

Lookup NU author(s): Shang Gao, Professor Gui Yun TianORCiD, Kong Jing Li

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Abstract

© 2014 IEEE.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.


Publication metadata

Author(s): Gao S, Tian GY, Dai X, Fan M, Shi X, Zhu J, Li K

Publication type: Article

Publication status: Published

Journal: IEEE Internet of Things Journal

Year: 2019

Volume: 6

Issue: 6

Pages: 9679-9688

Print publication date: 01/12/2019

Online publication date: 19/09/2019

Acceptance date: 09/07/2019

ISSN (electronic): 2327-4662

Publisher: IEEE

URL: https://doi.org/10.1109/JIOT.2019.2930472

DOI: 10.1109/JIOT.2019.2930472


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