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author:

Pan, Miaoxin (Pan, Miaoxin.) [1] | Chen, Chongcheng (Chen, Chongcheng.) [2] | Yin, Xiaojun (Yin, Xiaojun.) [3] | Huang, Zhengrui (Huang, Zhengrui.) [4]

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EI

Abstract:

Rapid acquisition of environmental parameters of emergency sites is crucial for emergency response. However, in areas where public ground networks do not provide sufficient coverage or are destroyed by disasters, the rapid backhaul of monitoring data from emergency sites is difficult. Due to the urgent demand for data collection in such areas, we propose an unmanned aerial vehicle (UAV)-aided emergency environmental monitoring system using a LoRa mesh networking approach, which can quickly build a large range of wireless communication networks suitable for small data transmission. First, we designed a LoRa-based mesh network protocol by using a custom slotted ALOHA medium access mechanism. Second, we designed and implemented a custom software and hardware platform of the monitoring system. The system adopts a communication mode, including multiple sensor nodes (SNs), multiple relay nodes (RNs), a gateway (GW), and a network server. Finally, we demonstrated the performance of the protocol and the system by in-lab and outdoor tests. The results show that when data rate is 0.293 kb/s, the line-of-sight 1-hop transmission distance is more than 10 km, and the 1-hop transmission delay is less than 6 s; the end-to-end delay has an upper bound, which can meet the real-time requirement of emergency response; the least upper bound of throughput per slot of our mesh protocol is much higher than that of LoRaWAN. Evaluation results also demonstrate the network robustness to environmental changes. © 2014 IEEE.

Keyword:

Antennas Emergency services Gateways (computer networks) Internet of things Mesh generation MESH networking Monitoring Network protocols Sensor nodes Unmanned aerial vehicles (UAV) Vehicle transmissions Wireless mesh networks (WMN)

Community:

  • [ 1 ] [Pan, Miaoxin]Key Lab. of Spatial Data Mining and Info. Sharing of Min. of Educ. and the Academy of Digital China, Fuzhou University, Fuzhou; 350108, China
  • [ 2 ] [Pan, Miaoxin]College of Computer and Cyber Security, Fujian Normal University, Fuzhou; 350117, China
  • [ 3 ] [Chen, Chongcheng]Key Lab. of Spatial Data Mining and Info. Sharing of Min. of Educ. and the Academy of Digital China, Fuzhou University, Fuzhou; 350108, China
  • [ 4 ] [Chen, Chongcheng]College of Computer and Cyber Security, Fujian Normal University, Fuzhou; 350117, China
  • [ 5 ] [Yin, Xiaojun]Computer Science Department, Minjiang Teachers College, Fuzhou; 350108, China
  • [ 6 ] [Huang, Zhengrui]Key Lab. of Spatial Data Mining and Info. Sharing of Min. of Educ. and the Academy of Digital China, Fuzhou University, Fuzhou; 350108, China
  • [ 7 ] [Huang, Zhengrui]College of Computer and Cyber Security, Fujian Normal University, Fuzhou; 350117, China

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Source :

IEEE Internet of Things Journal

Year: 2022

Issue: 4

Volume: 9

Page: 2918-2932

1 0 . 6

JCR@2022

8 . 2 0 0

JCR@2023

ESI HC Threshold:61

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 39

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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