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Data Reliability and Sensors Lifetime in Bridge Health Monitoring using LoRaWAN-Zigbee

Awad Ali1,*, Reyazur Rashid Irshad1, Ahmed Abdu Alattaab1, Aamir Fatahayab2

1 Department of Computer Science, College of Science and Arts-Sharourah, Najran University, Najran, Kingdom of Saudi Arabia
2 Department of Computer Science, JJTU, Jhunjhunu, Rajasthan, India

* Corresponding Author: Awad Ali. Email: email

Computers, Materials & Continua 2022, 73(2), 2663-2678.


The Wireless Sensor Network (WSN) is regarded as the fastest expanding technological trend in recent years due its application in a variety of sectors. In the monitoring region, several sensor nodes with various sensing capabilities are installed to gather appropriate data and communicate it to the gateway. The proposed system of the heterogeneous WSN employing LoRaWAN-Zigbee based hybrid communication is explored in this research study. To communicate in a network, two Long–Range Wide Area Network (LoRaWAN) sensor clusters and two Zigbee sensor clusters are employed, together with two Zigbee and LoRaWAN converters. The suggested Golden eagle shepherd optimization (GESO) method then forms Zigbee as well as LoRaWAN networking clusters. Furthermore, depending on energy usage and data packet size, the fitness of each sensor node is assessed using the Dynamic Intelligent Reasoning Based Neural (DIRN) approach. MATLAB software is used to implement and execute this study. When the Zigbee network’s transmission distance is 650 m and the LoRaWAN network’s transmission range is 3.5 km, the system can function with a packet loss rate of less than 0.04 percent. This study shows significant gains in the performance of the system when compared to traditional approaches based on digital findings obtained on software solutions.


Cite This Article

A. Ali, R. Rashid Irshad, A. Abdu Alattaab and A. Fatahayab, "Data reliability and sensors lifetime in bridge health monitoring using lorawan-zigbee," Computers, Materials & Continua, vol. 73, no.2, pp. 2663–2678, 2022.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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