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Characterization for an Industrial Wireless Network in a Gas Sensing Scenario



Mohamed Hany, Rick Candell


Employing wireless communications in gas sensing and air quality monitoring is extremely essential in many industrial scenarios where wired networks cannot perform the task safely and effectively. In industrial environments, deploying wireless gas sensing networks becomes a major safety requirement. Hence, we consider the use of wireless networking in safety gas sensing applications. At the National Institute of Standards and Technology (NIST), we have developed a wireless network characterization method to measure latency and reliability of the deployed network without accessing network-level metrics. In this work, we use our characterization method to study the performance of a gas sensing wireless network operating over industrial wireless channels. We have built the gas sensing scenario using the NIST industrial wireless testbed which includes ISA100.11a wireless devices, a channel emulator, and a high performance programmable logic controller (PLC) where the physical process is simulated. We use the channel emulator to replicate the path loss and multipath of the industrial environment while the signal injected to the emulator comes from ISA100.11a wireless devices. Moreover, we inject 4-20mA gas sensing signals into the wireless devices. In this work, we test various network parameters over the described setup.
Proceedings Title
Proceedings of the 2017 ISA International Instrumentation Symposium
Conference Dates
November 6-9, 2017
Conference Location
Houston, TX, US
Conference Title
2017 ISA International Instrumentation Symposium


Wireless gas sensing, Industrial wireless, ISA100.11a, Confined spaces, Cyber-physical systems, Safety, Channel models


Hany, M. and Candell, R. (2017), Characterization for an Industrial Wireless Network in a Gas Sensing Scenario, Proceedings of the 2017 ISA International Instrumentation Symposium, Houston, TX, US, [online], (Accessed May 23, 2024)


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Created November 8, 2017, Updated April 11, 2022