IoT Based Sensor Network for Air Quality Monitoring in the Oil and Gas Industry

Abstract Emissions from the petroleum industry occur in every chain of the oil producing process from extraction to the consumption phase. During the extraction phase, various pollutants like methane, carbon dioxide, carbon monoxide and methanol are released. These pollutants cause air pollution which can be harmful to humans, animals and plants. This paper develops an IoT based sensor network for air quality monitoring in the oil and gas industry which monitors the quality of air around the oil and gas facilities with a view to ensuring that the quality of air is within tolerable limit at all times. This was achieved by deploying the MQ2 and MQ8 sensors together with ESP32 processor. The MQ2 and MQ8 sensors monitor gases like LPG, carbon monoxide, smoke and hydrogen and send the data to the ESP32 processor. The processor massages the raw data and sends the result to the cloud via the Message Queuing Telemetry Transport (MQTT) protocol to the losant dashboard for data analytics and visualization. A C++ program which was written in the Arduino text editor enables communication between the processor and the losant platform. When the sensors get an abnormal reading, they send messages to the control center and automatically shuts down the drilling pump until the situation is brought under control. The result of this research effort is an air quality monitoring system which deploys sensors to monitor the quality of air around the oil and gas facilities and ensures that the gases emitted around the oil and gas facility are controlled at all times.

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Publication Details

Journal
SPE Nigeria Annual International Conference and Exhibition
Published
2024-08-05
DOI
https://doi.org/10.2118/221735-ms
Citations
1
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
0.70
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IoT Based Sensor Network for Air Quality Monitoring in the Oil and Gas Industry

Sunday Ajiroghene, O. M. Orji, R. I. Oshasha, M. O. Oyewo et al.
1 citations
SPE Nigeria Annual International Conference and Exhibition
Air Quality Monitoring and Forecasting
0.70
article

IoT Based Sensor Network for Air Quality Monitoring in the Oil and Gas Industry

Sunday Ajiroghene, O. M. Orji, R. I. Oshasha, M. O. Oyewo, I. V. Ngonadi
article en
1 citations

Abstract

Abstract Emissions from the petroleum industry occur in every chain of the oil producing process from extraction to the consumption phase. During the extraction phase, various pollutants like methane, carbon dioxide, carbon monoxide and methanol are released. These pollutants cause air pollution which can be harmful to humans, animals and plants. This paper develops an IoT based sensor network for air quality monitoring in the oil and gas industry which monitors the quality of air around the oil and gas facilities with a view to ensuring that the quality of air is within tolerable limit at all times. This was achieved by deploying the MQ2 and MQ8 sensors together with ESP32 processor. The MQ2 and MQ8 sensors monitor gases like LPG, carbon monoxide, smoke and hydrogen and send the data to the ESP32 processor. The processor massages the raw data and sends the result to the cloud via the Message Queuing Telemetry Transport (MQTT) protocol to the losant dashboard for data analytics and visualization. A C++ program which was written in the Arduino text editor enables communication between the processor and the losant platform. When the sensors get an abnormal reading, they send messages to the control center and automatically shuts down the drilling pump until the situation is brought under control. The result of this research effort is an air quality monitoring system which deploys sensors to monitor the quality of air around the oil and gas facilities and ensures that the gases emitted around the oil and gas facility are controlled at all times.

SPE Nigeria Annual International Conference and Exhibition
Petroleum Training Institute, Federal University of Petroleum Resource Effurun (NG)
Industry, innovation and infrastructure
Openalex Percentile: Top 40%
Air Quality Monitoring and Forecasting
0.70
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