As the world's reliance on oil and gas continues to grow, pipelines have become an increasingly important asset in the industry. Oil spills caused by factors such as corrosion, pipeline vandalism, and others pose a major threat to pipeline integrity, resulting in negative impacts on health, the economy, and the environment. In response to this challenge faced by the oil and gas industry, this project introduces a cost-effective, automated, and smart oil spill detection and alert system designed to address the gaps in existing detection strategies. This paper discusses the testing methodology and implementation process and reveals the system's effectiveness in real-time monitoring and early detection. The paper highlights the system's ability to significantly enhance safety, environmental protection, and economic efficiency in the oil and gas industry. Additionally, the paper recommends future research directions for the system.
O. S. Ogboro, Kehinde O. Adegboye, Chi-ife D. Ileka et al.· SPE Nigeria Annual Internati...· 0 citations
Workers in the oil and gas industry, construction, and mining are routinely exposed to life-threatening hazards that existing safety systems are too slow and too limited to address. Traditional safety approaches rely on manual reporting and passive physical protection, leaving critical gaps in real-time detection and emergency response. This paper presents the design, development, and evaluation of an Internet of Things (IoT) powered smart safety helmet, named the BEYOND HELMET, built specifically for oil and gas field workers in Nigeria.
The system integrates an ESP32 microcontroller, an MPU-6050 inertial measurement unit for fall detection, an MQ-7 gas sensor for carbon monoxide monitoring, a DHT22 temperature and humidity sensor, a SEN-11574 pulse rate sensor for heart rate monitoring, a NEO-6M GPS module for precise location tracking, a SIM800L GSM module for SMS-based emergency alerts, an ESP32-CAM camera for visual confirmation, and a 16x2 LCD display for local status output. All sensor data are processed onboard and transmitted in real time to supervisors through an IoT monitoring platform structured in JavaScript Object Notation (JSON) format.
Testing results indicate that the system achieves fall detection accuracy of approximately 95%, carbon monoxide hazard detection accuracy of approximately 90%, and abnormal heart rate detection accuracy of approximately 92%. Emergency alerts are dispatched in under 10 seconds compared to the 10 to 20 minutes typical of manual reporting systems, representing a response time reduction of 70 to 85%. The prototype was assembled at a total cost of approximately 43,400 Nigerian Naira, making it highly affordable and scalable for large industrial deployments. The results demonstrate that the BEYOND HELMET offers a comprehensive, cost-effective, and proactive safety solution for workers in hazardous environments.
O. S. Ogboro, Kehinde O. Adegboye, Chi-ife D. Ileka et al.· SPE Nigeria Annual Internati...· 0 citations
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