Prakash Prabhu
Chief Business Officer & Co-Founder, VisionBot
Computer vision has traditionally been used for inspection in highly structured manufacturing environments.
But thanks to increasingly powerful machine learning techniques, and mature data labelling capabilities, Visual AI is becoming capable of monitoring more complex and dynamic processes where humans are involved, this is revolutionizing our approaches to identifying and mitigating failures in a wide range of industrial processes – expanding well beyond traditional automated manufacturing applications and promoting Human Centred AI (HCAI).
The oil and gas sector, companies can adopt AI technologies to improve Operations, Safety and Reliability across the production and supply chain. This translates to autonomous processes, improving cost efficiencies, and reducing operational risks.
Some of the process impacted by Visual AI include:
- Maintenance and service life prediction.
- Safety and compliance monitoring.
- Reliability & Business Continuity.
- Risk evaluation.
- Sustainability and Environmental protection.
- Non-destructive testing and inspection.
- Analyze fatigue and corrosion of systems.
Intelligent Fire Detection With AI
Fire hazards are one of the most severe causes of accidents that may lead to casualties, considerable production loss, and equipment damage. Traditional fire detection was done by human operators through video cameras, especially in petroleum and chemical facilities.
However, it’s almost impossible for human operators to spot fires in time with hundreds of video cameras installed in large-scale settings. Human subjectivity, distraction, and visual perception limit the accuracy of human safety supervisors. Intelligent fire detection applies computer vision methods to video cameras to detect fires.
Some methods have shown better results when focusing on smoke detections. These use background subtraction to detect motion and reduce computational complexity. The availability of accurate model datasets and improved computation power of edge cameras can now make it possible to undertake complex analysis for Fire and Smoke detection on the camera.
Predictive Maintenance and Equipment Failure Detection
In oil fields and refineries, deep learning models can be used to detect equipment failures or deterioration. Therefore, custom neural networks are trained to detect anomalies during automated equipment inspection. If an AI model detects a potential issue, an image can be automatically sent to a human supervisor for manual review. By continuously monitoring equipment performance, they can predict potential failures, allowing for proactive maintenance to minimize downtime and prevent accidents.
well where deep neural networks (DNN) are applied. Traditional methods of physical interpretation are time-consuming, and the results depend strongly on the human expert (subjectivity).
In Industry tests, the ML model’s accuracy was 92% compared to manual interpretation and about 1,000 times faster than the manual method. AI methods can accelerate the process and, even more critically, exclude subjectivity in the interpretation process.
Conclusion
Today, we are only seeing the beginning of the era of Visual AI-driven applications. Edge AI makes it possible to move AI vision capabilities from the cloud to the field, enabling large-scale and distributed applications.
Because of the strategic importance and distinct operational workflows, most oil and gas companies aim to build and operate their Visual AI solutions with a primarily aim to improve maintenance, safety, management, life-cycle sustainability, quality, and operational efficiency.
As a leading Visual AI Company, VisionBot helps to leverage the latest in computer vision technology to help businesses and organizations automate processes, improve customer experiences, and gain valuable insights in to their operations.
Connect with our experts to understand how companies are using VisionBot™ Visual AI driven Computer Vision to strengthen security, safety and streamline operations.
We welcome Technology Integrators and sector speciality VAR’s to become a VisionBot™ channel partner, and discover the opportunity to offer a cutting-edge AI-powered computer vision solution to your customers.
*Views expressed in the article are solely of the Author
