FuelWatch AI

AI Fuel Leakage Detection System (AIFLDS)

AI Fuel Leakage Detection System (AIFLDS) is an intelligent computer vision platform developed to continuously monitor fuel stations using AI-enabled cameras and deep learning technologies. The system analyzes live video streams in real time to detect fuel leakage, abnormal events, and potential safety hazards before they escalate.

Strategically positioned cameras monitor fuel storage tanks, pipelines, and critical operational areas. Advanced AI models process the video feeds to identify visual indicators of leakage, automatically generating alerts for operators through a centralized monitoring platform. This enables rapid response, enhances operational safety, and minimizes environmental impact.

Key Features

• Real-time fuel leakage detection using AI and computer vision.
• Continuous monitoring of storage tanks and fuel pipelines.
• Detection of abnormal activities and safety hazards.
• Instant alert generation for detected incidents.
• Centralized dashboard for remote monitoring.
• High-accuracy deep learning models optimized for industrial environments.
• Scalable deployment across multiple fuel stations.
• Automated visual inspection to reduce manual monitoring.

My Role

I independently led the project from concept to production deployment. My responsibilities included system architecture, AI model development, dataset preparation, software engineering, camera integration, real-time analytics implementation, testing, validation, and deployment. I designed and optimized the deep learning models to achieve reliable fuel leakage detection while ensuring high performance in continuous monitoring environments.

Technologies

Python, OpenCV, PyTorch, Deep Learning, Computer Vision, Artificial Intelligence, Video Analytics, Real-Time Monitoring, Image Processing, Industrial Surveillance.