AI-powered anomalies detection in pipelines

A global oil and gas company manages thousands of kilometers of pipelines across remote and challenging terrains. It recognized that its longstanding surveillance methods were no longer adequate and cost-effective.

The client needed a solution to monitor pipelines faster, more accurately, and cost-effectively, ensuring safety, security, and environmental protection.

• Costly and time-consuming monitoring
• Prone to missing critical issues
• Inefficient detection of both security threats and structural anomalies (corrosion, insulation defects, leaks)

Innowise implemented an AI-powered, ML-based pipeline monitoring system using high-resolution drone imagery.

Key capabilities used:

• Comprehensive image acquisition across diverse environments, weather, altitudes, viewing angles, and seasons
• Advanced normalization and filtering with geometric and lighting adjustments, color correction, and noise reduction
• Detailed annotation and preprocessing for accurate tagging of people, vehicles, and construction equipment
• High-accuracy CNN-based detection models for reliable entity recognition under varying conditions
• Integrated anomaly-detection algorithms to identify corrosion, insulation defects, structural damage, and potential leaks
• Scalable cloud-based infrastructure for secure, continuous monitoring

• Effective remote monitoring of pipelines in hard-to-access areas
• Reduced false positives by up to 30%
• Earlier detection of corrosion, insulation defects, and leaks
• Strengthened security and reduced vandalism/theft risk

The solution increased visibility, improved decisions, and reduced manual surveillance costs, delivering a safer and more efficient monitoring system.