A Fortune 500 global infrastructure firm was facing a critical bottleneck in managing and interpreting sewer pipeline footage. The manual analysis of CCTV sewer data was time-consuming, error-prone, and inefficient, leading to delays in defect detection and costly maintenance cycles. To overcome this, they partnered with iLink to develop an advanced AI-powered video analysis system.

Client Overview

A leading global infrastructure consulting firm empowers cities and enterprises with smarter, more sustainable solutions. Operating across 150+ countries, the firm transforms complex engineering challenges into future-ready innovations through cutting-edge technology and deep domain expertise.

Challenges

● Relied on manual CCTV video analysis to detect sewer pipeline defects, requiring extensive human review. ● Time-consuming process that delayed maintenance decisions and reduced operational efficiency. ● Prone to human error, leading to inconsistent defect detection and classification. ● Variability across projects affected the reliability of infrastructure assessments. Solution ● Deployed AI-based image analysis to automate sewer defect detection and classification. ● Integrated human-in-the-loop feedback for continuous model accuracy improvement. ● Enabled defect tracking and annotation to support predictive maintenance. ● Auto-generated rehab cost estimates based on defect severity insights.

Business Outcome

• Improved Accuracy: Achieved greater precision in identifying defects and minimized the risk of defect omission.

• Faster Processing: Significantly reduced the time to process and analyze sewer pipeline videos.

• Proactive Maintenance: Enabled timely detection of critical issues, reducing safety risks and future maintenance costs.

• Cost Optimization: Auto-generated rehabilitation cost assessments improved budget planning and decision-making.