ComEd launched the Advanced Image Analytics program in 2022 to build a more effective and proactive maintenance program. This human + machine approach leverages the latest visual data technologies and AI-powered analytics to create a more resilient and reliable grid by identifying asset defects more accurately and quickly. By utilizing drones for image capture combined with AI processing for automated defect detection, the program is projected to improve maintenance efficiencies and provide ComEd with deeper, near real-time insights into the state of health of all distribution assets.

This presentation covers the program elements and lessons learned, which includes asset inspection through drone data capture, automated image upload and assignment to the correct asset, AI processing of inspection imagery to automate defect detection, and additional use cases for the captured asset data to improve operational performance and customer service.

Session highlights:

• Steps involved in starting a drone-based asset inspection program with computer vision AI analysis of asset inspection imagery.
• Steps and competencies required for developing, deploying and retraining AI classifier algorithms.
• Additional use cases and applications for your new drone-captured asset inspection image database.
• Integrations and database consolidations to improve data access and asset visibility.