This webinar, recorded on March 13, 2024, explains how ComEd is digitally transforming how they inspect and maintain their distribution networks by automating grid analytics. With demand and strain on the electrical grid expected to increase in the years ahead, ComEd determined that new methods were required to leverage new and existing data sources, employ advanced analytics and empower the workforce to more rapidly and effectively identify and repair conditions before they are service impacting.
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 utilizing drone powerline inspection 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.
The ComEd Image Analytics Platform, powered by Optelos, organizes ComEd distribution assets by Serving territory and Feeder in an intuitive GUI based on ComEd maintenance areas.
This webinar examines how ComEd implemented each of the program elements, consisting of:
1) Standardized Visual Data Collection: PTZ, drone and mobile device image capture.
2) Visual Data Management: Cloud-based image storage for secure and responsive image storage.
3) Image Analytics and Management: Use of integrated analytics tools and data hierarchy design to maximize data leverage and access.
4) AI Algorithm Development and Deployment: Process and procedures for developing AI algorithms.
5) AI Model Retraining and Enhancement: Process, best practices and lessons learned for image annotation and scope for improving AI results.
6) New Digital Data Applications and Leverage: Additional use cases for leveraging new and existing visual data and asset information once housed in a unified asset database.
ComEd developed AI classifiers to identify distribution assets and their defect conditions to automate asset inspections utilizing digital capture technologies (aerial drones, truck-mounted PTZ cameras and mobile devices).
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