Electrical Structure Monitoring Solution for Leading US-Based Energy Company
Overview
The US-based leading energy company provided electric, gas, and steam services to over 10M+ people. They wanted to develop an intelligent inspection solution for their 250K+ underground electric structures to perform asset visual inspections. ACL Digital helped the client by providing a solution that included a thermal camera for capturing installation images and the FLIR image extractor for obtaining temperature, location, and other metadata.
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Challenges
Lack of ML enabled solution based on Mask RCNN
Absence of hotspot detection and alerting capabilities for the team
Solutions
- The solution consists of a thermal camera to capture installation images, FLIR Image Extractor to obtain temperature, location and other metadata, a cloud for images storage, a cloud compute instance with a GPU, ML model to detect cables, a module to make decision to raise the warning flag or send notification
- Annotation of 25K+ images using makesense.ai tool providing polygonal annotation in PVOC annotation format
- The images will be used to train the ML model (Mask RCNN model) that is based on ResNet 101 architecture
- Mask is extracted based on the detection of electrical asset associated that helps to get the relevant temperature from the matrix
- Hotspot is then detected based on the ingenious algorithm
