Automated Meter Readings Process for a Leading Utility Brand

Automated Meter Readings Process for a Leading Utility Brand

The client is a leading utility provider that offers essential services such as electricity, water, and gas to millions of residential and commercial customers. To record consumption data accurately, they rely on digital meters.

The company constantly works to improve accuracy and fraud prevention in utility billing to ensure customers are billed correctly based on actual consumption.

Technologies

  • YOLO (You Only Look Once)
  • OpenCV
  • MySQL
  • Python
  • Flask/Django

Challenges

Inconsistent Manual Entries: Human errors in manual meter readings often lead to billing Inaccuracy Issues or incorrect consumption reporting.

Fraudulent Activities: There is a constant risk of meter tampering or bypassing, where fraudsters manipulate meter readings to underreport or overreport consumption.

Manual Cross-Verification: The process of manually verifying meter readings against images is time-consuming and error-prone, causing increased operational costs.

Quality of Meter Images: Capturing high-quality images of meters in varying lighting conditions and physical environments, including potential obstructions, can be challenging.

Approach

  • We deployed an image-based extraction solution that utilizes an object detection algorithm (YOLO-Based Image Recognition) to extract the meter readings from images. High-resolution cameras take images of digital meters. YOLO detects the meter’s display and identifies the values shown on it.
  • The extracted readings are compared with the manual entries in the MySQL database to spot discrepancies. The system generates real-time alerts when mismatches are identified. This helps the client to respond promptly to any differences or fraudulent activities.

Result

95% Accuracy in Meter Reading

25% Reduction in Fraudulent Readings

72% Improvement in Operational Efficiency

38% Cost Saving

84% Enhancement in Customer Trust

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