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C3 IoT > Case Studies > Driving Network Efficiency and Fraud Detection Efforts
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Driving Network Efficiency and Fraud Detection Efforts

 Driving Network Efficiency and Fraud Detection Efforts - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Big Data Analytics
  • Analytics & Modeling - Predictive Analytics
  • Infrastructure as a Service (IaaS)
Applicable Industries
  • Utilities
Applicable Functions
  • Business Operation
Use Cases
  • Advanced Metering Infrastructure
  • Energy Management System
The Challenge

Baltimore Gas and Electric Company (BGE) wanted to optimize the deployment and ongoing health of its advanced metering infrastructure (AMI) network and identify and reduce unbilled energy usage. BGE wanted a solution to deliver an annual economic benefit of $20 million.

The Customer
Baltimore Gas and Electric Company (BGE)
About The Customer
Baltimore Gas and Electric Company (BGE) is a subsidiary of Exelon Corporation and Maryland’s largest gas and electric utility. BGE provides service to more than 1.2 million electric customers and more than 650,000 natural gas customers in central M
The Solution

BGE launched C3 IoT applications across all two million sensors and devices in its service territory. BGE also deployed C3 AMI Operations to optimize the deployment and ongoing health of its advanced metering infrastructure (AMI) network and C3 Revenue Protection to identify and reduce unbilled energy usage. C3 IoT loaded two years of historical BGE data in a 10 terabyte federated cloud image and configured more than 140 complex analytics and predictive algorithms to match BGE's requirements and available data.

Data Collected
Energy Cost Per Unit, Energy Usage, Equipment Status, Process Parameters
Operational Impact
  • [Efficiency Improvement - Maintenance]
    Real-time status reports enable maintenance personnel to remotely diagnose the status of a device.
  • [Data Management - Data Analysis]
    Cloud solutions enable aggregation of 'big data' to enable more robust analysis and lower costs.
  • [Efficiency Improvement - Energy]
    The amount of unbilled energy consumption can be predicted and reduced through predictive analytics.
Quantitative Benefit
  • C3 Revenue Protection identified non-technical loss cases generating $2.8 million in economic benefit from verified fraud cases.

  • C3 AMI Operations identified sensor health issues with a 99% accuracy rate.

  • 120% of BGE's savings target was achieved.

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