Case Study
GE DIGITAL
Project overview
GE DIGITAL
- GE Digital is the software branch of GE.
- 4,000+ employees.
- $ 1 billion in annual revenue.
Deployment of visual intelligence solutions for the T&D sector.
Today, global T&D utilities spend millions of dollars every year on vegetation management and asset inspection programs. These legacy programs are costly, ineffective, and underutilize existing data. With the introduction of artificial intelligence, it is possible to discover new ways to plan and analyze grid networks and optimize systems and processes, all at scale. These changes can reduce outages while increasing compliance, improving safety, and reducing the possibility of catastrophic events such as wildfires or major regional outages.
GE Digital and Alteia have partnered to develop GE Visual Intelligence, a Visual Data Management Platform that embraces new remote sensing technology and A.I. This partnership will fundamentally alter the way GE Digital operates. With A.I, they will harness the power of existing data accumulated on their network and move towards a single source of truth across their portfolio. The future of business will be based on predictive models and a condition-based approach for operations.
GE Digital and Alteia have partnered to develop GE Visual Intelligence, a Visual Data Management Platform that embraces new remote sensing technology and A.I. This partnership will fundamentally alter the way GE Digital operates. With A.I, they will harness the power of existing data accumulated on their network and move towards a single source of truth across their portfolio. The future of business will be based on predictive models and a condition-based approach for operations.
Results
x10
improvement in inspection time
22%
cost savings on an annual basis vs. current costs
74%
return on investment for Utilities
30%
reduction in outages
Project highlights
- Deploy Alteia’s stack on existing GE cloud infrastructure with specific developments for the T&D market.
- Create a data pipeline to aggregate huge inspection files from numerous data sources seamlessly.
- Process incoming data on a single platform that specializes in 2D and 3D visual rendering.
- Apply AI and machine learning to auto-identify high-risk encroachment areas.
- Mitigate failure threats with automated Asset, Component, and Defect Visual Recognition Scale to support infrastructures that can be many thousands of miles or kilometers long.
