Asset Management

The future of asset management lies at the intersection of artificial intelligence (AI), advanced data acquisition techniques, and digital twins. By leveraging AI algorithms trained on LiDAR-derived point clouds and high-resolution photogrammetry data, we can now create precise digital twins of powerline infrastructure. Additionally, AI-powered image analysis facilitates automated defect detection, allowing for early intervention and preventative maintenance, further enhancing the safety and reliability of infrastructure.

Powerline Digital Twin

GeoAI presents an advanced and user-friendly solution tailored for the comprehensive inspection of power lines through the analysis of LiDAR point clouds. This cutting-edge GeoAI technology boasts a range of powerful tools for classification of critical elements such as power lines, transmission towers, vegetation, buildings, and various other objects of interest within the surveyed area.

One notable feature of GeoAI is its capability to automate the detection of user-defined danger points, addressing concerns such as vegetation encroachment and potential tree fall hazards. This ensures a proactive approach to risk management and enhances the overall safety and reliability of power line infrastructure.

Moreover, GeoAI goes beyond mere analysis by incorporating built-in reporting functions that empower users to swiftly generate detailed project reports. These reports provide a comprehensive overview of the inspection results, facilitating informed decision-making and streamlined communication within project teams. The versatility of GeoAI extends to result exports, allowing users to seamlessly transfer findings in KML formatted files, ensuring compatibility and ease of integration with other geospatial systems. In essence, GeoAI not only simplifies and enhances the power line inspection process but also contributes to a more informed and proactive approach to infrastructure management.

Powerline Digital Twin for Asset Management
Powerline Digital Twin for Asset Management
Powerline Digital Twin for Asset Management

Infrastructure Health Monitoring

In a world where aging infrastructure poses potential failures could have catastrophic consequences, GeoAI steps in as a solution. Traditional methods of inspection for structural defects are not only costly and time-consuming but also pose significant risks. GeoAI revolutionizes this process by harnessing the power of close-range photogrammetry and machine vision.

This innovative approach enables us to automatically detect structural defects in infrastructure. By utilizing machine vision technology, we ensure accurate assessments while minimizing costs and time. The data is now ready to be processed into an asset management plan. It is ultimately contributing to safer and more sustainable asset management for infrastructure.

Spalling Detection of concrete for asset management
Spalling Detection

Asset Management Portfolio

GeoAI have developed innovative solutions such as concrete spalling detection using advanced artificial intelligence techniques. Leveraging the power of GeoAI, we have created algorithms capable of accurately identifying and assessing concrete spalling, a common deterioration issue in infrastructure assets like bridges and buildings.

As part of our commitment to transparency and accessibility, we have showcased our concrete spalling detection capabilities through a demonstration video providing stakeholders with a visual overview of our technology in action. Additionally, our approach integrates seamlessly with digital twin platforms, offering remote monitoring and visualization of asset conditions. It is therefore can enhance asset management strategies and optimizing lifecycle performance.

Cooling Tower Viewing

Featured project:

Spatial Digital Twin New South Wales

What is Spatial Digital Twin? Spatial digital twin is a virtual representation of a physical environment such as city, region, or infrastructure system that integrates various spatial data with other […]