AI-InfraSolutions was created to overcome the barriers to high-quality data collection and processing. By partnering with Bentley, the team integrated Bentley’s Orbit 3DMsolution, which provided seamless data viewing and integration, allowing AI to classify and process outdoor assets in real-time. The project’s goal was to make advanced mobile mapping technology more accessible without significant upfront investment or specialized knowledge, allowing companies worldwide to leverage the solution quickly. 

The integration of Bentley’s Orbit 3DM technology significantly improved operational efficiency, enabling data to be processed within 24 hours. The solution’s quick turnaround and high-quality output allowed companies to make timely decisions and take advantage of new opportunities faster. The leasing model introduced also reduced capital investment requirements, making it easier for companies to adopt the technology and scale their operations. 

For AI-InfraSolutions, the integration of Bentley’s tools reduced development time, allowed faster deployment, and enhanced product competitiveness. Partners in mobile mapping benefited from lower entry barriers, enabling them to adopt an all-in-one solution without needing technical expertise. End users, including construction companies and government agencies, gained immediate access to high-quality data, leading to improved efficiency, cost savings, and better project outcomes. 

In summary, Bentley’s technology empowered AI-InfraSolutions to deliver a scalable, efficient, and profitable solution, transforming the way companies capture, process, and utilize mapping data. 

So, as data accumulates, the next step is to turn it into an accurate digital model of the physical world. This is done through the creation of Digital Twins, virtual representations of real-world objects or systems. AI-InfraSolutions aims to create Digital Twins of the entire urban environment, enabling real-time visualization and analysis of infrastructure assets. 

These Digital Twins are particularly useful for infrastructure planning and maintenance. For example, local authorities can use these models to simulate traffic scenarios, predict the need for road and bridge maintenance, or even plan urban expansion more efficiently. Additionally, Digital Twins can be enriched with additional layers of internal data, such as traffic conditions, performance of telecommunications networks, or public resource usage. 

The future of AI in the infrastructure sector promises to be even more transformative. In five to six years, AI-InfraSolutions anticipates that it will be possible to directly ask questions to datasets and get real-time answers, something that will significantly speed up the decision-making process.