An unfortunate fact of the
The reality is, when you move data between phases of, say, the usable lifecycle of a bridge, you end up shuttling that data back and forth between software systems that recognize only their own data sets. The minute you translate that data, you reduce its richness and value. When a project stakeholder needs data from an earlier phase of the process, planners, designers, and engineers often have to manually re-create that information, resulting in unnecessary rework.
The good news is that a disruption is brewing in the
The BIM/GIS Alliance Begins
Put the two together, and you have a layer of geospatial context blended into the
And then there’s scale:
When you bring together these two relative scales and move information seamlessly between them, you eliminate data redundancy. Adding better geospatial context to the
With all information stored in the cloud, stakeholders in both infrastructure and building projects will be able to manage data in any environment in any part of the world, yet reuse and repurpose that information in other contexts without having to continuously convert data.
BIM + Location Data = Better Design and Long-Term Savings
Whether general contractors bring the construction process into a factory for prefabrication or turn the building site into an open-air factory, there’s a new focus on improving logistics scheduling and minimizing job time and waste. Bringing a spatial dimension into this new industrialized-construction process will increase the efficiency of every project being built.
In the meantime, synthesis of the technologies is already underway. Case in point: Global engineering and design and firm
The Science of “Where” in Risk Assessment
Maximizing the long-term value of new roads, bridges, and facilities means delivering better designs to solve many of the sustainability and resiliency issues facing cities today. This will require optimizing dynamic data interchange between
Placing a digital design in a real place, within real geography, eliminates much of the front-end risk of designing and building. The biggest delays in large infrastructure projects come from the planning and permitting phases, which involve a lot of assessments of social, economic, and environmental impacts. Engineers and planners do much of that assessment outside of the design process using geospatial data; that’s how they look at floodplain maps or locate underground utilities. So, why not design using
For example, operating a road in the real world means managing utilities, managing guardrail installation, maintaining striping, and overseeing maintenance crews. There’s a lot of retrofitting and renovation. When
Closing the Data Loop
The machine map, which can be interpreted by computers, is best described as a 3D highway-design file enriched with real-world geospatial information. As the autonomous vehicles of tomorrow collect updated road geometry information such as lane closures or changes due to construction, they will identify high-risk areas, which can be fed back to planners designing and maintaining future roads. The whole process will become more seamless, and the
Connecting real-time sensor systems, geographic data, and modeling data improves everyone’s insight, leading to better infrastructure-design decisions at any scale.