SUMMARY
With the increasing focus on damage prevention, public safety concerns, and environmental damage due to underground utility strikes, it has become more critical to accurately locate, store, and be able to visualize subsurface utilities. We show several key technical and business details when implementing a subsurface mapping system from data collection to the use of machine learning for 3D modelling and visualization and give real-world examples and use cases of the different levels of accuracy needed and how they were implemented in field operations. The ability to make effective business decisions for infrastructure projects depends on having accurate data and the ability to visualize and trust that data. We will explore safety issues, lessons learned, and cost savings realized with reference to new standards from ASCE 38-22 & 75-22.

OBJECTIVES: 

• Identify required accuracy requirements and regulatory issues – ASCE 38/22 and 75/22
• Assess the benefits and needs when using low-cost hardware
• Determine the benefits (safety, efficiency, cost) of a cloud-based utility record system
• Using persistent utility data for visualization and decision making.
• Assess the results and compare with previous methods of collection, storage, and visualization.