With the increasing focus on damage prevention, public safety concerns, and environmental damage due to underground utility strikes, it has become more critical to accuracy locate, store and be able to visualize subsurface utilities. Several key technical details are discussed when implementing a subsurface mapping system from data collection to the use of machine learning for 3D modelling and visualization. The ability to make safe and effective decisions for infrastructure projects depends on having accurate data and the ability to visualize and trust that data.

OBJECTIVES:

• Identify required accuracy requirements and regulatory issues – ASCE 38/22 and 75/22
• Use of advanced techniques in SUE - machine learning, visualization and decision making.
• Assess the results and compare with previous methods of collection
• Thoughts/speculation on likely future changes and what they would mean?