One area experiencing explosive growth in the last year is AI, also referred to as Machine Learning (ML). AI/ML providers have increasingly demonstrated positive business results for utility owners, services companies, and consulting engineers in underground construction damage prevention use cases.
811 Ticketing Analytics & Risk Assessment
Several damage prevention stakeholders in the U.S. are turning to emerging data science practices powered by AI to quickly analyze hundreds of variables surrounding 811 tickets. This includes work types, historical contractor and permitting data, GIS map layers, and even weather patterns, for early detection of which excavation sites are most damage prone, and which factors in the built and natural environment might affect the precision of utility locates.
The ongoing use of AI and cloud computing to monitor and process so many various datasets can lead to insights that drive for better predictability. It can also provide useful decision tools for the individuals needing to enforce safe digging practices, and also determine where bad actors may be attempting to subvert local regulations.
Cross Bore Safety Assurance Audits & Inspection Support
In the case of cross bore safety, a “cross bore” is defined as the intersection of one utility pipeline through another, such as a gas pipeline installed through a sewer. One U.S.-based company has been leveraging AI Computer Vision technology (similarly used in facial recognition, traffic cameras, and medical scans) to automatically detect various pipeline defects, construction features, and conditions in sewer CCTV inspection data. The intention is to achieve a higher degree of accuracy than currently available with manual inspection and data review methods. As capabilities have progressed beyond proof-of-concept pilots, the prospect of Automatic Defect Recognition (ADR) technology has also been warmly embraced by industry organizations in the U.S., such as NASSCO (National Association of Sewer Service Companies) who have long been committed to elevating the level of quality and consistency in sewer condition assessments. It is also being implemented by diverse groups of industry stakeholders, ranging from sewer agencies and contractors large and small, to consulting engineers.
A recently-completed study in a use case involving review of CCTV cross bore sewer inspection data found an AI-assisted process yielded a 70% savings of manual workforce hours in QA/QC reviews. Other studies have also shown a nearly 2x increase in CCTV inspection productivity. The underground construction industry is now keen to examine possibilities in even more beneficial use cases for AI.
Whether it’s a discussion of where ADR in CCTV inspections can also provide opportunities for gas utilities to expand co-operative partnerships with sewer asset owners by cost-effectively providing sewer agencies with data to drive smarter sewer operations and capital budget management, or additional insights and decisions that support products relating to utility locating, excavation permitting, and overall conflict avoidance, we are seeing AI illuminate a path forward as we navigate through an otherwise hidden world.
Eric Sullivan is Director of Business Development with SewerAI. He can be reached at firstname.lastname@example.org.