Location And Marking System For AI-Assisted Underground Utility Management
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Solution Overview
Problem
Utility workers face inefficiencies and safety challenges in managing and accessing asset information during emergencies due to manual processes and fragmented data sources, particularly in handling underground infrastructure disruptions.
Innovation Solution
A computer-implemented location and marking system that provides seamless access to resource and asset databases, generating maps, and automating ticket management, including AI models to predict dig-in risks and optimize technician assignments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual procedures are used to manage and access asset information, then workers can access information through existing processes, but the efficiency and speed of data management and access are reduced
Solution Approach 1:
The patent replaces manual mechanical procedures with an automated computer vision system using AI models and image processing to detect, classify, and manage utility markers and assets, eliminating manual data entry and inspection processes
Solution Approach 2:
The system enables self-service automation where the AI model automatically detects, identifies, and manages utility markers without human intervention, performing data collection, classification, and database updates autonomously
2Reliability
If comprehensive asset information is collected and managed, then better decision-making and safety are achieved, but the complexity of data management and system operations increases
Solution Approach 1:
The patent segments the complex data management task into distinct AI processing stages: image capture, marker detection, classification, data extraction, and database integration, with each stage handled by specialized computational modules
Solution Approach 2:
The system introduces an intermediary AI processing layer between physical utility markers and the database, where automated image recognition and data extraction serve as intermediaries to simplify data flow and reduce manual intervention requirements
3Productivity
If automated functionality is implemented to manage and distribute data, then efficiency and speed of data management improve, but the initial system complexity and implementation requirements increase
Solution Approach 1:
The patent creates a universal automated system that performs multiple functions including image capture, utility marker detection, asset identification, data extraction, classification, and database integration through a single integrated AI platform
Solution Approach 2:
The system changes the operational parameters from manual processes to automated computational processes, transforming how data is collected, processed, and managed by shifting from human-operated procedures to AI-driven automated workflows
Data Source
AI summary
A novel location and marking system is configured to provide a seamless in-the-field access to resource and asset information databases with automated functionality that effectively and more efficiently manages, controls, and distributes data according to some embodiments. These assets include sites of residential and business gas, electrical, and/or water and sewer conduits and metering systems, as well as related underground infrastructure that can be susceptible to earthquakes, ground disturbances, and other emergency situations. In some embodiments, the systems enables utilities to manage assets in real-time, provide map asset status, and provide automatic ticket routing, dispatching and management. In some embodiments, the system is configured to ingest 811 tickets and output the 811 ticket information on a dashboard. In some embodiments, the system includes an AI model configured to predict a ticket completion duration.