AI Warning Alerts for Underground Asset Excavation
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Solution Overview
Problem
Current methods for managing underground assets during excavation activities are inefficient and lack complete automation, leading to potential safety hazards and disruptions in utility services.
Innovation Solution
An AI-based system that analyzes underground asset maps to identify risk features and generate warning alerts for excavated locations, reducing human intervention and enhancing safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual techniques are used to manage underground assets during excavation, then human judgment and flexibility are maintained, but safety risks increase and processing efficiency decreases
Solution Approach 1:
The patent replaces manual visual inspection and human judgment with an AI-based computer vision system that automatically analyzes underground asset maps. The system uses pre-trained AI models to detect, classify, and warn about underground assets, substituting human mechanical processes with automated digital processing while improving both safety and efficiency
Solution Approach 2:
The patent introduces an AI-based intermediate system that acts as a mediator between the underground asset maps and human operators. The AI model processes maps, identifies risks, and generates warnings, serving as an intelligent intermediary that enhances human decision-making without completely replacing human oversight
2Productivity
If complete automation is implemented using AI-based systems, then processing efficiency and safety are improved, but system complexity increases
Solution Approach 1:
The patent employs pre-trained AI models that have been previously trained on large datasets of underground asset maps. This preliminary training action allows the system to perform complex analysis tasks without requiring complex real-time processing, as the intelligence has been prepared in advance through offline training
Solution Approach 2:
The patent divides the complex task of underground asset analysis into distinct functional modules: map input, AI model processing, feature extraction, warning generation, and output. This segmentation allows each component to be optimized independently and simplifies the overall system architecture by breaking down complexity into manageable parts
3Reliability
If manual analysis of underground asset maps is performed, then system complexity remains low, but human errors increase and safety risks rise
Solution Approach 1:
The patent replaces manual human analysis with automated AI-based computer vision processing. The system uses machine learning models to detect and classify underground assets, eliminating human cognitive processes and replacing them with automated digital algorithms that provide consistent, error-free analysis
Solution Approach 2:
The patent implements a feedback mechanism where the AI system generates warnings based on detected assets, and these warnings can be verified and refined through continuous operation. The system learns from outcomes and improves its accuracy over time, creating a feedback loop that enhances reliability while maintaining manageable complexity
Data Source
AI summary
Disclosed herein is an AI based system and method for generating warning alerts for a location to be excavated. The method comprises obtaining, from at least one external source, at least one underground asset map of the location to be excavated. For each of the at least one underground asset map, the method comprises locating a region of interest within the underground asset map corresponding to an identified underground utility service provider and extracting at least one feature within the region of interest. The at least one extracted feature is then compared with a plurality of features stored in a repository corresponding to the identified underground utility service provider, to determine a match. In response to the determination, the extracted feature is identified as a risk feature corresponding to the identified underground utility service provider and one or more warning alerts indicative of risk assets are generated.