Mobile Compute Device Route Guidance for Gas Leak Investigation
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Solution Overview
Problem
Advanced Leak Detection Systems (ALDS) face challenges in efficiently pinpointing natural gas leaks due to low sensitivity handheld detectors and lack of guidance, resulting in time-consuming and costly on-foot investigations, with find rates varying significantly based on investigator skill and training.
Innovation Solution
A mobile compute device is configured to obtain and present route data to users, utilizing algorithms like surge-cast, surge-spiral, and raster scan to guide investigators efficiently to gas leak locations, adjusting routes based on environmental conditions and objects, and adapting algorithms in response to wind direction and stochastic changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If investigators use handheld detectors without guidance, then they have flexibility in search methods, but the time to identify gas leak locations increases significantly and find rates vary widely
Solution Approach 1:
A mobile computing device serves as an intermediary between the ALDS and the investigator, providing real-time route guidance and direction. The device receives data from the ALDS, processes it to determine optimal search routes, and presents guided directions to the investigator, eliminating the time loss associated with unguided manual searching while preserving investigator flexibility through electronic guidance.
Solution Approach 2:
The system performs preliminary actions by pre-calculating optimal investigation routes based on ALDS data before the investigator begins their search. The mobile computing device determines the most efficient path to the gas leak location in advance, allowing the investigator to follow predetermined directions rather than searching randomly, thereby significantly reducing investigation time.
2Reliability
If investigators rely on skill and training to find gas leaks, then find rates can reach up to 90%, but training effectiveness declines over time and requires continuous investment
Solution Approach 1:
The system replaces the mechanical system of human skill and training with an automated electronic guidance system. Instead of relying on investigator expertise that degrades over time, the mobile computing device provides algorithmic route determination that maintains consistent high find rates without requiring ongoing training investment or skill maintenance.
Solution Approach 2:
The system enables self-service by allowing the ALDS and mobile computing device to automatically determine optimal search routes without human intervention. The system self-corrects and adapts based on real-time data, maintaining reliable find rates independent of investigator training levels or experience.
3Device complexity
If ALDS provide only search area information, then the system remains simple, but the investigator lacks direction on where and how to investigate
Solution Approach 1:
The system segments the investigation process into distinct functional components: the ALDS provides search area identification, the mobile computing device handles route calculation and guidance generation, and the investigator executes the guided search. This segmentation allows each component to remain relatively simple while the integrated system provides comprehensive guidance, resolving the contradiction between system simplicity and investigator direction.
Data Source
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AI summary
Technologies for producing efficient investigation routes for identifying gas leak locations include a mobile compute device. The mobile compute device includes circuitry configured to obtain route data indicative of a route to be traveled along to identify a location of a gas leak. The circuitry is also configured to present the route data to a user to guide the user along the route.