Autonomous Drone Marking Maintenance for Underground Utility Lines
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional methods for marking underground utility lines are labor-intensive and inefficient, especially across large areas, and often require costly re-identification and re-marking due to obscured or damaged markings during construction projects.
Innovation Solution
An autonomous drone system equipped with detection equipment, such as sonar and electromagnetic sensors, navigation systems, and a payload for marking materials, which can autonomously detect and mark underground infrastructure, maintain existing markings, and communicate with a database to ensure accurate and efficient tracking and re-marking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional contractors manually detect and mark utility lines, then marking accuracy can be maintained, but labor intensity and time consumption increase significantly
Solution Approach 1:
The patent replaces manual mechanical marking operations with an autonomous aerial vehicle system equipped with sensors, processors, and marking mechanisms. The system automatically detects utility lines using electromagnetic sensors, processes the detected data to determine locations, and applies markings without human intervention, thereby replacing the mechanical labor system with an automated electromechanical system.
Solution Approach 2:
The autonomous aerial vehicle performs the complete marking process independently - detecting utility lines, processing location data, navigating to marked positions, and applying markings all without human assistance. The system serves itself by integrating detection, processing, navigation, and marking functions into a single autonomous platform that operates independently throughout the worksite.
2Area of stationary object
If utility lines are marked across large areas, then complete coverage is achieved, but the time and resources required increase significantly
Solution Approach 1:
The system transitions from static manual marking to dynamic autonomous operation. The aerial vehicle moves dynamically through the worksite, adjusting its position and altitude automatically, while the marking mechanism dynamically adapts its operation based on real-time detection data. This dynamic approach enables rapid coverage of large areas compared to static manual methods.
Solution Approach 2:
The autonomous system maintains continuous operation throughout the marking process - the aerial vehicle continuously flies, detects, processes, and marks without interruption. The system eliminates idle time between detection and marking by seamlessly integrating these functions, ensuring continuous productive action across the entire worksite area.
3Reliability
If markings are applied during construction projects, then utility locations are identified, but markings may be obscured or damaged requiring re-marking
Solution Approach 1:
The system incorporates feedback mechanisms where the aerial vehicle returns to previously marked areas to verify marking integrity. The sensors detect whether markings remain visible and intact, and if not, the system automatically re-applies markings. This feedback loop ensures marking durability by continuously monitoring and maintaining marking visibility throughout the construction process.
4Measurement precision
If multiple surveys are performed to track utility lines, then accurate tracking is maintained, but costs and time consumption increase
Solution Approach 1:
The system performs preliminary detection and marking before construction begins, establishing accurate utility line locations in advance. The autonomous vehicle maps the entire worksite and applies markings proactively, eliminating the need for multiple subsequent surveys. This preliminary action ensures tracking accuracy while reducing total survey time by completing identification in a single pass.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The autonomous drone system significantly reduces labor costs and enhances efficiency in marking and maintaining utility lines by autonomously detecting and re-marking underground infrastructure, minimizing the need for repeated surveys and ensuring accurate location and type identification of utility lines.
Implementation Method 1
The detection equipment include a depth sensor (e.g., a sonar and/or electromagnetic detector) configured to determine the depth of underground infrastructure.
Implementation Method 2
The detection equipment include a depth sensor (e.g., a sonar and/or electromagnetic detector) configured to determine the depth of underground infrastructure.
Implementation Method 3
determine whether each marking within the portion of the geographic area is sufficiently present using one or more marker sensors. The drone can determine whether each marking within the portion of the geographic area is sufficiently present by detecting an indicator in paint associated with each of the detected markings.
Data Source
AI summary
A marking maintenance system comprising a marking database, a drone, and a data network communicatively coupled to the marking database and drone. The marking database is arranged to store marking data associated with one or more markings. The marking data can include one or more marking locations within a geographic area and a type of infrastructure associated with each of the one or more marking. The drone is arranged to determine the location of the drone via one or more location sensors, receive data from the marking database, and deploy to each marking location within a portion of the geographic area. The drone is also arranged to determine whether each marking within the portion of the geographic area is sufficiently present using one or more marker sensors and repair each marking within the portion of the geographic area that is determined to not be sufficiently present.