Drone Fleet Coordination for Collision-Free Damage Inspection
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Solution Overview
Problem
Current methods for collecting data on property damage, such as those used in insurance claims, are time-consuming, inefficient, and prone to inaccuracies due to manual control and potential drone collisions, especially when multiple drones are used.
Innovation Solution
A system comprising a fleet of autonomous or semi-autonomous drones communicatively coupled with a damage identification computing device that navigates a geographical region to detect damage, prevents collisions, and stores data in a blockchain for secure record-keeping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple drones are used to collect data, then the productivity of data collection is improved, but the risk of collisions between drones increases
Solution Approach 1:
A centralized control system acts as an intermediary between multiple drones, coordinating their movements and assigning specific zones to each drone. This mediator system processes drone positions and mission parameters, ensuring drones operate in designated areas without conflicting with each other, thus maintaining high productivity while eliminating collision risks.
Solution Approach 2:
The inspection area is segmented into multiple zones, with each drone assigned to a specific zone. This spatial segmentation allows drones to operate independently in their designated areas, maximizing data collection productivity while preventing collisions since each drone has its own defined operational space.
2Ease of operation
If manual control is used for drone operation, then the ease of operation is improved, but the measurement precision of damage assessment deteriorates
Solution Approach 1:
The system enables semi-autonomous operation where drones automatically navigate to assigned zones and capture images based on pre-programmed parameters. The control system automatically processes images and assesses damage, eliminating manual intervention errors while maintaining operational simplicity through centralized management. This self-service approach ensures consistent, precise damage assessment without requiring manual control.
3Device complexity
If a single drone is used for data collection, then the device complexity is reduced, but the productivity of comprehensive damage assessment deteriorates
Solution Approach 1:
A centralized control system serves as an intermediary that manages multiple drones, handling mission assignment, position tracking, and image collection coordination. This mediator abstracts the complexity of multi-drone management, making the system as easy to operate as single-drone control while achieving comprehensive damage assessment through parallel data collection from multiple drones simultaneously.
4Productivity
If multiple drones operate in the same area, then the productivity of data collection is improved, but the loss of information due to data overlap increases
Solution Approach 1:
The inspection area is divided into distinct zones assigned to individual drones, ensuring each drone collects data from its specific segment without overlapping with others. This segmentation maximizes productivity through parallel collection while eliminating data redundancy, as each drone captures unique information from its designated area.
Data Source
AI summary
A damage identification (DI) system for identifying property damage may include a drone fleet including several autonomous or semi-autonomous drones communicatively coupled together and a DI computing device. Each drone may collect drone-collected damage data, including image data. The DI computing may assign a geographical region to the drone fleet. The drone fleet may automatically navigate to, and then within, the geographical region to detect potential damage to properties. The DI computing device may further receive drone-collected damage data associated with a property within the geographical region from the drone fleet when the drone fleet determines the property is actually or potentially damaged, generate aggregated damage data associated with the property based at least partially upon the drone-collected damage data, and/or store the aggregated damage data in a blockchain structure associated with the property for damage assessment of the property.