Drone Object Relocation for Weather Damage Prevention
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current technologies lack an efficient method to automatically protect objects from adverse weather conditions by relocating them to safe locations using drones, as they do not effectively monitor and respond to changing weather conditions in real-time.
Innovation Solution
A system that utilizes computer processors to register objects, monitor weather conditions, determine risk thresholds, and instruct drones to move objects from exposed locations to protected areas based on weather data, and revert them when conditions improve, employing drones equipped with cameras and grasping mechanisms for identification and transportation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If drones are used to transport objects to protected locations, then object protection from weather damage is improved, but system complexity and operational cost increase
Solution Approach 1:
The system enables objects to protect themselves by registering their location and vulnerability characteristics. The automated weather monitoring and risk assessment system allows the object's digital twin to trigger protective actions without human intervention, making the protection system self-service oriented.
Solution Approach 2:
The drone system is designed to handle multiple object types and various weather conditions through a unified platform. The digital twin technology creates universal virtual representations that can model different physical objects, allowing the same drone infrastructure to protect diverse assets against different environmental threats.
2Measurement precision
If real-time weather monitoring is implemented, then response accuracy is improved, but data processing requirements and computational load increase
Solution Approach 1:
The system extracts only the critical weather parameters and risk indicators needed for protection decisions, rather than processing all available weather data. The digital twin filters and prioritizes weather information based on object-specific vulnerability profiles, reducing computational overhead while maintaining detection precision.
Solution Approach 2:
The system implements continuous feedback loops where weather monitoring data is compared against object risk profiles, and protection actions are adjusted based on changing conditions. This feedback mechanism allows the system to maintain high detection accuracy while optimizing energy consumption by only processing data that triggers risk threshold changes.
3Loss of time
If automated drone deployment is used, then response time to weather events is improved, but operational costs and energy consumption increase
Solution Approach 1:
The system performs preliminary risk assessments and pre-positions drones in strategic locations based on weather forecasts and object vulnerability data. Digital twins predict potential weather threats and trigger early drone deployment to protected locations before adverse conditions occur, reducing response time while optimizing energy usage through proactive rather than reactive operations.
Data Source
AI summary
A tool for protecting outdoor objects from weather related damage. Responsive to a registration request, the tool registers an object and an originating location where the object is currently located. The tool determines whether a risk threshold for the object is exceeded based, at least in part, on weather conditions at the originating location. Responsive to a determination that the risk threshold for the object is exceeded, the tool instructs one or more drones to relocate the object from an originating location to a protected location that is protected from the weather conditions.