Drone Overhead Alert System Using Intersection Prediction
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Solution Overview
Problem
There is a need for a system to notify and alert individuals when drones are flying overhead, addressing concerns about safety and security due to the potential for drones to fall or crash, especially in populated areas.
Innovation Solution
A computer-implemented method and system that tracks drone positions and routes using a user device with a processor and memory, receiving drone data from a server, predicting intersection areas with the user's path, and providing alerts to change the user's path or speed to avoid drones when the distance becomes unsafe.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If drones are allowed to fly over populated areas for commercial use, then productivity and economic benefit are improved, but safety concerns and public acceptance deteriorate due to fear of drones falling or crashing
Solution Approach 1:
The system performs preliminary detection of drone positions and routes before the drone reaches the user's location. By predicting intersection areas between drone routes and user paths in advance, the system can issue early warnings and provide avoidance instructions before the hazard materializes, thereby maintaining both commercial drone operations and public safety perception
Solution Approach 2:
The system continuously receives updated drone position data from servers and user position data from the user device, processes this feedback information to recalculate intersection areas and distances, and dynamically updates warnings and avoidance instructions. This real-time feedback loop ensures that safety monitoring adapts to changing drone trajectories and user movements, maintaining reliability during commercial operations
2Reliability
If a drone monitoring system is implemented to track and alert users about drones flying overhead, then safety and security are improved, but device complexity and system infrastructure requirements worsen
Solution Approach 1:
The system introduces a server as an intermediary that centralizes the complex tasks of receiving drone position data from multiple drones, processing route intersection calculations, and generating warnings. The user device itself remains relatively simple, primarily handling position acquisition, displaying warnings, and showing avoidance instructions. This intermediary architecture distributes system complexity away from individual user devices while maintaining comprehensive safety monitoring
Solution Approach 2:
The server performs multiple functions: receiving drone position data from various sources, tracking multiple drones simultaneously, calculating intersection areas with user paths, determining safe distances, and generating avoidance instructions. By consolidating these diverse functions in a single multi-functional platform, the system achieves comprehensive safety monitoring without requiring each user device to be complex
3Measurement precision
If real-time drone position tracking and intersection prediction are performed, then measurement precision and alert accuracy are improved, but use of energy and computational resources worsen
Solution Approach 1:
The system extracts and separates the computationally intensive tasks of drone position tracking, route intersection prediction, and warning generation from the user device and places them on the server. The user device only performs lightweight tasks such as acquiring its own position data and displaying warnings. This extraction of heavy computational functions reduces energy consumption on the user device while maintaining high measurement precision through server-side processing
Solution Approach 2:
The system performs full precision tracking and prediction only when necessary - specifically when a drone's route is predicted to intersect with the user's path or when the drone is within a certain distance threshold. For drones that are far away or on non-intersecting routes, the system uses less intensive monitoring. This partial action approach maintains measurement precision when needed while reducing overall computational energy consumption
Data Source
AI summary
A system and method for tracking and alerting a drone flying overhead are provided herein. The method includes acquiring a first data associated with a user device position; detecting a path corresponding to movement of the user device; receiving, from a server at the user device, drone data associated with a plurality of drones; filtering the drone data to obtain a second data associated with a drone position and a respective drone route which intersects with the path; predicting an intersection area; determining a distance between the user device position and the drone position based on the first data and the second data; determining whether a determined distance is equal to or less than a preset distance; and instructing a user to change the path or the speed of travel down a path when the determined distance is equal to or less than the preset distance.