UAV Geofence Privacy Control for Sensor Restriction and Image Obfuscation
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) operating in areas with heightened privacy concerns face challenges in ensuring that they do not capture sensitive data or images beyond designated boundaries, as existing systems lack effective mechanisms to restrict sensor operations or obfuscate data in real-time.
Innovation Solution
A UAV computer system is configured to limit or disable sensors and payload devices when approaching geofence boundaries, and to obfuscate or delete images captured outside designated areas through real-time graphics processing, using GNSS, IMU, and ground altitude data to determine and modify imagery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the UAV operates sensors and payload devices freely, then data collection capability is improved, but privacy violation risk increases
Solution Approach 1:
The system pre-defines geofence boundaries and privacy zones before flight operations. The UAV computer system is pre-configured with geographic coordinates, elevation data, and sensor operational constraints for specific areas. This preliminary configuration enables automatic enforcement of privacy controls during flight without real-time intervention, allowing full sensor operation within authorized zones while automatically restricting operation near privacy boundaries.
Solution Approach 2:
The system applies different sensor operational characteristics to different geographic zones. Within the geofence, sensors operate at full capability. As the UAV approaches privacy zone boundaries, the system locally adjusts sensor parameters such as reducing camera aperture, narrowing field of view, or disabling specific sensors entirely. This creates a gradient of sensor operational intensity that maintains data collection productivity while progressively reducing privacy violation risk near boundaries.
2Object-affected harmful factors
If the UAV restricts sensor operations near geofence boundaries, then privacy protection is improved, but data collection efficiency decreases
Solution Approach 1:
The system applies partial restriction to sensor operations rather than complete shutdown. Instead of disabling sensors entirely near geofence boundaries, the system partially restricts operation by adjusting parameters such as reducing camera resolution, limiting frame rate, narrowing angular coverage, or reducing transmission power. This partial action maintains sufficient data collection efficiency for mission objectives while providing adequate privacy protection in boundary zones.
Solution Approach 2:
The sensor operational constraints are dynamically adjusted based on the UAV's real-time position relative to geofence boundaries. The system continuously monitors GPS coordinates and automatically modulates sensor parameters as the UAV approaches or recedes from privacy zones. This dynamic adjustment optimizes data collection efficiency when far from boundaries while progressively activating privacy protections only when necessary near boundaries, minimizing overall impact on productivity.
3Object-affected harmful factors
If the UAV modifies images in real-time, then privacy compliance is improved, but processing time and energy consumption increase
Solution Approach 1:
The system extracts and processes only the specific portions of images that require privacy modification. Rather than processing entire images or applying blanket filters to all captured data, the system identifies and isolates only those image regions that fall within privacy zones or contain sensitive information. This selective extraction approach applies privacy controls only where necessary, minimizing processing time and energy consumption while maintaining compliance.
Solution Approach 2:
The system uses lightweight, computationally efficient image processing algorithms that can be executed rapidly on-board the UAV. Instead of employing complex, time-consuming privacy enhancement techniques, the system applies simpler modifications such as selective pixel blurring, low-pass filtering, or geometric distortion that achieve adequate privacy compliance with minimal processing overhead. These lightweight processing operations complete quickly, reducing time loss and energy consumption.
4Adaptability or versatility
If the UAV uses multiple sensors and payload devices, then operational versatility is improved, but complexity of privacy control increases
Solution Approach 1:
The system implements a universal privacy control framework that manages multiple diverse sensors and payload devices through a single integrated computer system. This universal controller applies consistent geofence-based logic and boundary detection algorithms across all sensor types, regardless of their specific functions. Whether managing cameras, LIDAR, radar, or other sensors, the system uses the same privacy boundary definitions and control mechanisms, simplifying the overall complexity of managing privacy for multiple devices while maintaining operational versatility.
Data Source
AI summary
Disclosed in this specification are methods, systems and apparatus, including computer programs encoded on non-transitory computer storage media for unmanned aerial vehicle (UAV) flight operation and privacy controls. Based on geofence types, and UAV distance from a geofence, sensors and other devices connected to a UAV are conditionally operational. Image data collected during a UAV flight may be obfuscated by the UAV while in flight, or via a post-flight process using log data generated by the UAV.