Security Camera Drone Mapping With Privacy-Zone Flight Paths
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Solution Overview
Problem
Existing building mapping technologies face challenges in efficiently and privately mapping indoor spaces due to obstacles like furniture and varying building layouts, and they often lack user control over drone navigation during security events.
Innovation Solution
A security camera drone (SCD) performs pre-mapping and detailed mapping by recording user paths and environmental data, allowing users to specify zones of interest and restricted areas, generating flight mission trajectories that respect privacy and navigate around obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a drone is used to map indoor spaces during security events, then response time and visibility are improved, but user privacy concerns and control over navigation are worsened
Solution Approach 1:
The system performs pre-mapping of the building space before security events occur, creating a digital floor plan and identifying optimal trajectory paths in advance. This preliminary action allows the drone to quickly execute pre-planned routes during security events without requiring real-time user guidance, thus improving response time while maintaining user control over the pre-defined paths.
Solution Approach 2:
The system introduces a computational intermediary that generates trajectory paths based on pre-mapping data and user-defined restrictions. This intermediary automatically calculates optimal routes that respect privacy zones and building constraints, eliminating the need for direct real-time user control while ensuring privacy requirements are met.
2Loss of information
If a drone navigates through building spaces during security events, then visibility and knowledge of layout are improved, but privacy concerns and restricted access areas are worsened
Solution Approach 1:
The building space is segmented into restricted zones and accessible zones based on user preferences and privacy requirements. The drone's navigation system is configured to automatically avoid restricted zones while thoroughly mapping accessible areas, thus providing comprehensive visibility where needed while protecting privacy-sensitive areas.
Solution Approach 2:
A computational intermediary processes the mapping data and automatically generates trajectory paths that respect privacy boundaries. This intermediary acts as a mediator between the drone's exploration function and privacy protection requirements, ensuring that valuable layout information is obtained without compromising user privacy.
3Measurement precision
If detailed mapping is performed during security events, then accurate floor plans and environmental data are obtained, but response time and efficiency are worsened
Solution Approach 1:
Comprehensive pre-mapping is performed during normal conditions to create detailed baseline floor plans and identify all building features. During security events, the drone only needs to execute pre-planned trajectory paths and capture specific event-related data, maintaining high accuracy while dramatically improving response efficiency.
Solution Approach 2:
The system performs partial mapping during security events by focusing only on critical areas and event-relevant data collection, rather than complete remapping. The pre-collected detailed data serves as a foundation, allowing the drone to achieve sufficient accuracy for security response without the time cost of comprehensive mapping.
Data Source
AI summary
A security monitoring system may implement a building space mapping process using a drone. The process involves generating a floor plan of the building space by performing pre-mapping and detailed mapping protocols, and allowing the user to specify particular areas of interest that may restrict or enhance the drone's ability to move through the building space. The drone may generate and travel along a trajectory path based on the floor plan and information collected during the mapping protocols.