Autonomous Security Drone Navigation Using RF Triangulation
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Solution Overview
Problem
Conventional commercial surveillance systems require significant investment in video cameras and are prone to missing conditions, leading to false alarms and high costs for alarm monitoring companies, building owners, and security professionals, while military drones are expensive and not practical for small areas.
Innovation Solution
Deploying unmanned aerial vehicles (UAVs or drones) equipped with sensors and autonomous flight control to hover over specific locations within a facility, capturing and processing sensor data to detect unusual feature differences, thereby reducing false alarms and enhancing surveillance efficiency at lower costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional video surveillance systems are deployed to cover all critical areas, then surveillance coverage is improved, but system cost and complexity increase significantly
Solution Approach 1:
The patent applies multi-functionality by integrating multiple surveillance capabilities into a single mobile drone platform. The drone combines aerial video capture, ground-level inspection, sensor data collection, and autonomous navigation in one system, replacing multiple separate surveillance systems with a single versatile platform that can adapt to different monitoring needs through software configuration and mission planning.
Solution Approach 2:
The patent implements dynamics by transitioning from fixed, stationary camera positions to a mobile, dynamically positionable drone system. The drone can move freely throughout the facility, adjust its position in real-time based on detected events, and adapt its surveillance coverage dynamically, providing both broad area monitoring and focused detailed inspection as needed.
2Reliability
If multiple video cameras and analytics tools are deployed to detect all conditions, then detection capability is improved, but false alarms increase and costs rise
Solution Approach 1:
The patent combines multiple detection modalities and data sources into a unified analysis system. The drone integrates video camera data, sensor readings (temperature, humidity, gas detection), and autonomous navigation information, merging these diverse inputs into a single coherent surveillance system that cross-validates information to reduce false alarms through multi-parameter verification.
Solution Approach 2:
The patent implements feedback mechanisms where the drone autonomously responds to detected conditions by adjusting its behavior. When sensors detect unusual conditions or the video system identifies potential threats, the system provides feedback that triggers autonomous navigation to reposition the drone for better observation, hover at critical locations for detailed inspection, or return to base for data analysis, creating a closed-loop surveillance system that continuously refines its detection accuracy.
3Reliability
If military surveillance drones are used for large outdoor areas, then surveillance effectiveness is improved, but cost becomes prohibitive for small facilities
Solution Approach 1:
The patent employs cost-effective, commercially available drone components and sensors rather than expensive military-grade equipment. The system uses affordable video cameras, standard environmental sensors, and consumer-grade autonomous navigation technology, making the surveillance system economically viable for small to medium-sized facilities while maintaining effective surveillance capabilities through intelligent software and autonomous operation.
Data Source
AI summary
A method of aerial surveillance including sending from a building management system (BMS), to a computer system, an alarm condition. The method further including programming, by the computer system, a drone with a route to a location of interest, wherein the route includes a portion of a map, the map including a data structure representation of a number of radio-frequency (RF) devices associated with one or more surveillance locations. The drone navigates to the location of interest by triangulating its position on the route using signals from the number of RF devices. The method further including sending, by the drone, to the computer system, sensor data including image data in response to arriving at the location of interest.