Indoor UAV Surveillance Tours With Baseline Anomaly Detection
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Solution Overview
Problem
Conventional commercial surveillance systems require significant investment in video cameras and infrastructure, leading to missed conditions and high costs due to false alarms, making them impractical for small to medium-sized facilities, while military drones are too expensive for commercial use.
Innovation Solution
Programming an unmanned aerial vehicle (UAV) to fly specific patterns within a facility, receive sensor data, process it for feature differences, and adjust flight instructions to detect anomalies, reducing the need for extensive camera coverage and minimizing false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If conventional commercial surveillance systems use multiple video cameras to cover large areas, then surveillance coverage is improved, but system cost and complexity increase significantly
Solution Approach 1:
The system divides the surveillance task into segments performed by a single mobile drone that visits different locations sequentially, rather than using multiple stationary cameras simultaneously. The drone performs repeated tours of the facility, capturing images at different waypoints during each tour.
Solution Approach 2:
The system transitions from a two-dimensional array of stationary cameras to a three-dimensional mobile platform that moves through space. The drone operates in the air space above the facility, providing surveillance from a different spatial dimension and eliminating the need for extensive horizontal camera deployment.
2Reliability
If conventional surveillance systems deploy many video cameras and analytics, then detection capability is improved, but false alarms increase and cost more
Solution Approach 1:
The system performs preliminary action by capturing baseline images during an initial tour before scheduled tours begin. These baseline images are stored and used for comparison during subsequent tours, enabling the system to detect changes from the normal state without requiring complex real-time analytics on every frame.
Solution Approach 2:
The system uses feedback by comparing images captured during scheduled tours against the stored baseline images. The image processor analyzes differences between current and baseline images to detect suspicious activity, creating a closed-loop system that reduces false alarms by referencing established normal conditions.
3Reliability
If military surveillance drones are used for large outdoor areas, then surveillance effectiveness is improved, but cost becomes prohibitive for commercial use
Solution Approach 1:
The system employs inexpensive commercial off-the-shelf drone components rather than expensive military-grade equipment. The drone uses standard cameras, basic navigation systems, and commercially available flight controllers, making the overall system cost-effective for commercial applications while maintaining sufficient surveillance effectiveness.
Solution Approach 2:
The system uses universal multi-functional components that can serve multiple purposes. The drone's camera serves both for navigation and surveillance, the flight controller handles both autonomous flight and image timing, and the same hardware platform can be used across different commercial applications, reducing overall system cost.
Data Source
AI summary
An unmanned aerial vehicle is described and includes a computer carried by the unmanned aerial vehicle to control flight of the unmanned aerial vehicle and at least one sensor. The unmanned aerial vehicle is caused to fly a specific pattern within a facility, receive sensor data from a sensor carried by the vehicle, apply processing to the sensor data to detect an unacceptable level of detected feature differences in features contained in the sensor data, determine a new flight instruction for the vehicle based on the processing; and send the new flight instruction for the vehicle to a system for controlling flight of the vehicle.