Autonomous Hovering Drone Surveillance to Reduce False Alarms
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional commercial surveillance systems require significant investment in video cameras and are prone to missing conditions and false alarms, making them costly and inefficient for monitoring large areas.
Innovation Solution
Deploying unmanned aerial vehicles (drones) equipped with sensors and autonomous navigation, which can be remotely controlled to hover over specific locations within a facility, capture sensor data, and analyze it for unusual features, 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 area coverage is improved, but system cost and complexity increase significantly
Solution Approach 1:
The patent employs mobile robots equipped with cameras that dynamically move throughout the facility to perform surveillance, replacing static multiple camera systems. The robots can traverse different areas and adjust their positioning to monitor various locations, providing comprehensive coverage with fewer devices.
Solution Approach 2:
The patent introduces mobile robotic units that operate in the physical space of the facility, adding a mobile dimension to surveillance. Instead of relying solely on fixed camera positions, the system uses robots that can physically relocate to capture images from different vantage points and areas.
2Reliability
If conventional surveillance systems deploy many video cameras and analytics processors, then detection capability is improved, but false alarm rate increases
Solution Approach 1:
The patent implements a feedback mechanism where captured images are analyzed by processors that compare current images with historical data from the same locations. This feedback loop allows the system to learn from past observations and distinguish between normal variations and actual anomalies, reducing false alarms while maintaining detection capability.
Solution Approach 2:
The system performs preliminary actions by capturing and storing baseline images of normal conditions at various locations before monitoring for anomalies. This preliminary data serves as a reference for comparison, enabling the system to identify deviations from normal conditions more accurately and reduce false positive detections.
3Reliability
If conventional systems use extensive video camera coverage, then surveillance robustness is improved, but cost increases significantly
Solution Approach 1:
The patent employs mobile robotic units that serve multiple functions: they can navigate to different locations, capture images, store data, and perform analysis. These multi-functional robots replace the need for numerous specialized fixed cameras and processors, providing robust surveillance coverage while reducing overall system cost through functional consolidation.
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 to a specific location within a facility, where the unmanned aerial vehicle enters a hover mode, where the unmanned aerial vehicle remains in a substantially fixed location hovering over the specific location within the facility and sends raw or processing results of sensor data from the sensor to a remote server system.