Multi-sensor Surveillance System with Common Operating Picture
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Solution Overview
Problem
Current surveillance systems using unmanned aerial vehicles (UAVs) with multiple cameras generate overwhelming video data streams, making it difficult for a single human operator to identify and redirect the UAV effectively due to bandwidth limitations and the need for extensive monitoring of multiple data streams.
Innovation Solution
A method and apparatus that process video data streams by identifying objects, forming graphical representations, and displaying them in a three-dimensional model using a geographic coordinate system, allowing for easier visualization and operator decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple cameras are used in UAVs to capture comprehensive surveillance data, then the coverage and detection capability are improved, but the amount of video data streams increases making it difficult for operators to process
Solution Approach 1:
The system extracts only the essential information from multiple video streams by automatically identifying and tracking objects of interest. Instead of presenting all raw video data to operators, the system extracts object locations, movements, and relevant features, significantly reducing the information load while maintaining detection capability.
Solution Approach 2:
The patent introduces an automated object identification and tracking system as an intermediary between the multiple cameras and the human operator. This intermediary process automatically processes video streams from multiple cameras, identifies objects, tracks their movements, and presents consolidated information to operators, eliminating the need for operators to directly view and analyze all raw video streams.
2Quantity of substance
If a single human operator monitors multiple video data streams, then operator cost is reduced, but the operator becomes overwhelmed and unable to effectively identify and redirect UAVs
Solution Approach 1:
The system implements automated object identification, tracking, and data consolidation capabilities that serve themselves without human intervention. The automated system processes multiple video streams, identifies objects of interest, tracks their movements, and maintains updated location information, freeing operators from the burden of manually monitoring all video streams while keeping operator numbers low.
Solution Approach 2:
An automated processing system acts as an intermediary between multiple video streams and the single operator, filtering and consolidating information to present only relevant data. This intermediary layer handles the complexity of processing multiple streams, allowing the operator to work with simplified, pre-processed information and reducing overall operational complexity.
3Measurement precision
If video data is transmitted at high rates to maintain real-time surveillance, then data accuracy is improved, but bandwidth limitations restrict the amount of data that can be transmitted
Solution Approach 1:
The system extracts only the critical data elements needed for surveillance operations, such as object identification, location coordinates, and movement vectors. By extracting and transmitting only this essential information rather than complete video streams, the system maintains data accuracy for tracking and analysis while dramatically reducing the volume of data that must be transmitted over bandwidth-constrained channels.
Data Source
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AI summary
A method and apparatus for processing video data streams for an area. Objects are identified in the area from images in the video data streams. The video data streams are generated by cameras. First locations are identified for the objects using the images. The first locations are defined using a coordinate system for the images. Graphical representations are formed for the objects using the images. The graphical representations are displayed for the objects in second locations in a model of the area on a display system with respect to features in the area that are represented in the model. The second locations are defined using a geographic coordinate system for the model. A first location in the first locations for an object in the objects corresponds to a second location in the second locations for a corresponding graphical representation in the graphical representations.