Dynamic Video Compression Adjustment for Public Safety
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Solution Overview
Problem
Public safety video streaming applications require dynamic adjustment of video compression parameters based on the viewer's environment and mission, as fixed compression settings are inadequate for changing operational needs, such as situational awareness and high-quality object recognition, while conserving wireless network resources.
Innovation Solution
A policy enforcement device dynamically adjusts video compression parameters, such as spatial resolution, frame rate, and bit rate, based on environmental conditions detected by sensors like GPS and CAD assignment, allowing for real-time adaptation of video quality to match the viewer's mission and environment without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If video compression parameters are statically fixed for a given bit rate, then network bandwidth consumption is reduced, but video quality cannot be dynamically adjusted to match changing viewer mission requirements
Solution Approach 1:
The patent implements dynamic adjustment of video compression parameters based on the viewer's current mission and environmental context. The system transitions from static fixed parameters to dynamic parameter selection, where encoding resolution, frame rate, and bit rate are adjusted in real-time according to mission requirements (e.g., surveillance vs. identification vs. recognition tasks).
Solution Approach 2:
The system changes multiple video encoding parameters simultaneously based on mission type and environmental conditions. Different parameter sets are selected for different missions: lower parameters for surveillance during transit, higher parameters for identification and recognition when stationary or critically needed, optimizing the trade-off between quality and bandwidth consumption.
2Measurement precision
If high encoded video quality is transmitted to officers en route to an incident, then object recognition capability is improved, but wireless system resources are unnecessarily consumed
Solution Approach 1:
The system prepares multiple pre-defined video quality profiles corresponding to different mission stages and environmental conditions. These profiles are established in advance and automatically selected based on the viewer's current state, eliminating the need for real-time manual adjustment and enabling rapid adaptation to changing requirements.
Solution Approach 2:
Different video quality levels are applied locally to match specific mission requirements and environmental contexts. During transit or low-priority phases, lower quality is sufficient. When the officer arrives on scene or critical identification is needed, higher quality is applied locally to that specific viewing context, optimizing resource allocation.
3Productivity
If low encoded video quality is used to minimize wireless resource impact, then network efficiency is improved, but video quality is insufficient for recognition tasks when needed
Solution Approach 1:
The system dynamically adjusts video encoding quality based on real-time assessment of mission requirements and environmental conditions. Quality is not fixed but adapts continuously, transitioning from low quality during routine surveillance to high quality when recognition tasks are identified as necessary, thereby optimizing both network efficiency and video quality as needed.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor mission progress, environmental conditions, and resource availability to continuously adjust video quality parameters. This feedback loop ensures that quality is increased only when and where necessary for mission success, preventing unnecessary bandwidth consumption while ensuring adequate quality for critical tasks.
4Measurement precision
If video compression parameters are manually adjusted for each viewer's mission, then video quality matches mission requirements, but system complexity and operational overhead increase
Solution Approach 1:
The system automatically determines the appropriate video quality parameters based on the viewer's mission type and environmental context without requiring manual intervention. The automatic parameter selection engine analyzes mission requirements and selects optimal encoding settings, eliminating the need for manual adjustment while maintaining precise quality matching.
Solution Approach 2:
A single automated parameter selection engine handles multiple mission types and environmental conditions, providing universal functionality across diverse public safety operations. This multi-functional system replaces the need for separate manual configuration processes for each mission type, reducing operational overhead while maintaining adaptability.
Data Source
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AI summary
A policy enforcement device performs a method for adjusting video compression parameters for encoding source video based on a viewer's environment. The method includes: receiving, from a video receiving device, a video stream identifier indicating a video stream and a source of the video stream, wherein the video receiving device is remote from the source of the video stream; receiving an indication of environmental conditions of a viewer of the video stream using the video receiving device; determining a set of video compression parameters based on the indication of environmental conditions of the viewer; sending the set of video compression parameters to the identified source of the video stream to enable encoding of the video stream to a different compression level.