Multi-Sensor Data Streams With Priority-Based Bandwidth Control
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Solution Overview
Problem
Existing real-time event broadcasting systems limit the amount of information conveyed to consumers by treating camera streams as fundamental data units rather than composite data from multiple sensors, leading to inefficient information presentation and bandwidth utilization.
Innovation Solution
A multi-sensor solution that captures and transmits composite image and data streams from various sensors, including CCD, CMOS, and non-image-based sensors, with prioritization algorithms and interpolation processes to enhance user experience and optimize bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple sensor data streams are transmitted to provide comprehensive scene information, then the information completeness and user experience are improved, but the bandwidth consumption and system complexity increase
Solution Approach 1:
The patent segments the comprehensive sensor data into multiple priority levels (high, medium, low). High-priority data contains essential scene information, while lower-priority data provides supplementary details. This segmentation allows the system to transmit only the necessary amount of data based on available bandwidth, resolving the contradiction between information completeness and bandwidth consumption by enabling selective transmission of data segments.
Solution Approach 2:
The patent applies local quality by differentiating the transmission quality of different data segments. Critical sensor data is transmitted with high fidelity and priority, while less critical data is transmitted with lower priority or compressed more aggressively. This allows the system to optimize bandwidth usage while maintaining the quality of essential information, addressing the trade-off between information completeness and bandwidth consumption.
2Loss of information
If data from multiple sensor types is integrated, then the visualization quality and information richness are improved, but the device complexity and processing requirements increase
Solution Approach 1:
The patent segments the multi-sensor data processing system into modular components: data acquisition modules for different sensor types, priority determination modules, and data integration modules. Each sensor type (cameras, microphones, depth sensors, etc.) is processed independently through its own pipeline, then integrated at a higher level. This modular segmentation reduces system complexity while maintaining the ability to integrate diverse sensor data for comprehensive visualization.
Solution Approach 2:
The patent implements a universal data processing framework that can handle multiple sensor types through a common architecture. The system uses a standardized interface and processing pipeline that works with various sensor inputs (image, audio, depth, temperature), allowing the same core logic to process different data types. This multi-functionality reduces device complexity by avoiding separate processing systems for each sensor type.
3Loss of time
If real-time processing of multi-sensor data is implemented, then the broadcasting timeliness is improved, but the computational load and energy consumption increase
Solution Approach 1:
The patent implements periodic processing intervals for different priority levels of sensor data. High-priority data is processed and transmitted with shorter intervals, while lower-priority data uses longer intervals. This periodic action with varying frequencies allows the system to maintain real-time responsiveness for critical information while reducing computational load for less time-sensitive data, balancing timeliness with energy consumption.
Solution Approach 2:
The system employs self-service mechanisms where each sensor data stream automatically determines its own priority level and processing requirements based on its characteristics and current system state. This enables autonomous decision-making at the data source level, reducing the need for centralized computational processing and thereby lowering overall computational load while maintaining real-time processing capability for essential data.
Data Source
AI summary
A computer-based filming production system is described. An illustrative system includes a real-world, physical environment having a set of sensors disposed about a filming volume and a production center computing system including at least one computer readable memory that enables a processor to store a prioritization policy including priorities for digital data streams and for each filming production workflow stage of a set of multiple filming production workflow stages, receive a set of sensor data representing a filming production in the filming production from the set of sensors, generate a set of digital data streams of renderable content from the set of sensor data via the filming production workflow stages and according to the priorities for each filming production workflow stage, where each digital data streams comprises prioritized rendering instructions for their respective renderable content derived from the prioritization policy, and then transmit the set of digital data streams.