Category-Based Sensing Data Transmission for Network Congestion Relief
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Solution Overview
Problem
The transmission of large volumes of sensing data from multiple devices to a central server can cause network congestion and inefficiencies, particularly in scenarios where devices capture different viewing angles, leading to occlusion and blind spots.
Innovation Solution
A category-based data transmission method that extracts and transmits only relevant data categories, using predefined or dynamically determined categories and periodicities to reduce the amount of data transmitted, addressing the mismatch in viewing angles and optimizing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all sensing data from multiple devices is transmitted to the sensing center, then complete environmental reconstruction can be achieved, but network congestion occurs due to substantial data amount
Solution Approach 1:
The patent extracts only the necessary and useful sensing data from multiple devices based on predefined categories and task requirements, rather than transmitting all raw data. This extraction process filters out redundant information while preserving the essential data needed for environmental reconstruction, thereby reducing network congestion while maintaining reconstruction completeness.
Solution Approach 2:
The patent segments sensing data into different categories (e.g., point cloud data, image data, depth information) and selectively transmits only the relevant segments required for specific tasks. This segmentation allows the system to transmit discrete, organized data portions rather than bulk data, reducing overall transmission volume while ensuring necessary information is delivered.
2Quantity of substance
If category-based data extraction is implemented, then data transmission volume is reduced, but data processing complexity increases at the transmitting device
Solution Approach 1:
The patent performs preliminary categorization and selection of sensing data at the source devices before transmission. By pre-processing and organizing data into defined categories according to task requirements, the system reduces the burden on the receiving end and simplifies overall system architecture, even though individual devices perform additional processing locally.
3Reliability
If all sensing data is transmitted for fusion, then accurate environmental reconstruction is achieved, but network resources are wasted
Solution Approach 1:
The patent extracts only the essential sensing data components required for accurate environmental reconstruction, filtering out redundant and unnecessary data before transmission. This extraction ensures that network resources are utilized efficiently by transmitting only the minimum necessary data volume while preserving reconstruction accuracy.
Solution Approach 2:
The patent transmits a partial set of sensing data that is sufficient for achieving the required reconstruction accuracy, rather than transmitting all available data. This partial action approach avoids the waste of network resources associated with excessive data transmission while maintaining the necessary level of accuracy for environmental reconstruction.
Data Source
AI summary
A data transmission method includes: obtaining Q first categories, where the Q first categories are data categories used by a second apparatus to execute a first task; obtaining S pieces of first sensing data, where the S pieces of first sensing data include C categories of data, and the C categories include at least one category different from the Q first categories; determining M pieces of first data from the S pieces of first sensing data based on the Q first categories, where categories corresponding to the M pieces of first data belong to the Q first categories, Q, S, M, and C are all positive integers, and M is less than S; and sending second data to the second apparatus, where the second data corresponds to the M pieces of first data.