Sense Chip Data Densifier for Low-Latency Image Transmission
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Solution Overview
Problem
Existing data transmission methods face high latency and power consumption due to the need to transmit entire image data, especially when only specific regions of interest require updates, leading to inefficiencies in data densification.
Innovation Solution
A data densification method using a sense chip with multiple operation units that classify and filter out non-interesting data units, merging the remaining sub-densified data into densified data for efficient transmission, reducing power consumption and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If sequential comparison of each data unit with information of interest is used, then hardware complexity is reduced, but output latency increases significantly
Solution Approach 1:
The patent divides the data units into multiple groups and processes each group in parallel using separate operation units. This segmentation allows simultaneous processing of multiple data units while keeping each operation unit's complexity manageable, thus reducing overall latency without requiring exponentially complex hardware
Solution Approach 2:
The patent uses classification information to identify and process only the subset of data units that are of interest, rather than processing all data units. This partial action approach reduces the number of operations needed while maintaining hardware efficiency
2Loss of time
If simultaneous comparison of all data units with information of interest is used, then output latency is reduced, but hardware complexity increases exponentially
Solution Approach 1:
The patent segments data units into groups that can be processed in parallel by multiple operation units. This allows simultaneous processing (reducing latency) while keeping each operation unit's complexity manageable through division of labor
Solution Approach 2:
Multiple operation units are designed with identical or similar structures that can process different groups of data units using the same classification information. This universal design allows parallel processing without requiring exponentially different hardware for each data unit
3Loss of information
If entire sense image data is transmitted, then data completeness is maintained, but power consumption increases
Solution Approach 1:
The patent extracts and transmits only the data units that are of interest to the system, filtering out unnecessary data before transmission. This extraction process maintains data completeness for relevant information while significantly reducing the total data volume and associated power consumption
Solution Approach 2:
The patent applies different processing treatments to different data units based on their importance. Data units of interest are processed and transmitted with higher priority and completeness, while non-interest data units are filtered out, creating local quality differentiation in data handling
Data Source
AI summary
The present invention proposes a data densifier comprising a plurality of first operation units and a second operation unit. The plurality of first operation units are respectively configured to be instantiated according to classification information, and the plurality of instantiated first operation units are configured to densify a plurality of sub data included in input data into a plurality of sub densified data. The second operation unit is configured to be instantiated according to the classification information, and the instantiated second operation unit is configured to merge the plurality of sub densified data from the plurality of first operation units into densified data. In addition, a data densification method used by the data densifier and a sense chip comprising the data densifier are also proposed.