Relay Server Spatial Overlap Removal for Sensor Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional data compression techniques do not account for redundancy among sensor data from multiple terminals, leading to potential further reduction in network traffic when collecting large amounts of data from numerous sensor terminals.
Innovation Solution
A relay server that collects sensor data from multiple terminals, identifies spatial overlaps, removes redundant data, and integrates the data to create relay data for upload to a central server, utilizing methods like Draco for further compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data compression is applied to individual sensor data files, then the size of individual data files is reduced and traffic during collection is reduced, but redundancy among sensor data from multiple terminals is not accounted for and further traffic reduction is possible
Solution Approach 1:
The patent merges sensor data from multiple terminals before compression, combining data from multiple sources into a single dataset that is then compressed as a whole. This allows the compression algorithm to identify and eliminate redundancies across different terminals, achieving greater compression ratios than individual file compression while managing complexity through unified processing.
Solution Approach 2:
The patent performs data aggregation and redundancy identification before the compression process. By preliminarily organizing data from multiple terminals and identifying overlapping information, the system prepares the data in an optimal state for compression, enabling more efficient traffic reduction without overwhelming computational complexity during the compression phase.
2Reliability
If sensor data is collected continuously from a large number of sensor terminals, then comprehensive data coverage is achieved, but network traffic increases and puts a great load on the network
Solution Approach 1:
The patent combines sensor data from multiple terminals and removes redundancies before transmission, merging overlapping information into a single consolidated dataset. This approach maintains comprehensive data coverage by preserving unique information from each terminal while eliminating duplicate data, thereby significantly reducing network traffic and energy consumption without sacrificing data completeness.
Solution Approach 2:
The patent discards redundant sensor data that appears across multiple terminals while recovering and preserving unique valuable information from each terminal. By identifying and removing duplicate measurements from overlapping sensor fields, the system reduces network load while maintaining the integrity and comprehensiveness of the collected data through selective retention of non-redundant information.
Data Source
AI summary
Provided is a relay server capable of reducing network traffic when collecting large amounts of sensor data from a large number of sensor terminals. A relay server that collects sensor data from a plurality of sensor terminals and uploads the sensor data to a central server via a network includes a data collection unit that collects the sensor data from the plurality of sensor terminals, a relay data creation unit that calculates a presence of spatial overlaps between the collected sensor data, removes overlaps between the sensor data, and creates relay data integrating the sensor data, and an upload unit that uploads the relay data to the central server.