Edge Image Optimization via Local Server Rule Adaptation
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Solution Overview
Problem
Existing techniques fail to optimize image data transmission by balancing connection speed, bandwidth, processing power, and resource load, leading to challenges in capturing, processing, and analyzing images in applications like IoT and surveillance.
Innovation Solution
A method and system that involve receiving server rules, generating local decision-making rules based on these rules and local events, analyzing image data to create image analytics, and optimizing image data for transmission, which includes both the original data and analytics, to efficiently manage bandwidth and processing loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all captured image data is transmitted to the server for processing, then the server can perform comprehensive analysis, but the network bandwidth consumption increases and the server processing load increases
Solution Approach 1:
The patent segments image data processing into two parts: local preprocessing at the edge device and remote processing at the server. The edge device performs initial analysis and filters image data locally, transmitting only relevant portions to the server. This segmentation reduces network bandwidth consumption while maintaining analysis completeness by distributing processing tasks across different locations.
Solution Approach 2:
The patent applies preliminary action by performing image analysis and filtering at the edge device before transmission to the server. The edge device pre-processes images, identifies relevant data based on local decision-making rules, and prepares optimized data for transmission. This preliminary processing reduces the volume of data that needs to be transmitted and processed remotely.
2Quantity of substance
If image data is processed locally at the edge device, then bandwidth consumption is reduced, but the local processing power requirements increase
Solution Approach 1:
The patent applies partial action by implementing selective local processing rather than complete processing. The edge device performs only essential preprocessing tasks such as basic filtering and initial analysis, while more complex processing is deferred to the server. This approach reduces local processing power requirements while still achieving bandwidth optimization.
Solution Approach 2:
The patent introduces a rule-based decision-making system as an intermediary between the edge device and server. Local decision-making rules guide the edge device in determining which images require processing and transmission, reducing unnecessary local processing operations. This intermediary layer optimizes the balance between local processing power consumption and bandwidth utilization.
3Measurement precision
If complex processing is performed at the server, then comprehensive image analysis is achieved, but the server processing load increases
Solution Approach 1:
The patent extracts and removes unnecessary image data at the edge device before transmission to the server. By filtering out irrelevant images and data through local decision-making rules, the system reduces the processing load on the server. Only essential and relevant image data is transmitted and processed at the server, maintaining analysis accuracy while improving server processing efficiency.
Solution Approach 2:
The patent applies local quality by tailoring the processing approach to local conditions at the edge device. Local decision-making rules are generated based on specific local events and requirements, enabling the edge device to perform appropriate preprocessing operations. This localized approach ensures that only data requiring server-level analysis is transmitted, optimizing the division of labor between edge and cloud.
4Adaptability or versatility
If more image data is transmitted to the server, then the server can perform more comprehensive analysis, but the network bandwidth requirements increase
Solution Approach 1:
The patent implements dynamic adaptation by adjusting the amount and type of image data transmitted based on local conditions and server capabilities. The system dynamically generates local decision-making rules based on local events, network conditions, and server status. This dynamic approach allows the system to maintain analysis comprehensiveness while adapting transmission requirements to available network bandwidth.
Data Source
AI summary
This disclosure relates generally to edge computing, and more particularly to method and system for optimizing image data for data transmission. In one embodiment, a method is provided for optimizing image data for transmission to a server. The method may include receiving a plurality of server rules from the server with respect to an optimization and a transmission of the image data, generating a plurality of local decision making rules based on the plurality of server rules and one or more local events, analyzing at least a first portion of the image data based on the plurality of local decision making rules to generate image analytics data, and generating optimized image data for transmission to the server. The optimized image data comprises at least a second portion of the image data and the image analytics data.