Data Distribution System for Secure Sensing Data Sharing
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Solution Overview
Problem
Images and sensing data acquired by security cameras and in-vehicle cameras are primarily used privately by their installers and are not readily available to other users for security protection due to interface incompatibilities and privacy concerns.
Innovation Solution
A data distribution system comprising sensor devices and a server that enables the acquisition, processing, and distribution of sensing data. The system includes a sensor unit for data acquisition, a model acquirer for recognition model retrieval, a recognizer for data applicability assessment, a data generator for processing data according to requests, and a distributor for data dissemination. The server accepts distribution requests, generates recognition models, and transmits them to sensor devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If sensing data is shared across multiple users, then data utility and security protection capability are improved, but data security and privacy protection risks increase
Solution Approach 1:
The patent extracts only the essential features and metadata from sensing data (e.g., object type, location, time) while removing personally identifiable information and sensitive details. This allows the data to be shared for security protection purposes without exposing private information, resolving the contradiction between data utility and privacy protection.
Solution Approach 2:
The patent introduces an intermediary processing system that acts as a mediator between data collectors and data users. This intermediary anonymizes and aggregates sensing data before sharing, enabling multi-user access while maintaining privacy protection through controlled data transformation and selective information disclosure.
2Measurement precision
If sensing data is processed and shared in raw form, then data accuracy is improved, but data processing load and transmission bandwidth requirements increase
Solution Approach 1:
The patent extracts only the essential features and metadata from sensing data (e.g., object type, location, time) while removing personally identifiable information and sensitive details. This allows the data to be shared for security protection purposes without exposing private information, resolving the contradiction between data utility and privacy protection.
Solution Approach 2:
The patent segments sensing data into different levels of processing: raw data remains local for high-accuracy analysis, while processed features and metadata are shared for broader utility. This segmentation allows different parts of the data to serve different purposes, reducing overall processing load while maintaining accuracy where needed.
3Productivity
If a centralized data collection system is implemented, then data management efficiency is improved, but system complexity and single points of failure increase
Solution Approach 1:
The patent segments the data management system into distributed nodes that independently process and manage their own sensing data. Each node can share processed features with others, creating a federated system that maintains management efficiency through standardized protocols while reducing complexity and eliminating single points of failure through decentralization.
Solution Approach 2:
The patent enables each data node to autonomously perform local processing, filtering, and feature extraction on its sensing data. This self-service capability reduces the burden on centralized management, allowing efficient data handling at the edge while maintaining coordination through standardized sharing protocols, thereby reducing overall system complexity.
Data Source
AI summary
Provided is a data distribution system 1 including one or more sensor devices 10 to acquire sensing data and a server 20 to accept a distribution request from one or more requestors requesting distribution of predetermined data capable of being generated from the sensing data.