Edge Sensor Processing With Feature Vectors for Privacy Protection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Security systems generate large volumes of sensitive sensor data that require extensive computing resources, and transmitting this data to remote systems can compromise user privacy.
Innovation Solution
Distribute processing of sensor data among edge devices within a local network, generating feature vectors locally to preserve privacy, and selectively transmit these vectors to remote systems for further analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor data is transmitted to remote systems for processing, then sophisticated event determinations can be made, but user privacy is compromised due to exposure of raw sensitive data
Solution Approach 1:
The patent segments the data processing function by separating raw sensor data processing from remote systems and assigning feature vector generation to local edge devices. This segmentation allows sophisticated event determination to occur through distributed processing while keeping raw sensitive data local, thus resolving the contradiction between analysis capability and privacy protection
Solution Approach 2:
The patent introduces feature vectors as an intermediary representation between raw sensor data and remote system analysis. Instead of transmitting raw sensitive data, edge devices generate compressed feature vectors that retain essential information for event determination while obscuring personally identifiable information, thereby enabling accurate analysis without privacy exposure
2Measurement precision
If all sensor data is processed by remote systems, then comprehensive analysis is achieved, but computational burden on remote systems increases significantly
Solution Approach 1:
The patent divides the computational workload by segmenting processing tasks between edge devices and remote systems. Edge devices perform computationally intensive feature extraction locally, while remote systems focus on higher-level analysis of the generated feature vectors. This segmentation reduces the computational burden on remote systems while maintaining comprehensive analysis capability
Solution Approach 2:
The patent applies preliminary action by having edge devices perform feature vector generation before data reaches remote systems. This pre-processing step extracts essential characteristics and patterns from raw sensor data locally, so that remote systems receive pre-processed, condensed information rather than raw data, significantly reducing their computational burden while preserving analysis comprehensiveness
Data Source
AI summary
Disclosed herein are computing system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for distributing processing of sensor data. For example, a computing system may be configured to determine processing capabilities of each of one or more edge devices of a network. Additionally, the computing system may determine available processing resources of each of the one or more edge devices. Moreover, the computing system may select, from the one or more edge devices, a target device, based on the processing capabilities of each of the one or more edge devices and the available processing resources of each of the one or more edge devices. Further, the computing system may communicate with the target device to cause the target device to generate one or more feature vectors based on sensor data generated by the target device.