Edge AI Network Relay for Privacy-Safe Object Detection
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Solution Overview
Problem
Smart cameras rely on public cloud services for storage and processing, raising privacy and security concerns, and require specialized hardware, making it difficult to implement robust, independently secured IoT-enabled security systems.
Innovation Solution
An Input Output (I/O) Network Relay and a device with edge processing capabilities that integrate with video security systems, allowing for local operation and integration with various devices to trigger actions, perform object detection, and use machine learning for scene and object detection without relying on cloud architectures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cloud-based platforms are used for video processing and storage, then advanced AI capabilities and object detection are improved, but privacy and security are worsened due to data transmission over public networks
Solution Approach 1:
The patent extracts the AI processing capabilities from the cloud environment and embeds them directly into the camera device. The camera includes an integrated processor that performs object detection, scene analysis, and AI-based recognition locally, eliminating the need to transmit video data to external cloud servers while maintaining advanced detection capabilities.
Solution Approach 2:
The patent introduces an on-device AI processor as an intermediary between the camera sensor and the output system. This local processing unit acts as a mediator that analyzes video data in real-time without requiring external cloud infrastructure, thus preserving privacy while enabling sophisticated object detection and recognition functions.
2Measurement precision
If specialized smart camera hardware is used for cloud integration, then cloud-based AI processing is improved, but device compatibility and independence are worsened
Solution Approach 1:
The patent designs the smart camera with universal interfaces and protocols that enable compatibility with multiple camera types and configurations. The system can process video from various sources including IP cameras, analog cameras, and multiple camera feeds simultaneously, while maintaining the integrated AI processing capabilities for object detection and analysis.
3Measurement precision
If cloud services are required for video processing, then advanced detection features are improved, but system autonomy and energy efficiency are worsened
Solution Approach 1:
The patent extracts the computationally intensive AI processing functions from remote cloud servers and relocates them to the camera's local processor. This enables the camera to perform object detection, facial recognition, and scene analysis independently without requiring continuous cloud connectivity, thereby reducing energy consumption associated with data transmission and enabling autonomous operation.
4Adaptability or versatility
If cloud-based IoT platforms are used for device control, then smart home integration is improved, but system security and independence are worsened
Solution Approach 1:
The patent introduces a local processing unit and edge computing architecture as intermediaries that enable smart home integration functions to execute on-device. The camera can perform local video analysis, trigger alerts, and integrate with security systems without requiring constant cloud platform mediation, thus maintaining smart functionality while reducing security vulnerabilities associated with cloud dependency.
Data Source
AI summary
Embodiments are directed to a relay configured to operate a plurality of electric appliances in conjunction with smart camera device that performs object detection.