Intelligent Image Sensory System for Real-Time Content Classification
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Solution Overview
Problem
Current information handling systems face challenges in efficiently processing and classifying digital image and video data, particularly in real-time, due to network congestion, increased latency, and security risks associated with remote cloud-based processing, which can lead to inappropriate content being transmitted.
Innovation Solution
An intelligent image sensory system is developed, integrating a CCD/CMOS image sensor with a dedicated image signal processor and memory device, capable of local classification and processing, reducing the need for remote processing and minimizing data transmission, while incorporating AI for content analysis and audio input for enhanced control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If remote cloud-based processing is used for image classification, then processing capability is improved, but network bandwidth consumption increases and latency increases
Solution Approach 1:
The system segments the image processing function from the host system and places it in a dedicated camera module with embedded processing circuits. This allows classification to occur locally at the camera level without requiring continuous network communication, thus maintaining processing capability while reducing network bandwidth consumption.
Solution Approach 2:
The patent introduces an intermediary classification system within the camera module that acts as a gatekeeper between the image sensor and the host system. This intermediary performs preliminary classification locally, filtering out inappropriate content before it reaches the host or requires network transmission, thereby reducing both processing load and network usage.
2Extent of automation
If remote cloud-based processing is used for image classification, then processing capability is improved, but latency increases
Solution Approach 1:
By segmenting the processing function into a dedicated camera module with embedded processing circuits, the system enables immediate local classification without waiting for remote cloud processing. This significantly reduces latency while maintaining classification capability.
Solution Approach 2:
The classification process is performed preliminarily and immediately at the camera module level as images are captured, before any potential transmission to the host system or network. This preliminary action eliminates the time delay associated with remote processing.
3Extent of automation
If remote cloud-based processing is used for image classification, then processing capability is improved, but security risks increase
Solution Approach 1:
The patent extracts the classification function from the host system and network environment, placing it within the isolated camera module. This extraction removes the security vulnerability of transmitting private data over networks, as classification occurs in a secure, isolated environment within the camera itself.
Solution Approach 2:
The embedded processing circuits within the camera module serve as a secure intermediary that handles sensitive image data locally without requiring transmission to external systems. This intermediary layer protects private data from network-based security threats while maintaining classification functionality.
4Loss of energy
If local processing is implemented in the camera module, then network bandwidth consumption is reduced, but device complexity increases
Solution Approach 1:
The patent merges the image sensor, processing circuits, and memory into a single integrated camera module. This consolidation reduces overall system complexity by eliminating the need for separate processing units and reducing the number of components that require management, while still enabling local processing to reduce network bandwidth consumption.
Solution Approach 2:
The camera module is designed with multi-functional embedded processing circuits that can perform classification, filtering, and other image processing tasks locally. This universality allows a single device to handle multiple functions that would otherwise require separate components, reducing overall system complexity while enabling bandwidth reduction.
5Loss of energy
If local processing is implemented in the camera module, then power consumption is reduced, but device complexity increases
Solution Approach 1:
By merging the processing circuits directly into the camera module's fabric, the system eliminates the need for data transmission to remote systems, significantly reducing power consumption. The integrated design reduces the number of active components and communication interfaces, offsetting the added complexity of local processing.
Solution Approach 2:
The camera module performs classification and processing autonomously using its own embedded circuits and memory, without requiring external processing power or network resources. This self-service capability reduces overall system power consumption while the integration keeps the added complexity manageable within a single module.
Data Source
AI summary
An intelligent image sensory system includes its own embedded or modular image processing capability. The intelligent image sensory system may capture, process, and content classify digital frames. Each digital frame may be classified as permissible or objectionable, according to trainable content rules and policies. The intelligent image sensory system conducts a real time, frame-by-frame content analysis to avoid sharing of personal/sensitive data. An audio input system may also be controlled, based on the content of each frame.