Local Content Filtering for Real-Time Media Analysis
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Solution Overview
Problem
Existing content filtering systems rely on external servers, which consume significant computing power and network bandwidth, and may not effectively monitor offline content or data transferred through local ports.
Innovation Solution
A local content filtering method that uses a device's local processor and resources to preprocess and analyze media samples in real-time, determining if they contain objectionable content, and optionally sending suspicious content to a remote processor for further analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If external servers are used for content filtering, then filtering capability is provided, but network bandwidth consumption increases significantly
Solution Approach 1:
The content filtering system is segmented into local processing components and remote server components. The local processor handles preprocessing and initial analysis of media samples, while only suspicious content is sent to remote servers for further analysis. This segmentation reduces the amount of data transmitted over the network while maintaining effective filtering capability.
Solution Approach 2:
The local processor performs preliminary actions by preprocessing media samples and conducting initial content analysis before data is sent to remote servers. This preliminary action filters out benign content locally, reducing the volume of data that needs to be transmitted and processed remotely, thereby conserving network bandwidth.
2Reliability
If external servers are used for content filtering, then filtering capability is provided, but computing power consumption increases
Solution Approach 1:
The computing workload is segmented between local and remote systems. The local processor handles computationally intensive preprocessing and initial analysis tasks, while remote servers perform only the analysis of suspicious content. This segmentation distributes computing power consumption more efficiently and reduces overall system resource requirements.
Solution Approach 2:
Preliminary content analysis and preprocessing are performed locally before data is transmitted to remote servers. This preliminary action reduces the computing power required at remote servers by filtering out benign content locally, thereby reducing overall computing power consumption while maintaining filtering capability.
3Loss of energy
If local processing is used, then network bandwidth is conserved, but device resources are consumed
Solution Approach 1:
The local processor performs partial content analysis using AI routines trained to detect suspicious content. By using partial action (analyzing only media samples and focusing on key detection tasks), the system conserves device resources while still achieving effective filtering. The AI routines are optimized to make accurate detections with minimal computational overhead.
Data Source
AI summary
The present invention in some embodiments thereof relates to a system and method for detecting inappropriate content on a device and filtering content on a variety of media. Inappropriate content is detected by taking a sample of media from at least one of a local memory, a data stream from a network and a data stream from local sensor, preprocessing the sample using a local processor and locally stored software to determine if the sample is a likely candidate to include objectionable content, in response to said sample being found to be a likely candidate perform at least one of quarantining the sample, marking the media, sending the sample to a remote processor for further analysis, analyzing the sample using an artificial intelligence routine running on a local processor and analyzing the sample using an artificial intelligence routine running on said local processor.