Edge AI Sensing Modules for Privacy-Preserving Threat Detection
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Solution Overview
Problem
Conventional threat detection systems fail to provide adequate information and raise privacy concerns due to the transmission of data, including image data, in public areas, limiting their effectiveness in detecting active shooters and other threats.
Innovation Solution
The implementation of AI-enabled sensing modules that operate with a Software as a Service (SaaS) backend, capable of detecting various threats while preserving privacy by processing raw sensor data locally and deleting it immediately after analysis, thus preventing data access outside the sensing module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional detection systems transmit data including image data in public areas for analysis, then detection capability is provided, but privacy issues arise and data security deteriorates
Solution Approach 1:
The patent extracts the data processing function from the cloud/remote server and places it directly within the edge device (sensing module). The sensing module performs local analysis of sensor data using onboard processors and AI models, extracting only necessary metadata or alerts for transmission rather than transmitting raw image data. This extraction of processing capability to the edge eliminates the privacy harm while maintaining detection capability.
Solution Approach 2:
The system segments the detection architecture into distributed edge computing nodes (sensing modules) that independently process data locally. Each sensing module operates as an autonomous unit with its own processor and AI models, eliminating the need for centralized cloud processing of sensitive data. This segmentation allows data to be processed where it is generated, preventing privacy violations while maintaining system-wide detection capability.
2Reliability
If conventional detection systems transmit data in public areas, then detection is enabled, but data accessibility and security control are lost
Solution Approach 1:
The sensing modules are designed with self-contained processing capabilities, including onboard AI models and processors that enable them to autonomously analyze sensor data without requiring external cloud services. The modules self-manage their data processing, making decisions locally about what to transmit and what to discard, thereby maintaining security control while enabling detection functionality.
Solution Approach 2:
The system performs preliminary data processing and analysis at the edge device before any data transmission occurs. AI models and algorithms pre-loaded in the sensing modules conduct initial threat assessment and data filtering locally, determining whether and what data needs to be transmitted to external systems. This preliminary action prevents sensitive data from entering public networks, maintaining security while preserving detection capability.
3Object-affected harmful factors
If all raw sensor data is processed locally at sensing modules and deleted immediately, then privacy is preserved and data security is improved, but processing complexity and computational requirements increase
Solution Approach 1:
The patent applies parameter changes by implementing dynamic adjustment of processing intensity and data retention policies based on detected conditions. The sensing modules modify their processing behavior according to environmental context, threat levels, and operational requirements, allowing the system to adapt computational complexity to actual needs rather than maintaining constant high processing demands.
Solution Approach 2:
The system implements partial processing by selectively analyzing only the portions of sensor data that are most relevant for threat detection, rather than processing all raw data uniformly. The AI models prioritize and focus computational resources on critical features and patterns, reducing overall processing complexity while maintaining effective privacy protection and detection capability.
Data Source
AI summary
Disclosed implementations provide a system of sensing modules that can operate in conjunction with a Software as a Service (SaaS) backend to detect and alert of various threats. The sensing modules can be installed at fixed locations or can be mobile. All sensing and detection processing can be accomplished by the sensing module or by several sensing modules cooperating on a mesh network or other network communication architecture. Privacy is preserved because all raw sensor data collected for analysis is processed locally at the sensing module(s) and deleted immediately following the completion of analysis. Accordingly, raw sensor data is inaccessible outside of the sensing module(s) which can be secured through hardware and software security techniques.