UWB Surveillance Anonymization for Privacy-Secure Event Detection
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Solution Overview
Problem
Existing surveillance systems face challenges in ensuring data security and privacy, particularly in the context of personal sensor data collected by UWB sensors, as they often require significant effort to anonymize or delete data to protect identity, which can be inefficient and prone to unauthorized access.
Innovation Solution
A UWB monitoring system that employs anonymization techniques such as data modification or deletion, encryption, and selective suspension of anonymization during exceptional events, combined with UWB tokens for secure access control, to ensure that personal sensor data is protected and only accessible to authorized entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If personal sensor data is collected and stored for surveillance purposes, then monitoring capability and detection accuracy are improved, but data security risks and privacy protection difficulties increase
Solution Approach 1:
The patent extracts personally identifiable information (PII) from sensor data through automated anonymization processes. The system identifies and removes or masks PII elements such as facial features, voice patterns, and personal identifiers, retaining only the surveillance-relevant data for security monitoring purposes.
Solution Approach 2:
The patent introduces an intermediary anonymization layer between data collection and data storage/processing. This intermediary process transforms raw personal data into anonymized data while preserving the utility for security monitoring, acting as a buffer that protects original personal information.
2Reliability
If data anonymization is continuously applied to protect privacy, then personal data protection is improved, but access to necessary personal data during exceptional events becomes difficult
Solution Approach 1:
The patent implements dynamic anonymization that adjusts based on situational context. During normal operations, full anonymization is applied to protect privacy. When exceptional events are detected (such as security threats or emergencies), the system dynamically reduces anonymization intensity to allow access to personally identifiable information for investigative purposes.
Solution Approach 2:
The system changes the anonymization parameter settings based on event severity and type. The degree of anonymization is adjusted as a variable parameter, transitioning from high anonymization during routine monitoring to lower anonymization during exceptional events, balancing privacy protection with operational needs.
3Reliability
If anonymization filters are applied at the sensor level, then data security is improved, but processing time and computational effort increase
Solution Approach 1:
The patent applies anonymization filters in real-time as data is being collected from sensors, rather than processing data in batches afterward. This preliminary anonymization ensures data is protected from the moment of collection, preventing exposure during transmission and storage while maintaining continuous surveillance capability.
Solution Approach 2:
The patent replaces manual data handling and post-processing anonymization with automated real-time anonymization systems. The automated filters process data streams continuously without human intervention, reducing both processing time and the risk of manual errors while maintaining data security.
4Reliability
If all personal data is anonymized by default, then privacy protection is improved, but operational efficiency during security incidents decreases
Solution Approach 1:
The system dynamically adjusts the level of anonymization based on operational context. During normal surveillance operations, full anonymization is maintained to protect privacy. When security incidents or exceptional events are detected, the system automatically reduces anonymization to provide investigators with access to personally identifiable information, improving operational efficiency during critical events.
Solution Approach 2:
The degree of anonymization is implemented as a controllable parameter that changes based on event severity. The system transitions from a static all-or-nothing anonymization approach to a dynamic parameter-based approach, allowing fine-tuned adjustment of privacy protection levels to match operational requirements during different types and severities of security events.
Data Source
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AI summary
The invention relates to a UWB monitoring system (100) for monitoring a spatial region (102). The UWB monitoring system comprises a plurality of UWB sensors (110) which are distributed in the spatial region. The UWB sensors are configured to capture sensor data and to transmit the captured sensor data via the UWB. The UWB monitoring system is configured to capture sensor data comprising personal sensor data in the spatial domain using the UWB sensors, to filter the captured sensor data using an anonymisation filter (123), wherein the anonymisation filter is configured to anonymise the personal sensor data, to analyse the captured sensor data for detecting an exception event, and, upon detecting the exception event, to temporarily suspend anonymising the personal sensor data.