Local Sensor Filtering for Anonymous Occupant Tracking
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Solution Overview
Problem
Traditional ambient sensing technologies face privacy challenges due to the use of personally identifiable information (PII) and facial features, which expose sensitive information, and are inefficient with continuous sensor data transmission leading to computing resource waste.
Innovation Solution
A device configuration with local filtering mechanisms processes sensor data based on relevance to predictive tasks, limiting data transmission and using tracking target signatures based on point cloud features, enhancing privacy and reducing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data is continuously transmitted to a remote system for processing, then the system can monitor the environment comprehensively, but computing resource waste increases due to processing irrelevant data
Solution Approach 1:
The patent applies preliminary action by implementing a local filtering mechanism that pre-processes sensor data before transmission. The filtering mechanism evaluates data relevance to predictive tasks and only transmits filtered data to the remote system, avoiding the waste of computing resources on irrelevant data while maintaining comprehensive monitoring capability
Solution Approach 2:
The system is segmented into two functional parts: a local filtering mechanism at the sensing device that handles preliminary data processing, and a remote prediction system that receives only filtered relevant data. This segmentation distributes computing tasks appropriately, reducing overall resource waste while maintaining monitoring effectiveness
2Measurement precision
If PII and facial features are used to identify occupants, then tracking accuracy is improved, but privacy risks increase due to exposure of sensitive information
Solution Approach 1:
The patent extracts and removes personally identifiable information (PII) and facial features from the sensor data stream. The system processes data to identify occupants and track their activities while deliberately excluding PII and biometric information from being transmitted or stored, thereby maintaining tracking accuracy without compromising privacy
Solution Approach 2:
An intermediary processing layer is introduced between the sensing device and the prediction system. This intermediary filters out PII and facial features while preserving the essential movement and activity data needed for tracking, acting as a mediator that protects privacy while maintaining functional accuracy
Data Source
AI summary
Various embodiments of the present disclosure provide a local sensor processing technique process that improves the functionality of a computer in various aspects. The technique comprises receiving sensor data and generating movement data based on the sensor data that is reflective of a candidate movement for a tracking target within the monitored environment, generating movement feature values based on the movement data and a plurality of excursion feature parameters associated with (a) an entity signature definition and (b) one or more defined contextual attributes, generating a plurality of sensor-based feature values for an excursion event based on the movement feature values and historical movement feature values, identifying a triggering event based on a comparison between the sensor-based feature values and excursion event criteria, and in response to detecting the triggering event, providing an excursion message that comprises the plurality of sensor-based feature values.