Electronic Device Identification via Multi-Point Data Tracking
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Solution Overview
Problem
Conventional asset management solutions fail to accurately account for remote and mobile computing devices due to hardware and software changes, leading to challenges in identifying and tracking PC assets, which can result in regulatory concerns and data security issues.
Innovation Solution
A device attribute collection application that gathers key data points from electronic devices and a device identification application that links these devices to their owners, even if the data points change over time, enabling consistent tracking throughout the device's lifecycle and remote identification in case of theft or loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If firmware serial numbers are used to identify computer assets, then the identification is simple and relatively reliable, but hardware changes cause misidentification
Solution Approach 1:
The patent segments the identification system into multiple independent data points (hardware identifiers, software identifiers, configuration data) collected from different components of the computing device. This segmentation allows the system to track changes in individual components while maintaining overall device identification through the collective profile of multiple data points.
Solution Approach 2:
The patent transitions from one-dimensional identification (single serial number) to multi-dimensional identification by collecting and analyzing multiple data points across different dimensions (hardware, software, configuration). This dimensional expansion enables the system to distinguish between legitimate changes and misidentification scenarios.
2Ease of operation
If software-assigned identifiers are used to identify computer assets, then identifiers can be easily assigned, but opportunities for reassignment exist during OS reinstallation or hardware changes
Solution Approach 1:
The patent merges multiple identification data sources (hardware identifiers, software identifiers, configuration data) into a unified device profile. This combination creates a composite identification system where changing one data point does not result in complete reassignment, as the other data points maintain the device's identity linkage.
Solution Approach 2:
The patent implements a feedback mechanism that continuously monitors and compares current data points against the original device profile. When changes are detected, the system provides feedback to determine whether the device is the same asset that has changed or a different asset, preventing unauthorized reassignment while allowing legitimate modifications.
3Measurement precision
If multiple data points are collected to track device changes, then identification accuracy improves, but system complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where the system automatically collects, stores, and analyzes device data points without requiring manual intervention. The automated profile creation and change detection processes reduce operational complexity while maintaining high identification precision through systematic data management.
Solution Approach 2:
The patent manages complexity by dynamically adjusting which data points are collected and analyzed based on the device type, usage context, and change patterns. This selective parameter approach maintains measurement precision by focusing on the most relevant identifiers while reducing unnecessary data collection and processing overhead.
Data Source
AI summary
A utility to determine identity of an electronic device electronically, by running a device attribute collection application that collects key data points of the electronic devices and a device identification application that uses these key data points to link the electronic device to a specific owner or entity. Data points of the device may change over time for reasons such as reconfiguration, repair or normal daily use. The device identification application intelligently and consistently tracks changes in key data points associated with the device, even if the data points change over its lifecycle. The device may be identified remotely with the device identification application (e.g., in the event of theft or loss of the device) based on the collected data points. The device identification application may be deployed in conjunction with services that may include asset tracking, asset recovery, data delete, software deployment, etc.