Biometric Identification Supplement with Device Detection
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Solution Overview
Problem
Biometric identification systems face inefficiencies due to resource-intensive processes, inaccuracies, and scalability issues, particularly when identifying individuals among a large number of users, leading to delays and false positives/negatives.
Innovation Solution
Supplementing biometric identification with device identifiers, which are detected and associated with individual identities, to reduce the number of potential matches and improve accuracy and efficiency by using device detection to narrow down the search in biometric databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If biometric identification is performed using resource-intensive processes to improve accuracy, then identification accuracy is improved, but computing resources (power, processor, storage, memory, network capacity) are excessively consumed and delays occur
Solution Approach 1:
The identification process is segmented into two stages: first, a quick device identifier check that filters the candidate pool, then a more thorough biometric analysis only on the reduced set of matches. This segmentation reduces overall computational resources while maintaining accuracy.
Solution Approach 2:
Device identifier detection is performed as a preliminary action before full biometric analysis. This preliminary filter narrows down the search space, so that resource-intensive biometric processing is only applied to a small subset of potential matches rather than the entire database.
2Reliability
If multiple biometrics are used to improve identification accuracy, then false positives and false negatives are reduced, but the complexity of the identification system increases
Solution Approach 1:
The system merges device identifier detection with biometric analysis into a unified identification process. By combining these two identification methods, the system achieves higher reliability through multiple verification layers while managing complexity through integrated architecture rather than separate independent systems.
3Adaptability or versatility
If biometric databases are scaled to identify hundreds or thousands of individuals, then identification coverage is improved, but the probability of hash collisions grows at an unacceptable rate
Solution Approach 1:
Device identifiers serve as an intermediary filtering layer between the query and the biometric database. This intermediary reduces the effective search space before biometric comparison, thereby maintaining identification precision even as database scale increases to cover hundreds or thousands of individuals.
Data Source
AI summary
A computer may identify an individual according to one or more biometrics based on various physiological aspects of the individual, such as metrics of various features of the face, gait, fingerprint, or voice of the individual. However, biometrics are often computationally intensive to compute, inaccurate, and unable to scale to identify an individual among a large set of known individuals. Therefore, the biometric identification of an individual may be supplemented by identifying one or more devices associated with the individual (e.g., a mobile phone, a vehicle driven by the individual, or an implanted medical device). When an individual is registered for identification, various device identifiers of devices associated with the individual may be stored along with the biometrics of the individual. Individuals may then be identified using both biometrics and detected device identifiers, thereby improving the efficiency, speed, accuracy, and scalability of the identification.