Geolocation Characterization via Segmented Cellular Signaling

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Solution Overview

Problem

Existing methods for characterizing geographical locations of groups of mobile device users infringe on privacy and are often illegal due to continuous location tracking, limiting their ability to construct reliable patterns, especially when restricted to short collection periods like 90 minutes.

Innovation Solution

A system that aggregates signaling data from cellular networks over a limited time, cross-checks it with anonymous multi-sensor data, and uses statistical models to derive mobility patterns, classifying users into groups while ensuring privacy through anonymous records and periodic erasure of identity details, providing insights into behavioral patterns without continuous tracking.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If continuous location tracking is used to characterize geographical locations and user behavior patterns, then the reliability and accuracy of location characterization is improved, but user privacy is infringed and the method becomes illegal in many jurisdictions

Engineering Contradiction:

Improvereliability of location pattern constructionVSAvoiduser privacy infringement

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent segments the continuous tracking process into discrete 90-minute collection windows. Within each window, location data is collected and processed independently, then discarded. This segmentation allows sufficient data accumulation for reliable pattern construction while preventing continuous surveillance that would violate privacy rights.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system implements periodic data collection at 90-minute intervals rather than continuous tracking. Each periodic collection cycle gathers necessary location information, processes it through statistical models, and then terminates data collection. This periodic approach maintains analytical reliability while respecting privacy boundaries established by law.

Inventive Principle:

Principle #19Periodic action

2Object-affected harmful factors

If data collection is limited to 90 minutes to comply with privacy laws, then user privacy is protected, but the ability to construct reliable location patterns is reduced

Engineering Contradiction:

Improveuser privacy protectionVSAvoidability to construct reliable location patterns

Core Design Contradiction:

Object-affected harmful factorsVSReliability

Solution Approach 1:

The patent uses statistical models to create aggregated representations of user behavior patterns rather than tracking individual users continuously. The system collects location data from multiple users, processes it through statistical algorithms, and generates population-level mobility patterns. This copying approach extracts meaningful insights from limited data windows while maintaining privacy protection.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system changes the analysis parameter from individual continuous tracking to aggregated statistical patterns over 90-minute windows. By transforming individual location data into statistical distributions and mobility patterns, the system extracts reliable behavioral characteristics from limited time periods without requiring long-term continuous surveillance.

Inventive Principle:

Principle #35Parameter changes

3Loss of information

If statistical models and multi-sensor data are used to analyze user mobility patterns, then insights into user behavior are provided, but the system complexity increases

Engineering Contradiction:

Improveinsights about user behaviorVSAvoidsystem complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent employs a unified statistical modeling framework that processes multiple data sources (cellular network signaling data, GPS data, accelerometer data) through the same analytical pipeline. This universal approach handles diverse input types consistently, reducing system complexity compared to having separate processing systems for each data source.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system introduces statistical models as intermediary layers between raw sensor data and behavioral insights. These statistical models aggregate and interpret multi-sensor data, transforming complex raw inputs into meaningful mobility patterns. The intermediary statistical processing simplifies the overall system architecture by providing a standardized transformation layer.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS9609483B2System for characterizing geographical locations based on multi sensors anonymous data sources

Publication Date: 2017.03.28 DEUTSCHE TELEKOM AG

AI summary

System and method for characterizing a geographical location by finding the behavioral patterns of groups of users of mobile devices being in the vicinity of the geographical location. Accordingly, after an examined Point of Interest is determined, signaling data related to the users is aggregated over a limited period of time, from the cellular network they use. The location, including change in the location of the users, is continuously calculated and cross-checked with anonymous multi-sensors with data records from external data sources. Then the mobility patterns of users are derived and the users are classified to groups according to the cross-checking results. Finally, the geographical location is characterized according to the mobility patterns and the classification.