Trajectory Determination Device Using Mobile Signaling Data
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Solution Overview
Problem
Current methods for determining human flows between locations are unreliable, costly, and lack contextual information, as they cannot accurately identify the origin of individuals, their transportation means, or provide detailed movement patterns.
Innovation Solution
A trajectory determination device and method that processes signaling data from mobile communication devices to classify movement markers as either movement or short stops, using specific rules to generate trajectory data, and identifies candidate sets for further analysis based on speed and location thresholds, allowing for the extraction of reliable and contextual movement information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If statistical methods with human measurement are used to determine human flows, then implementation is simple, but reliability is poor and contextual information is lost
Solution Approach 1:
The patent replaces manual human measurement with an automated electronic processing system that analyzes signaling data from mobile devices. The classifier and analyzer components automatically process location data, time markers, and movement patterns without human intervention, substituting mechanical human observation with electronic data processing to improve reliability while maintaining manageable complexity
Solution Approach 2:
The system creates a digital representation (copy) of physical human movement by processing signaling data from mobile devices. Instead of directly observing and counting people, the system generates trajectory data that copies movement patterns from electronic signals, enabling reliable automated analysis of human flows with full contextual information preserved
2Ease of manufacture
If manual counting methods are used to measure people entering and leaving locations, then implementation cost is high, but the method provides basic flow data
Solution Approach 1:
The system enables mobile devices to self-report their location and movement data through signaling data automatically generated during normal network operations. The classifier and analyzer components process this self-reported data without requiring active user participation or specialized equipment, reducing implementation cost while capturing rich contextual information about movement patterns, origins, and transportation methods
Solution Approach 2:
The patent utilizes existing mobile communication infrastructure and signaling data that already exists for regular network operations. The same network infrastructure used for basic communication also provides trajectory information, making the system cost-effective while delivering comprehensive movement data including location, time, and contextual details about human flows
3Measurement precision
If basic signaling data is processed without classification rules, then processing is fast, but trajectory accuracy is poor
Solution Approach 1:
The patent segments the trajectory determination process into distinct functional stages: a classifier that applies movement rules to mark signaling data with movement markers, and an analyzer that processes marked data to generate trajectory information. This segmentation allows each component to specialize in specific processing tasks, improving accuracy through systematic rule application while managing processing time through efficient modular architecture
Solution Approach 2:
The classifier performs preliminary action by pre-processing signaling data and marking it with movement markers before the analyzer processes it. This preliminary classification organizes raw data into structured information with identified movement patterns, making the subsequent trajectory analysis more accurate and efficient, thereby improving measurement precision without excessive time loss
Data Source
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AI summary
A trajectory determining device is designed for determining trajectory data (10) based on signalling data associating mobile communication device identifiers, time markers and signalling identifiers, at least some of the signalling identifiers designating a location cell. These trajectory data are used in order to identify pairs of movement markers associated with a same mobile communication device identifier, and corresponding signalling data, the time markers of which are between the time markers of a given pair, are reprocessed in order to return classified movement data (16) associating movement type data and departure and arrival data determined from location cells associated with the signalling data and a group of chosen locations.