Crowd Size Estimation Using Wireless Network Data
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Solution Overview
Problem
Existing crowd size estimation methods, such as aerial photographic analysis, face limitations in providing continuous and accurate estimates, especially for dynamic events, geographically dispersed locations, and situations where aerial photography is not feasible, and are prone to errors and high costs.
Innovation Solution
A system and method utilizing wireless communications network data, specifically call detail records and signaling messages, to estimate crowd size through an analytical model that incorporates population-specific parameters, user data, and transaction data, allowing for continuous and accurate crowd size estimation without pre-knowledge of event locations or conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If aerial photographic analysis is used to estimate crowd sizes, then crowd size estimation can be performed, but the method requires pre-knowledge of event locations and cannot provide continuous estimation
Solution Approach 1:
The patent replaces the mechanical aerial photography system with an electronic data collection system using mobile devices. Instead of using aircraft to capture images, the system collects call detail records and signaling messages from mobile phones in the crowd, transforming a mechanical observation method into an electronic data-based estimation method that can operate continuously without pre-knowledge of event locations.
Solution Approach 2:
The patent introduces mobile devices as an intermediary between the crowd and the estimation system. These devices act as mediators that automatically collect and transmit data about crowd presence, eliminating the need for direct aerial observation and enabling continuous monitoring without requiring prior knowledge of where crowds will form.
2Adaptability or versatility
If aerial photographic analysis is used for geographically dispersed events, then crowd sizes can be estimated at multiple sites, but costs increase significantly
Solution Approach 1:
The patent creates a universal estimation system that uses the same mobile device data collection methodology across all locations. Instead of deploying separate aerial photography resources to each site, the system universally applies mobile device-based estimation at any number of geographically dispersed locations simultaneously, making the capability scalable without proportional cost increases.
Solution Approach 2:
The patent uses copies of data from mobile devices rather than requiring direct aerial observation at each location. By collecting and analyzing signaling messages and call detail records from mobile phones, the system creates data copies that can be processed remotely, eliminating the need for expensive aerial deployment to each dispersed location.
3Measurement precision
If aerial photography is used during night events or in restricted spaces, then crowd sizes can be estimated, but the method becomes infeasible due to lighting and access constraints
Solution Approach 1:
The patent replaces the optical-based aerial photography system with an electronic signal-based system. Instead of relying on visible light to capture images, the system uses mobile device signaling messages and call detail records that are independent of lighting conditions, thereby eliminating the harmful effect of darkness during night events.
Solution Approach 2:
The patent introduces mobile devices as intermediaries that collect data internally without requiring external illumination. These devices autonomously generate and transmit signaling messages that can be captured by the estimation system regardless of external lighting conditions or terrain restrictions, bypassing the harmful environmental factors that constrain aerial photography.
4Measurement precision
If aerial photographic analysis is performed at high resolution to improve accuracy, then detailed crowd counting is possible, but the complexity and cost of coordination increase
Solution Approach 1:
The patent extracts the data collection function from the complex aerial photography coordination system and places it directly in the mobile devices within the crowd. By taking out the observation function from centralized aerial control and distributing it to individual mobile devices, the system achieves high precision through aggregate data while dramatically reducing coordination complexity.
Solution Approach 2:
The patent enables mobile devices to self-serve the data collection function. Each device automatically generates and transmits its own signaling messages and location data without requiring external coordination or control. This self-service approach eliminates the complex coordination hierarchy needed for aerial photography while maintaining or improving measurement precision through distributed data collection.
Data Source
AI summary
Systems, methods, and computer program products are for estimating crowd size at a location. An exemplary method includes determining, at a crowd size analyzer, a number of wireless service users at the location, and estimating, at the crowd size analyzer, a total number of people at the location based upon the number of wireless service users determined to be at the location.