Bandwidth Density Model for Crowd-Aware Communication Optimization
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Solution Overview
Problem
Existing communication technologies face challenges in managing communication service quality, particularly in crowded geographical spaces where high crowd density leads to reduced bandwidth and poorer communication services, due to dynamic and complex localized environment constraints.
Innovation Solution
A computer-implemented method and system that generates a bandwidth density model based on crowd movement and user activity information, determining optimal communication service parameters and instructing users to move to target locations within a geographical space to optimize communication quality by minimizing crowd density and interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users remain in crowded geographical spaces, then user activity and engagement are maintained, but communication bandwidth density decreases and service quality deteriorates
Solution Approach 1:
The system continuously monitors crowd movement information and user activity information, generates a bandwidth density model based on this feedback data, and uses it to determine quality of communication service parameters. This closed-loop feedback mechanism enables dynamic adjustment of communication resource allocation based on real-time crowd density and user activity patterns, resolving the contradiction between maintaining user engagement in crowded spaces and ensuring communication service quality.
Solution Approach 2:
The bandwidth density model dynamically captures variations in communication bandwidth density with respect to location and time. The system continuously updates quality of communication service parameters based on changing crowd movement patterns and user activity, enabling adaptive resource allocation that responds to dynamic environmental conditions rather than relying on static configurations.
2Productivity
If communication resources are allocated to high-density areas, then more users can be served, but bandwidth per user decreases and interference increases
Solution Approach 1:
The system determines quality of communication service parameters with respect to specific locations within the geographical space. By analyzing crowd movement information and user activity at different locations, the bandwidth density model enables localized resource allocation that tailors communication resources to specific spatial zones, allowing high-density areas to receive appropriate resources while minimizing interference through location-specific optimization.
3Reliability
If the system instructs users to move to target locations, then communication bandwidth and service quality improve, but user convenience and operational simplicity decrease
Solution Approach 1:
The system automatically generates a bandwidth density model based on crowd movement information and user activity information without requiring manual user input or intervention. The determination of quality of communication service parameters and target locations is performed autonomously by the system, reducing the operational burden on users while maintaining improved communication service quality through automated resource optimization.
Data Source
AI summary
Techniques for managing the quality of a communication service may include obtaining crowd movement information relating to movement of individuals in a crowd within geographical spaces, and obtaining user activity information relating to one or more activities of interest to a user in a geographical space. A bandwidth density model is generated, based on the obtained crowd movement information and user activity information, the bandwidth model describing a variation of communication bandwidth density in the geographical space with respect to location and time. Quality of communication service parameters are determined, based on the bandwidth density model, with respect to location for the geographical space. Based on the quality of communication service parameters and a current location of the user in the geographical space, a target location in the geographical space is determined for the user. The user is instructed to move to the target location in the geographical space.