Spatial-Temporal Pattern Analysis for Communication Network Queries
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Solution Overview
Problem
Current technologies lack effective methods for predicting and analyzing spatial-temporal informative patterns in data networks, which are crucial for optimizing communication network operations, resource allocation, and user interaction insights.
Innovation Solution
An Information Management Component (IMC) utilizing artificial intelligence (AI) and machine learning (ML) techniques analyzes data from various sources to determine and provide spatial-temporal patterns, enabling enhanced resource allocation, network planning, and user interaction insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional data analysis methods are used in communication networks, then implementation simplicity is maintained, but the ability to predict and analyze spatial-temporal informative patterns is insufficient
Solution Approach 1:
The patent replaces traditional mechanical data analysis methods with artificial intelligence and machine learning systems. The IMC uses AI/ML algorithms to automatically analyze communication network data, identify spatial-temporal patterns, and generate insights without manual intervention, thereby achieving high prediction accuracy while managing system complexity through automated intelligent processing
Solution Approach 2:
The patent introduces an Information Management Component (IMC) as an intermediary system between raw network data and decision-making processes. The IMC acts as a mediator that collects, processes, analyzes, and presents spatial-temporal pattern information to network operators, enabling them to make informed decisions without directly handling complex raw data or sophisticated analysis algorithms
2Loss of information
If comprehensive data analysis is performed to improve network operations, then user interaction insights are enhanced, but data processing time increases
Solution Approach 1:
The patent implements preliminary action by continuously collecting and pre-processing communication network data in the background before specific analysis requests are made. The IMC maintains ready-to-analyze data structures and pre-processed information, enabling rapid generation of spatial-temporal pattern insights when queries are submitted, thus reducing actual processing time while maintaining comprehensive information analysis
Solution Approach 2:
The patent extracts only the most relevant spatial-temporal pattern information from comprehensive network data for specific analysis purposes. The IMC selectively extracts meaningful patterns related to user interactions, device behaviors, and network performance metrics, discarding redundant information, thereby providing complete user interaction insights while minimizing data processing time and resources
Data Source
AI summary
Spatial-temporal informative patterns for users and devices associated with data networks can be predicted or determined. An information management component (IMC) can analyze respective groups of items of data stored in respective formats in respective databases. Some items of data can comprise respective signal measurement data representative of respective signal measurements associated with respective devices associated with a communication network. Based on the analysis results, IMC can determine a spatial-temporal pattern(s) associated with the respective groups of items of data, wherein the spatial-temporal pattern(s) can relate to a subject of interest. The IMC can utilize artificial intelligence and/or machine learning algorithms and models to facilitate determining the spatial-temporal pattern(s). In response to a query relating to the subject of interest, the IMC can provide information relating to the subject of interest and responsive to the query based on the spatial-temporal pattern(s).