Cloud-Based Geospatial Data Processing for Scalable Visualization
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Solution Overview
Problem
Carrier retail stores in areas with little to no radio coverage are often unsuccessful and unprofitable, leading to significant investment losses, as existing visualization tools are limited in processing and storing large data files, and are not scalable, making it difficult to generate accurate multilayer geographic visualizations for determining optimal store locations.
Innovation Solution
The system migrates storage and processing from a container to a cloud system, allowing for the efficient handling of large import files and scalable data storage, using a user-defined function to process files from various formats like Shapefiles and KML, and storing them in a cloud database for generating multilayer geographic visualizations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing visualization tools are used to process and store large data files, then the tools can generate geographic visualizations, but they are limited in processing capability and not scalable
Solution Approach 1:
The patent transitions from local container-based processing to cloud-based processing, adding a dimensional shift in terms of computing infrastructure. This enables handling of larger datasets and provides scalability through cloud resources while maintaining the same visualization functionality.
Solution Approach 2:
The patent introduces a cloud system as an intermediary between the container and the data processing tasks. The cloud system handles the heavy lifting of processing large data files and generating visualizations, allowing the container to remain lightweight while gaining access to powerful processing capabilities.
2Adaptability or versatility
If retail stores are positioned in areas with little to no radio coverage, then carrier expansion is achieved, but the stores are unsuccessful and unprofitable
Solution Approach 1:
The patent implements a feedback mechanism where multilayer geographic visualizations showing radio coverage data are used to guide retail store location decisions. By analyzing and visualizing coverage information before making location decisions, the system enables data-driven choices that improve the likelihood of store profitability while still allowing strategic expansion.
3Quantity of substance
If large import files are processed locally in a container, then data can be handled, but the container becomes overloaded and processing is inefficient
Solution Approach 1:
The patent extracts the data processing tasks from the container environment and relocates them to the cloud system. This separation allows the container to remain simple and lightweight for visualization purposes, while the cloud system handles the computationally intensive processing of large import files externally.
Data Source
AI summary
A method comprises storing, at a storage bucket of the communication system, an import file received from a client application at a workstation, wherein a user defined function of the communication system is triggered to execute when the import file is received from the workstation, retrieving, by the user defined function, the import file from the storage bucket, processing, by the user defined function, the import file to obtain a geospatial file, storing the geospatial file in a cloud database of the communication system, fetching, by an application of the communication system, the geospatial file from the cloud database, and generating, by a visualization application of the communication system, the multilayer geographical virtualization based on the geospatial file fetched from the cloud database.