Network Status Insight System for Remote Work Connectivity
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Solution Overview
Problem
Enterprises face challenges in accurately and automatically providing network status insight information, especially for remote employees, due to issues like ISP outages, power outages, and local router problems, which disrupt remote work and are difficult to predict and respond to in real-time.
Innovation Solution
A network status insight system using a back-end application server that receives information from enterprise data stores, network provider data stores, and third-party outage detectors to apply a network status algorithm, generating enterprise network status results and displaying them through an interactive user interface, leveraging Machine Learning or Artificial Intelligence for risk assessment and mitigation strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to predict and analyze network status risks, then system complexity is reduced, but accuracy and real-time response capability deteriorate
Solution Approach 1:
The patent introduces an intermediary automated analysis system that acts as a mediator between raw network data and decision-makers. This system includes data collection modules, analysis engines, and reporting mechanisms that automatically process network status information, reducing the need for manual analysis while improving accuracy and real-time response capability.
Solution Approach 2:
The patent replaces manual mechanical analysis processes with automated computational systems. The system uses software-based data collection, processing, and analysis mechanisms to substitute human manual efforts, thereby improving measurement precision while managing system complexity through automation.
2Productivity
If real-time automated analysis is implemented for network status, then response speed and accuracy improve, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent divides the automated analysis system into distinct functional modules: data collection modules that gather network status information, analysis engines that process the data, and reporting mechanisms that deliver insights. This segmentation allows each component to be developed and implemented independently, reducing overall system complexity while enabling real-time automated analysis.
Solution Approach 2:
The patent designs the automated analysis system to perform multiple functions: monitoring network status, predicting risks, generating reports, and providing alerts. This multi-functionality consolidates what would otherwise require separate systems into a single integrated platform, improving response speed while managing implementation complexity through resource sharing.
3Measurement precision
If comprehensive data collection from multiple sources is performed, then analysis accuracy improves, but information processing complexity and time requirements increase
Solution Approach 1:
The patent implements preliminary data processing and filtering mechanisms that prepare and organize data from multiple sources before the actual analysis occurs. This includes data validation, normalization, and pre-processing steps that reduce the complexity of subsequent analysis while maintaining comprehensive data collection, thereby improving accuracy without proportionally increasing processing time.
Data Source
AI summary
Embodiments may be associated with a network status insight system implemented via a back-end application computer server. A network provider data store may contain electronic records, each electronic record representing a network provider of an enterprise. An enterprise data store may contain electronic records, each electronic record representing a remote analysis entity of the enterprise (e.g., a remote employee or worker). The computer server may receive, from the enterprise data store, information about analysis entities of the enterprise and, from the network provider data store, information about networks used by the enterprise. The computer may also receive, from a third-party outage detector platform information about outages associated with the enterprise (e.g., network outages and/or power outages). A network status algorithm may then be applied to correlate the received information to generate enterprise network status results (e.g., for display on an insight dashboard and/or a risk assessment prediction for the enterprise).