IoT Hub Onboarding with Distributed Security Profiles
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Solution Overview
Problem
Existing IoT systems face challenges in customizing configuration settings and security protocols for diverse employee groups within large enterprises, leading to inefficiencies and system delays due to reliance on uniform centralized datasets and large processing overheads.
Innovation Solution
An IoT system that customizes system requirements based on user job descriptions, utilizing a central IoT hub to onboard and manage user devices by assessing conformance with baseline security protocols and performance characteristics, and employing machine learning to optimize data processing and remediation routines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a uniform centralized dataset is used for all IoT nodes, then system management is simplified, but customization of configuration settings and security protocols for different employee groups becomes impossible
Solution Approach 1:
The patent segments the centralized dataset into multiple distributed datasets, each associated with specific employee groups or job functions. Each IoT node is configured to access relevant distributed datasets rather than a single uniform dataset, enabling customization while maintaining manageable system architecture through modular data organization.
Solution Approach 2:
The patent implements local quality by allowing different IoT nodes to access different configuration settings and security protocols based on their specific employee group assignments. Each node receives customized configuration data locally relevant to its function, rather than applying a single uniform configuration across all nodes.
2Reliability
If large datasets containing all error messages and remediation routines are processed, then comprehensive error coverage is achieved, but processing overhead increases and system delays occur
Solution Approach 1:
The patent extracts only the necessary subset of error messages and remediation routines from the complete dataset based on the specific error type and employee group permissions. Instead of processing the entire large dataset, the system selectively retrieves relevant portions, significantly reducing processing overhead while maintaining comprehensive coverage for applicable errors.
Solution Approach 2:
The patent applies partial action by processing only the minimum necessary data subset required to resolve the current error, rather than exhaustively processing all available error data. This selective approach achieves sufficient error coverage for the specific situation without the excessive processing burden of complete dataset analysis.
3Adaptability or versatility
If customized configuration settings and security protocols are implemented for different employee groups, then job-specific requirements are met, but system complexity increases
Solution Approach 1:
The patent implements self-service by enabling IoT nodes to automatically retrieve and apply their own customized configuration settings and security protocols from distributed datasets based on their embedded employee group identifiers. This automated self-configuration process reduces manual configuration management complexity while maintaining job-specific customization capabilities.
Solution Approach 2:
The patent applies preliminary action by pre-organizing configuration settings and security protocols into distributed datasets associated with specific employee groups before deployment. When an IoT node joins the system, it automatically receives its pre-configured settings, eliminating the need for complex real-time configuration management and reducing overall system complexity.
Data Source
AI summary
Apparatus and methods for establishing a user Internet of Things (“IoT”) system is provided. The method may be performed by a central IoT hub run on a user's personal computing device. The method may include detecting user devices in electronic communication with the central IoT hub and onboarding, to the user IoT system, user devices determined to be in conformance with baseline security protocols and performance characteristics. The onboarded user device may be IoT nodes. The method may include monitoring enterprise data to pre-emptively identify and address probable failures of the IoT nodes prior to failure of the IoT nodes. The method may also include addressing known failures for each IoT node on the user IoT system.