IIoT Customization Engine for API Service Adaptation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Industrial Internet of Things (IIoT) systems face challenges in customizing services exposed by fleet assets, as existing APIs do not allow for tailored operations or additional functionality without modifying the assets or software, and there is a need for flexible management of industrial assets across diverse environments.
Innovation Solution
A customization engine deployed in the IIoT cloud processes incoming API requests, allowing asset managers to define service configurations and configuration programs that can preprocess requests, validate data, modify operations, or reject specific API calls, thereby extending the functionality of integrated APIs without altering them.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standard integrated APIs are used for fleet asset management, then system simplicity and ease of operation are maintained, but adaptability and versatility are limited because customization requires modifying assets or software
Solution Approach 1:
The patent introduces a customization engine as an intermediary component between the standard integrated API and the fleet assets. This engine receives API requests, applies service configurations and configuration programs to customize operations, and returns results without modifying the original API or assets. The intermediary layer enables adaptability while preserving system simplicity.
Solution Approach 2:
The system segments the API processing functionality into two independent parts: the standard integrated API that handles core operations, and the customization engine that handles adaptation logic. This segmentation allows each component to remain simple while the combination provides extensive customization capability through configurable service definitions and programs.
2Adaptability or versatility
If existing API frameworks are used without modification, then system stability and reliability are maintained, but adaptability is reduced because tailored operations cannot be implemented
Solution Approach 1:
The customization engine enables self-service configuration where asset managers can define service configurations and configuration programs through a declarative approach. The system automatically processes these configurations to implement tailored operations without requiring manual code changes or complex programming, making the system adaptable while easy to operate.
Solution Approach 2:
Service configurations and configuration programs are defined in advance before runtime operations. This preliminary configuration allows the system to automatically apply appropriate customizations to API requests based on pre-defined rules, eliminating the need for complex real-time decision-making and simplifying operational management while maintaining high adaptability.
3Adaptability or versatility
If service configurations and configuration programs are added to enable customization, then adaptability and versatility improve, but device complexity increases due to additional configuration management requirements
Solution Approach 1:
The customization engine provides universal configuration mechanisms that can handle diverse customization scenarios through a unified framework. Service configurations and configuration programs serve multiple purposes including request preprocessing, validation, modification, and rejection decisions. This multi-functionality reduces the need for separate complex systems for each customization task.
Solution Approach 2:
The system uses template-based configuration programs that can be copied and reused across different service scenarios. Once a configuration program is defined for a particular customization need, it can be replicated and adapted for similar scenarios, reducing the overall complexity of configuration management while maintaining high adaptability across the fleet asset portfolio.
Data Source
AI summary
A system includes at least one hardware processor and a memory storing a plurality of service configurations and a plurality of configuration programs, including a first configuration program, and a first service configuration identifying at least one conditional element and the first configuration program. The system also includes a customization engine configured to receive a REST call from a requesting device, the REST call identifying an IIoT machine, the IIoT machine executing a service exposing a REST-ful API. The customization engine also parses the REST call into a plurality of parameters, compares the parameters to the conditional element(s) and determines that the parameters satisfies the conditional element(s), identifies the first configuration program from the first service configuration, and executes the first configuration program resulting in a second plurality of parameters, constructs an outbound REST call to include the second parameters, and transmits the outbound REST call to the IIoT machine.