AI Orchestrator Dynamic Patching for Industrial IoT
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Solution Overview
Problem
Industrial AI orchestration systems face challenges in dynamically updating AI software to align with changes in machine and IoT device capabilities, leading to suboptimal workflow utilization and productivity on the industrial floor.
Innovation Solution
An AI orchestrator program identifies changes in machine and IoT device capabilities, recommends executable functionalities, and installs necessary AI software patches to ensure the AI orchestration software is updated dynamically, aligning with the current capabilities and improving productivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI orchestration software is updated dynamically to align with machine and IoT device capabilities, then productivity and workflow utilization are improved, but system complexity and update management difficulty increase
Solution Approach 1:
The AI orchestrator automatically detects capability changes in machines and IoT devices, identifies required software patches, and installs updates without manual intervention. This self-service mechanism resolves the contradiction by automating the update process, maintaining high productivity while reducing the operational complexity of software management.
Solution Approach 2:
The system continuously monitors capability changes in machines and IoT devices, uses this feedback to determine when software updates are needed, and automatically applies patches. This closed-loop feedback mechanism ensures software remains aligned with device capabilities, improving workflow utilization while simplifying update management through automation.
2Adaptability or versatility
If AI software patches are installed automatically based on capability changes, then adaptability of the system is improved, but risk of errors and system stability issues increases
Solution Approach 1:
The AI orchestrator identifies and prepares software patches in advance based on detected capability changes, validating compatibility before actual installation. This preliminary action ensures that only appropriate patches are applied, enhancing software adaptability while maintaining system stability through pre-validation.
Solution Approach 2:
The system performs self-diagnosis to detect capability changes and automatically selects and applies appropriate software patches. This automated self-service approach improves adaptability by ensuring software matches current device capabilities, while reducing human error and maintaining stability through consistent, rule-based update application.
Data Source
AI summary
According to one embodiment, a method, computer system, and computer program product for managing artificial intelligence (AI) orchestration of machines and internet-of-things (IoT) devices of an industrial floor. The embodiment may include identifying a change in capability of at least one machine and/or IoT device of the industrial floor. The embodiment may include identifying executable functionality resulting from the identified change. The embodiment may include identifying one or more artificial intelligence (AI) software patches to perform the identified executable functionality. The embodiment may include installing the identified one or more AI software patches within the at least one machine and/or IoT device.