Cloud OS Instruction Mapping for Remote Device Cluster Control
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Solution Overview
Problem
Autonomous systems face challenges in ensuring consistent results and controlling complex subsystems across deployments, particularly in automated manufacturing processes like food production, where individual devices need to be coordinated to achieve desired outcomes.
Innovation Solution
A cloud-based operating system that uses a cloud server to generate instructions for a local server, which distributes specific operations to remote devices, enabling coordinated execution of tasks across a network of devices, including robotic systems and IoT devices, to perform complex operations like food preparation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a cloud-based operating system with distributed instruction generation and device-specific operation mapping is implemented, then adaptability and versatility of the automated system improve, but device complexity and system architecture complexity increase
Solution Approach 1:
The system segments the automated manufacturing system into multiple independent device clusters, each with its own local server and set of remote devices. The cloud-based operating system divides production recipes into device-specific operations that can be independently mapped and executed by different clusters, enabling flexible reconfiguration without redesigning the entire system.
Solution Approach 2:
The cloud-based operating system implements a universal data model and operation mapping framework that can accommodate diverse device types and configurations. The system uses standardized command structures and device cluster definitions that allow different device clusters to perform different functions while being controlled through a common interface, enhancing versatility without proportionally increasing complexity.
2Manufacturing precision
If individual device control and coordination are implemented for complex subsystems, then manufacturing precision and reliability improve, but device complexity and control difficulty increase
Solution Approach 1:
The local server acts as an intermediary between the cloud-based operating system and the remote devices within a device cluster. It receives high-level commands from the cloud system, translates them into device-specific operations using the operation mapping, and coordinates execution across multiple remote devices. This intermediary layer simplifies control while maintaining precise coordination of complex subsystems.
Solution Approach 2:
The system implements feedback mechanisms where execution results and device status information are reported back to the cloud-based operating system. This enables real-time monitoring and adjustment of device operations, ensuring manufacturing precision while allowing the system to adapt to actual device performance and conditions.
Data Source
AI summary
In one embodiment, the present disclosure includes a cloud computer system for controlling a plurality of remote devices comprising a cloud server including a cloud based operating system comprising a data model stored in a computer memory. The data model includes commands that may be performed by a plurality of remote devices in a remote system and, for each remote device, one or more operations for triggering processes executed by the remote device. The cloud based operating system generates a set of instructions from the plurality of commands and corresponding operations to control a portion of the remote devices to perform a task.