Cloud computer system for controlling clusters of remote devices
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Solution Overview
Problem
Autonomous systems face challenges in ensuring consistent results and control across deployments due to complex subsystems and the need for individual or collective control of these subsystems, particularly in automated manufacturing processes like food production.
Innovation Solution
A cloud-based operating system that uses a cloud server to generate instructions for a local server, which distributes specific instructions to remote devices for executing predefined processes, enabling coordinated task execution across a network of devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a cloud-based operating system with centralized control is implemented, then control consistency and task execution reliability are improved, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent introduces a cloud-based operating system as an intermediary layer between the user and the distributed remote devices. This mediator generates standardized instructions from high-level commands, translating complex device-specific operations into uniform control signals that can be distributed across multiple devices, thereby ensuring control consistency without requiring direct complex point-to-point control logic.
Solution Approach 2:
The cloud-based operating system serves multiple functions: it stores device information and capabilities, generates control instructions, manages device clusters, and coordinates task execution. By consolidating these diverse functions into a single universal platform, the system achieves reliable centralized control while avoiding the complexity of implementing separate control mechanisms for each function.
2Adaptability or versatility
If multiple remote devices are coordinated to perform tasks, then system versatility and automation capability are improved, but control difficulty and coordination overhead increase
Solution Approach 1:
The patent segments the coordination task into distinct layers: the cloud-based operating system handles high-level task planning and instruction generation, while individual remote devices execute specific device-specific processes. This segmentation allows the system to coordinate multiple devices for versatile automation without requiring each device to understand the entire system state, reducing coordination overhead through clear division of responsibilities.
Solution Approach 2:
The cloud-based operating system stores information about multiple remote devices and their capabilities, creating a virtual model or copy of the physical device cluster. This digital twin allows the system to simulate and plan coordinated tasks before execution, enabling versatile automation scenarios to be designed and tested virtually, thereby reducing the complexity of real-time coordination.
3Ease of operation
If device-specific processes are executed at remote devices, then operational flexibility and device utilization are improved, but control precision and standardization decrease
Solution Approach 1:
The patent enables each remote device to execute its own device-specific processes locally, utilizing its unique capabilities and characteristics. This local quality approach allows devices to operate at full capacity with optimal performance for their specific functions while the cloud-based operating system ensures that these diverse local operations contribute to a standardized, coordinated task outcome.
Solution Approach 2:
The cloud-based operating system dynamically adjusts control parameters and instruction details based on the specific capabilities and states of remote devices. By modifying control parameters rather than changing the fundamental control architecture, the system maintains standardization and precision while accommodating device-specific variations and maximizing each device's utilization.
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.