Grow Pod Distributed Control for Hot-Swappable Module Scaling
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Solution Overview
Problem
Current crop growth technologies face challenges in efficiently managing and optimizing the control of environmental conditions in assembly line grow pods, leading to high processing burdens and inefficiencies, particularly when scaling up or down, and requiring frequent maintenance and asset reconfiguration.
Innovation Solution
A distributed control system comprising a master controller and hardware controller devices with a plug-in network interface, allowing for modular control and distribution of tasks among various components, enabling efficient use of assets and minimizing downtime through hot-swappable control modules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a centralized computing system is used to control all environmental conditions and monitor all plants, then comprehensive control capability is achieved, but processing burden increases and system reliability decreases
Solution Approach 1:
The patent divides the centralized computing system into multiple distributed control nodes, each responsible for specific zones or functions within the grow pod. This segmentation reduces the processing burden on any single node and eliminates single points of failure, thereby improving both control capability and system reliability.
Solution Approach 2:
The patent introduces a hierarchical control architecture that adds a spatial dimension to the control system, with master controllers at higher levels and subordinate control devices at lower levels. This dimensional restructuring distributes computational tasks across multiple levels, reducing processing burden while maintaining comprehensive control.
2Adaptability or versatility
If a centralized computing system is used to manage all control tasks, then unified control is achieved, but processing load increases and response time decreases
Solution Approach 1:
The patent segments the control tasks into discrete functions distributed across multiple control nodes. Each node handles specific tasks locally, reducing the processing load on any single system and improving overall response time while maintaining coordinated control through inter-node communication.
Solution Approach 2:
The patent implements partial action by allowing individual control nodes to autonomously handle routine control tasks without requiring centralized processing for every decision. This distributes the processing load and improves response time for time-critical operations.
3Productivity
If the computing system is designed for a specific grow pod size, then optimization for that size is achieved, but adaptability to different sizes decreases
Solution Approach 1:
The patent designs control nodes with universal functionality that can be configured for different grow pod sizes and types. Each node can adapt its operational parameters and control strategies based on the specific configuration, allowing the same hardware platform to optimize performance across varying scales without requiring complete redesign.
Solution Approach 2:
The patent implements dynamic configurability in the control system, where nodes can dynamically adjust their operational characteristics based on the actual grow pod configuration. This allows the system to maintain optimization for the specific size and layout while retaining adaptability to different configurations through runtime parameter adjustment.
4Stability of the object's composition
If control hardware is fixed and integrated, then system stability is achieved, but ease of repair and maintenance decreases
Solution Approach 1:
The patent segments the control hardware into modular, independently replaceable units. Each control node is designed as a discrete module that can be removed and replaced without affecting the stability of the overall system, as long as the replacement module maintains the required communication and control interfaces.
Solution Approach 2:
The patent extracts the control functionality from fixed integrated circuits and implements it in removable hardware modules or programmable devices. This allows the control logic to be maintained and updated independently while preserving system stability through consistent interface protocols, and significantly improves ease of repair by enabling quick module replacement.
5Reliability
If the computing system requires complete reset for upgrades, then system integrity is maintained, but downtime increases and productivity decreases
Solution Approach 1:
The patent segments the control software and configuration into modular components that can be updated independently at each control node. This allows upgrades to be applied incrementally across the distributed system without requiring a complete shutdown, maintaining system integrity through controlled updates while minimizing downtime.
Solution Approach 2:
The patent implements preliminary action by allowing control nodes to prepare for upgrades during low-demand periods or in a staged manner. Nodes can be updated sequentially rather than simultaneously, with each node maintaining operational integrity before and during the transition, thereby preserving system integrity while avoiding complete system downtime.
Data Source
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AI summary
A distributed control system for use in an assembly line grow pod includes a master controller and a hardware controller device. The master controller includes a first processor and a first memory for storing a first set of instructions that dictates plant growing operations and a second set of instructions that dictates a plurality of distributed control functions. The hardware controller device is coupled to the master controller via a plug-in network interface. The hardware controller device includes a second processor and a second memory for storing a third set of instructions that dictate a selected control function of the plurality of distributed control functions. Upon the plug-in connection, the master controller identifies an address of the hardware controller device and sends a set of parameters defining a plurality of tasks relating to the selected control function.