Decentralized Farm Control With Cloud Backup and ML Automation
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Solution Overview
Problem
Conventional farm control systems face limitations such as finite sensor and actuator capacity, scalability issues, high costs, single-point failures, and lack of machine learning integration, leading to inefficiencies and potential crop loss.
Innovation Solution
A decentralized farming control system with a software backbone that supports virtually unlimited nodes, machine learning capabilities, and redundancy, allowing for scalable and flexible control with cloud-based backup to prevent failures and enhance automation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional PLC-based control systems are used, then basic farm operations can be controlled, but the system lacks scalability and has limited sensor/actuator capacity
Solution Approach 1:
The system divides the farm into multiple zones with independent controllers, each managing specific sensors and actuators. This segmentation allows the system to scale by adding more zone controllers without overwhelming a single central PLC, thereby increasing sensor/actuator capacity while maintaining manageable system complexity.
Solution Approach 2:
The patent introduces a hierarchical control architecture with multiple levels (field devices, zone controllers, central management system). This dimensional expansion from flat PLC architecture to multi-layered structure enables the system to accommodate numerous sensors and actuators by distributing processing across layers, resolving the contradiction between capacity and complexity.
2Productivity
If PLCs with limited processing capabilities are used, then basic control functions are achieved, but bottlenecks occur in processing input and outputting commands
Solution Approach 1:
Processing tasks are segmented and distributed across multiple controllers and processors in the hierarchical architecture. Field devices handle local real-time control, zone controllers manage regional processing, and the central system handles high-level decision-making. This distribution eliminates single-point bottlenecks and improves overall processing speed while reducing control response time.
Solution Approach 2:
The patent introduces communication protocols and intermediate controllers that act as mediators between field devices and the central system. These intermediaries buffer and pre-process data locally before transmitting to higher levels, reducing the processing burden on central PLCs and improving both processing speed and response time.
3Reliability
If conventional control systems with single-point failure are used, then system simplicity is maintained, but reliability decreases due to potential crop loss
Solution Approach 1:
The hierarchical control architecture incorporates redundant controllers at each level. If a field controller or zone controller fails, backup controllers automatically take over, preventing system-wide failure. This beforehand cushioning through redundancy significantly improves reliability while the modular structure keeps the added complexity manageable.
Solution Approach 2:
The system dynamically changes operational parameters and control strategies based on real-time conditions and controller availability. When controllers fail, the system reconfigures control parameters and redistributes tasks to remaining functional controllers, maintaining system reliability without requiring complete system redesign.
4Adaptability or versatility
If scalable solutions are implemented with unlimited modules, then adaptability increases, but system complexity and cost increase
Solution Approach 1:
The patent employs universal, standardized controllers and communication protocols that can be deployed across all farm zones. These multi-functional modules can handle various sensor types and actuator configurations, allowing the system to scale by simply adding more identical units rather than requiring specialized expensive components for each zone, thereby reducing overall system cost.
Solution Approach 2:
The hierarchical control architecture uses replicated controller units at different levels that follow standardized designs. Instead of designing unique complex controllers for each farm section, the system copies proven controller templates and configures them for specific zones, reducing development and manufacturing costs while maintaining scalability and adaptability.
Data Source
AI summary
A farming control system for monitoring and controlling one or more contained farms is described herein. The farming control system includes a local system having a plurality of modules to obtain crop data and perform farming operations on crops. The modules transmit the crop data to and receive the farming operations from a local controller, or a cloud controller when the local controller fails. The local system and the cloud system may use machine learning based on the crop data to determine the farming operations to be performed.