C-GRC Controller Automating Agricultural Compliance Monitoring
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Solution Overview
Problem
Agricultural safety control systems face challenges in monitoring and demonstrating compliance across various segments of an agricultural operation, especially as technology reduces human interaction, leading to a need for automated data collection and traceability of agricultural products.
Innovation Solution
A Centralized Governance Regulatory Compliance (C-GRC) controller is introduced to dynamically monitor and collate data, automate compliance plan governance, and maintain traceability through cryptographic key exchanges and Radio Frequency (RF) tags, ensuring compliance with agricultural safety requirements across the agricultural cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data collection by personnel is used to verify compliance, then compliance monitoring can be performed, but labor intensity and operational complexity increase
Solution Approach 1:
The system enables automated self-monitoring of compliance through sensors, RFID tags, and blockchain technology. Data is automatically collected, verified, and recorded without human intervention, allowing the system to serve itself in terms of compliance monitoring while reducing operational complexity
Solution Approach 2:
Manual mechanical data collection processes are replaced with automated electronic systems including sensors, RFID readers, and blockchain smart contracts. This substitution eliminates the need for personnel to manually verify compliance while maintaining or enhancing monitoring reliability
2Productivity
If technology streamlines agricultural operations to reduce human interaction, then productivity increases, but compliance traceability and data collection become more challenging
Solution Approach 1:
The system implements continuous feedback loops where sensors automatically monitor operational parameters, blockchain records all transactions and compliance data immutably, and the system provides real-time verification. This ensures that as automation increases, compliance information is systematically captured and traceable without loss
Solution Approach 2:
Blockchain technology serves as an intermediary layer between automated operational systems and compliance verification requirements. It automatically captures, stores, and verifies compliance data generated by streamlined operations, preventing information loss while maintaining high productivity
3Measurement precision
If automated monitoring systems are implemented across all agricultural segments, then compliance accuracy improves, but system complexity and implementation cost increase
Solution Approach 1:
The compliance monitoring system is divided into modular segments corresponding to different agricultural operations (planting, growth, harvesting, storage). Each segment has dedicated sensors and blockchain smart contracts that independently monitor specific compliance requirements, improving measurement precision while managing complexity through modular design
Solution Approach 2:
The blockchain infrastructure provides universal functionality across all agricultural segments, serving as a common platform for data recording, verification, and traceability. This multi-functional approach allows different sensors and monitoring devices to integrate with a single standardized system, reducing overall complexity while maintaining high compliance measurement accuracy
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The C-GRC controller provides a granular record of agricultural activities, verifies the chain of custody, and ensures compliance with safety rules, enhancing the integrity and health monitoring of agricultural products from seed management to shipment, thereby improving agricultural safety and quality control.
Implementation Method 1
maintain traceability through cryptographic key exchanges and Radio Frequency (RF) tags
Data Source
AI summary
The present disclosure describes techniques that facilitate a Governance Regulatory Compliance (C-GRC) controller that is configured to dynamically monitor and collate data associated with an agricultural operation for demonstrating compliance with an agricultural compliance plan. The C-GRC controller may act as a centralized server that dynamically monitors the cycle of agricultural activities for an agricultural product and in doing so, automates the governance of an agricultural compliance plan across a plurality of entities that are each responsible for one or more agricultural activities. The C-GRC controller may detect independent interactions conducted between a complying entity and a participating entity. These interactions may be intended to gather information relating to compliance of a pending task. In doing so, the C-GRC controller may update an agricultural compliance plan accordingly. The C-GRC controller may dynamically advance progress through an agricultural compliance plan or dynamically regress progress based on a complying entity retracting compliance.