Connected Planter Data Playthrough During Sync Delays
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Agricultural implement systems face challenges in maintaining accurate and timely data synchronization during real-time operations, leading to potential double planting and operational disruptions due to data delays or unavailability.
Innovation Solution
A computerized method and system that interpolates anticipated agricultural data when one implement becomes unavailable, using a non-transitory computer readable medium to provide sharing playthrough data for continued operation, incorporating a navigation system, transmitter, sensors, and a processor to handle agricultural tasks and data, and employing high-speed communication protocols like Ethernet for efficient data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time data sharing is implemented between multiple agricultural implements, then operational coordination and planting accuracy are improved, but data transmission delays and communication failures occur
Solution Approach 1:
The system performs preliminary actions by predicting planting data for future time periods before actual planting occurs. The prediction engine generates anticipated planting information in advance, allowing the system to prepare for potential data delays and maintain operational continuity without waiting for real-time data synchronization.
Solution Approach 2:
The prediction engine acts as an intermediary between actual planting operations and real-time data sharing. When communication delays occur between agricultural implements, the prediction engine provides intermediate predicted data that bridges the gap, allowing operations to continue smoothly until actual data becomes available again.
2Reliability
If multiple agricultural implements share planting data in real-time, then double planting is prevented, but system complexity and communication requirements increase
Solution Approach 1:
Each agricultural implement equipped with the prediction engine becomes self-sufficient in generating its own predicted planting data when needed. The system serves itself by autonomously predicting planting information without requiring constant external validation or complex centralized coordination, reducing overall system complexity while maintaining reliability.
Solution Approach 2:
The system performs preliminary actions by predicting planting data for future time periods before actual planting occurs. The prediction engine generates anticipated planting information in advance, allowing the system to prepare for potential data delays and maintain operational continuity without waiting for real-time data synchronization.
3Productivity
If predictive data is used to maintain operations during data unavailability, then operational efficiency is maintained, but data synchronization accuracy may be compromised
Solution Approach 1:
The system dynamically adjusts between using actual real-time planting data and predicted planting data based on communication availability. When data sharing is successful, the system uses actual data for maximum accuracy. When communication fails, it seamlessly transitions to using predicted data to maintain operational efficiency, then reconciles with actual data when connectivity is restored.
Solution Approach 2:
The system implements feedback mechanisms to continuously monitor communication status between agricultural implements. When data synchronization succeeds, the system receives feedback confirming actual planting locations and adjusts predictions accordingly. When communication fails, the feedback loop temporarily relies on predicted data until connectivity is restored, at which point actual data feedback recalibrates the prediction model.
Data Source
AI summary
Continued and precise operation of an agricultural implement exists even where a subsystem, such as a GPS receiver, wireless communicator, a sensor, or the like, fails, falters, or is otherwise unusable. Data is continually tracked to the extent possible during failure or faltering and is temporarily stored. To continue operations during periods of unavailability, a representation of planted ground is anticipated by other agricultural implements and/or calculated with agricultural data from other agricultural implements. Normal operations then continue until data sync can catch back up to real-time.