Farm Management Error Reporting via Frequency Filtering
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Solution Overview
Problem
Existing farm management systems face challenges in efficiently handling the overwhelming number of error messages generated by automatic devices, leading to critical errors being drowned out in less important messages.
Innovation Solution
A farm management system incorporating a message handling node that receives error messages from automatic devices, generates error reports based on frequency criteria, and sends these reports to user terminals, allowing for flexible filtering and prioritization of error messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If error messages are sent directly from automatic devices to user terminals, then complete information about all errors is provided, but the volume of messages becomes overwhelming and critical errors are drowned out
Solution Approach 1:
The patent introduces an intermediate processing system (server or message handling node) that receives error messages from automatic devices, processes them through rule-based filtering and aggregation, and sends only relevant error reports to user terminals. This intermediary layer prevents information loss while filtering out noise, resolving the contradiction between providing complete information and maintaining ease of operation.
Solution Approach 2:
The system changes the parameters of error message transmission by applying frequency criteria, time windows, and aggregation rules to transform raw error messages into consolidated error reports. This parameter-based processing reduces message volume while preserving critical information, addressing both information completeness and operational ease.
2Reliability
If all error messages are forwarded to user terminals, then no critical errors are missed, but users receive thousands of messages per day making it impossible to identify important issues
Solution Approach 1:
The system extracts only the essential and critical error information from the bulk of error messages by applying filtering rules based on frequency thresholds, error types, and time windows. This extraction process maintains reliability for critical errors while dramatically reducing the quantity of messages sent to users.
Solution Approach 2:
The system performs preliminary filtering, aggregation, and analysis of error messages before they are sent to user terminals. By pre-processing messages according to defined rules and criteria, the system ensures that only relevant errors reach users, maintaining detection reliability while reducing message quantity.
3Ease of operation
If error messages are filtered aggressively to reduce volume, then message volume is manageable, but critical errors may be filtered out along with non-critical ones
Solution Approach 1:
The system applies different filtering criteria and thresholds to different types of error messages, devices, and contexts. Critical errors receive minimal or no filtering, while non-critical errors are aggregated and filtered more aggressively. This localized quality approach ensures manageable message volumes while preserving critical error detection reliability.
Solution Approach 2:
The system uses feedback mechanisms where error message patterns, frequencies, and types inform the filtering rules. By continuously analyzing error patterns and adjusting filtering criteria, the system maintains high reliability for critical errors while achieving manageable message volumes through adaptive filtering.
Data Source
AI summary
A message handling node of a farm management system that receives error messages from a plurality of automatic devices, and generates and sends out error reports to user terminals, where the message handling node applies a rules system prescribing that an error report concerning a particular one of the automatic devices is generated based on fulfillment of a frequency criterion relating to a number of times at which the message handling node receives the error messages from said particular one device within at least one previous period in order to manage a total number of error reports received by each of the user terminals.