Nondestructive Data Pipeline for Agricultural Convergence
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Solution Overview
Problem
The increasing heterogeneity of devices in agriculture leads to challenges in reliable and accurate data exchange, resulting in potential errors, latencies, or delays in agricultural actions.
Innovation Solution
A nondestructive data pipeline system that tags raw data with identifiers for efficient re-translation in case of errors, and uses APIs to collect and process data from various sources, enabling convergence-based insights and actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is translated from heterogeneous device formats, then data compatibility is improved, but translation errors and latencies occur
Solution Approach 1:
The system performs preliminary actions by buffering raw data from heterogeneous devices before translation occurs. This allows the system to maintain original data formats while preparing standardized translation layers, preventing translation errors before they affect downstream processes and enabling reliable data exchange across diverse agricultural devices
Solution Approach 2:
The patent introduces an intermediary translation layer that sits between heterogeneous device data formats and the standardized data model. This intermediary layer handles format conversion, validation, and error correction, ensuring reliable translation from diverse sensor formats to a unified data representation without introducing latencies
2Reliability
If raw data is buffered for re-translation, then error correction capability is improved, but data storage requirements increase
Solution Approach 1:
The system segments data into discrete records with unique identifiers before buffering, allowing selective re-translation of only erroneous portions rather than entire datasets. This segmentation enables efficient error correction while minimizing storage requirements by processing data in manageable units
Solution Approach 2:
The patent implements a mechanism that discards corrupted or erroneous data portions after identification, then recovers by re-translating only the affected segments from the buffered raw data. This approach maintains reliability through error correction while optimizing storage by not retaining entire datasets indefinitely
3Quantity of substance
If data is collected from multiple heterogeneous sources, then data completeness is improved, but system complexity increases
Solution Approach 1:
The system implements a universal data collection framework that handles multiple heterogeneous sources through a single standardized interface. The same buffering and translation mechanisms work across diverse agricultural devices (sensors, drones, satellites), maintaining data completeness from multiple sources while reducing system complexity through abstraction
Solution Approach 2:
The patent introduces an intermediary data collection layer that统一 handles data from multiple heterogeneous sources. This layer abstracts the complexity of different device protocols and formats, presenting a consistent data model to the rest of the system while maintaining completeness by collecting data from all available sources
Data Source
AI summary
A nondestructive data pipeline to execute convergence based agricultural actions is provided. A system receives, for storage in a buffer, raw data from a plurality of data feeds that are indicative of performance of agriculture on a farm. The system tags, prior to execution of a data translation process, the raw data with a plurality of identifiers. The system executes, with the raw data maintained in the buffer, the data translation process to map the raw data from a first one or more shapes into a second shape to generate a normalized data set. The system determines, responsive to detection of the error, an identifier tagged to a portion of the raw data in the buffer that corresponds to the portion of the normalized data set with the error. The system updates the normalized data set to remove the error.