Activity Swath Width Detection Using Fourier Spatial Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional agricultural analytic tools fail to accurately calculate swath width based on automatically collected data, leading to inefficiencies and errors in agronomic calculations due to reliance on user-entered values and geometric methods that are prone to noise and incorrect assumptions.
Innovation Solution
A system utilizing a data collection device coupled to farming machinery to collect and geo-tag data points, which are then analyzed using a Fourier transform to determine the effective coverage width, providing a noise-resistant and accurate method for generating agronomic metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional geometric methods are used to calculate swath width, then the calculation process is simple, but the measurement precision is low due to noise and incorrect assumptions
Solution Approach 1:
The patent replaces conventional geometric calculation methods with signal processing techniques (Fourier transform) to determine swath width. Instead of using geometric assumptions and manual calculations, the system processes spatial data points through spectral analysis to identify the dominant frequency corresponding to the implement width, thereby substituting mechanical/geometric methods with a more robust mathematical approach that resists noise and eliminates incorrect assumptions about driving patterns
Solution Approach 2:
The patent introduces an intermediary processing step involving Fourier transform analysis between data collection and swath width determination. This intermediary technique acts as a mediator that converts spatial data into frequency domain information, allowing the system to extract the swath width signal while filtering out noise and variations in driving behavior, thus bridging the gap between raw data and accurate measurement
2Reliability
If user-entered swath width values are used, then data collection is simple, but the reliability is low due to user error and lack of accuracy
Solution Approach 1:
The patent enables the system to automatically determine swath width without user input by processing spatial data collected from the implement's operation. The system self-calibrates and self-measures by analyzing the pattern of data points generated during field operations, eliminating the need for users to manually enter swath width values and thereby improving reliability through objective, data-driven measurement rather than subjective user input
Solution Approach 2:
The patent substitutes manual user input with automated signal processing. Instead of relying on users to enter swath width values, the system automatically extracts this information through Fourier transform analysis of spatial data, replacing the manual data entry mechanism with an automated computational approach that continuously and accurately determines swath width based on actual operating conditions
3Measurement precision
If Fourier transform analysis is used to determine swath width, then measurement precision is improved and noise resistance is increased, but the extent of automation and computational complexity increases
Solution Approach 1:
The patent employs Fourier transform analysis to replace conventional swath width measurement approaches. By converting spatial data into the frequency domain, the system can identify the dominant frequency corresponding to the implement width, providing a robust method that automatically determines swath width with high precision while resisting the effects of noise and variations in driving behavior
Solution Approach 2:
The patent transforms the problem from spatial domain to frequency domain by applying Fourier transform. This parameter change allows the system to analyze the data in terms of frequencies rather than distances, making the swath width determination more robust to noise and independent of specific driving patterns, thereby improving measurement precision through a fundamental change in the analytical parameter space
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
This approach enables the automatic generation of accurate agronomic metrics, such as coverage width, improving efficiency and reducing errors by analyzing spatial data points with Fourier analysis, thus providing reliable analytical insights for farmers.
Implementation Method 1
a discrete Fourier transform of the distribution is calculated to determine a set of frequencies associated with identified peaks in the identified peaks
Data Source
Figure 1~2
Figure 3
Figure 4
AI summary
Embodiments of the present disclosure provide for tracking of collected machine or agronomic worked data to provide detailed analytical output. In various embodiments, a plurality of data points associated with a course of traversal within a collection area is obtained. Each point of the plurality of data points corresponds to a location within the collection area and includes a corresponding set of spatial coordinates. A distribution is generated based on the spatial coordinates. The distribution includes an identified set of occurrences associated with one of the spatial coordinates of the set of spatial coordinates. The distribution is input into a Fourier transform to determine a set of frequencies associated with identified peaks. An effective coverage width, which is the distance corresponding to a peak in the Fourier transform, is determined based on the set of frequencies associated with the identified peaks.