Feed Bin Measurement Error Correction via Environmental Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current feed management technologies face issues such as frequent breakdowns of load cell methods, requirement of extensive facilities for laser methods, and inaccuracy due to scattered laser signals, necessitating a more reliable and precise method for measuring feed remaining amounts and spoilage in farmhouses.
Innovation Solution
A feed management service provision device that includes a measurement device inside the feed bin, a communication unit, an error correction model training unit, an error correction unit, a feed remaining amount calculation unit, and a feed management service provision unit, which uses error-corrected feed measurement distance values and environment data to accurately determine the remaining feed amount and spoilage degree, and provides user notifications and recommendations for replenishment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the load cell method is used to measure feed remaining amount, then the measurement can be obtained, but frequent breakdowns occur due to excessive application of load
Solution Approach 1:
The patent replaces the mechanical load cell system with an optical measurement system. A camera captures images of the feed bin interior, and image processing algorithms calculate the feed remaining amount based on the visible space and feed level in the images. This substitution eliminates mechanical contact and load application, thereby preventing breakdowns while maintaining measurement capability.
2Measurement precision
If the laser method is used to measure feed distance, then non-contact measurement is achieved, but various facilities are required and periodic horizontal level check is needed
Solution Approach 1:
The patent uses a camera to capture visual images of the feed bin interior, creating a visual copy or representation of the feed level and bin contents. Image processing algorithms then analyze these visual copies to determine feed distance and remaining amount. This approach replaces complex laser facilities with a simpler camera-based system that captures sufficient information through imaging.
3Measurement precision
If the laser method is used for feed measurement, then non-contact measurement is possible, but inaccurate information is obtained when the laser scatters
Solution Approach 1:
The patent replaces the laser optical system with a camera-based visual system. Instead of using laser beams that can scatter and produce inaccurate readings, the system uses broad-spectrum lighting captured by the camera. Image processing algorithms analyze the visual information to determine feed level, which is more robust to scattering effects and provides reliable measurements in various lighting conditions.
4Measurement precision
If error correction model training is performed using data from multiple feed bins, then prediction accuracy of remaining feed amount is enhanced, but data processing complexity increases
Solution Approach 1:
The patent trains error correction models using aggregated data from multiple feed bins to create a universal model that can accurately predict remaining feed amounts across different bin types, locations, and conditions. This universal model reduces the need for bin-specific calibration and improves overall prediction accuracy. The system manages data processing complexity through standardized data collection protocols and efficient training procedures.
Data Source
AI summary
Disclosed are a feed management service provision device and method. A feed management service provision device for providing a feed management service in connection with a measurement device installed inside a feed bin in a farmhouse, according to one embodiment of the present invention, comprises: a communication unit receiving, from the measurement device, a feed distance measurement value representing the distance between the measurement device and the feed, and environment data on the environment inside the feed bin; an error correction model training unit for training an error correction model using a plurality of pieces of training data collected from a plurality of feed bins, including a plurality of feed distance measurement values for training, a plurality of pieces of environment data for training, and a plurality of actual feed distance values corresponding to the plurality of feed distance measurement values for training; an error correction unit for calculating an error-corrected feed distance measurement value using the error correction model that has been trained and the feed distance measurement values and the environment data received from the communication unit; a residual feed amount calculation unit for calculating the residual amount of feed on the basis of the error-corrected feed distance measurement value and feed bin-related information; and a feed management service provision unit for providing a feed management service to a user device on the basis of the residual amount of feed.