Livestock Weight Sorting System with Dynamic Threshold Adjustment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Livestock farms face challenges in determining the optimal weight thresholds for sorting livestock efficiently and accurately, which affects market selection and feeding requirements, due to lack of comprehensive data and external market considerations, leading to increased costs and labor.
Innovation Solution
A system utilizing sensors and a server to collect and adjust weight thresholds based on market parameters, enabling precise sorting and data sharing across farms, potentially using blockchain technology for data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual determination of weight thresholds is used for sorting livestock, then flexibility in adjusting sorting criteria is maintained, but labor costs and time consumption increase significantly
Solution Approach 1:
The system enables automatic determination of weight thresholds through sensors and data processing, eliminating the need for manual intervention. The apparatus autonomously collects livestock weight data, processes it according to market requirements, and adjusts sorting thresholds without human labor, thus resolving the contradiction between operational flexibility and time consumption.
Solution Approach 2:
The patent replaces manual mechanical determination with an automated electronic system comprising sensors, processors, and control apparatus. This substitution transforms the manual process into an automated one that rapidly determines optimal weight thresholds based on real-time data and market parameters, significantly reducing time while maintaining flexibility.
2Measurement precision
If comprehensive data collection from multiple sources is implemented to determine optimal sorting thresholds, then sorting accuracy and market compliance improve, but system complexity and data processing requirements increase
Solution Approach 1:
The system divides data collection and processing into distinct functional modules: sensors for data acquisition, processors for analysis, and control apparatus for threshold determination. This segmentation allows comprehensive data collection from multiple sources while managing system complexity through modular architecture, where each component handles specific tasks independently.
Solution Approach 2:
The apparatus is designed with multi-functional capabilities that integrate various data sources (sensors, market data, historical records) into a unified sorting system. This universal design enables the system to handle diverse data types and sorting requirements through a single integrated platform, improving sorting accuracy without proportionally increasing complexity.
3Productivity
If livestock are sorted into separate groups based on weight thresholds, then feeding efficiency and market compliance improve, but the difficulty and cost of determining appropriate thresholds increase
Solution Approach 1:
The system implements feedback mechanisms where sensor data from sorted livestock groups is continuously monitored and fed back to the control apparatus. This feedback loop enables automatic adjustment of weight thresholds based on actual feeding outcomes and market requirements, improving feeding efficiency while simplifying threshold determination through data-driven optimization rather than complex manual analysis.
Solution Approach 2:
The apparatus performs preliminary data collection and analysis to pre-determine optimal weight thresholds before sorting operations begin. By preparing sorting criteria in advance based on market requirements and historical data, the system enables efficient sorting and feeding operations without requiring complex real-time threshold determination during the sorting process.
Data Source
AI summary
A system for managing objects is provided. The system comprises a data collection gateway and a plurality of apparatus. Each of the plurality of apparatus obtains parameters relating to objects in a farm from a server through the data collection gateway. The parameters include a reference threshold weight of the objects. Each of the plurality of apparatus collects weights of the objects through sensors. Also, each of the plurality of apparatus adjusts the reference threshold weight based on the obtained parameters to generate an adjusted threshold weight. Further, each of the plurality of apparatus sorts the objects to different areas in the farm based on the adjusted threshold weight and the collected weights.