Pig Behavior Monitoring via Acceleration Analysis
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Solution Overview
Problem
Traditional methods for monitoring abnormal behavior in live pigs during feeding rely heavily on experience and are inefficient, making it difficult to detect abnormal behaviors in a timely manner, which can lead to undetected health issues or safety risks.
Innovation Solution
An intelligent method and system that acquires instantaneous acceleration data from pigs, calculates variations, generates sampling characteristic values, sets thresholds based on historical data, and sends alarm signals when abnormal behavior is detected, utilizing a neural network for accurate judgment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional experience-based monitoring methods are used, then the system is simple to operate, but the detection precision and timeliness of abnormal behavior are insufficient
Solution Approach 1:
The patent replaces traditional experience-based manual monitoring with an automated electronic monitoring system that uses acceleration sensors to detect pig behavior. The system substitutes human judgment with objective sensor data and algorithmic analysis, significantly improving detection precision while automating the monitoring process.
Solution Approach 2:
The system performs self-monitoring and self-diagnosis by automatically collecting acceleration data, processing it through algorithms, and generating alerts without requiring continuous human intervention. The automated analysis and alerting mechanisms enable the system to serve itself, reducing operational complexity despite the advanced technology involved.
2Productivity
If traditional monitoring methods are used, then the device complexity is low, but the productivity and timeliness of abnormal behavior detection are insufficient
Solution Approach 1:
The patent replaces manual monitoring processes with automated sensor-based detection systems. Acceleration sensors continuously monitor pig movements, and embedded processors automatically analyze the data to detect abnormal behaviors, dramatically improving detection efficiency and productivity compared to traditional methods.
Solution Approach 2:
The monitoring system operates continuously without interruption, collecting acceleration data at all times and processing it through the embedded algorithm. This continuous monitoring ensures that abnormal behaviors are detected immediately upon occurrence, maximizing detection efficiency and eliminating gaps in surveillance.
3Reliability
If experience-based monitoring is used, then the ease of operation is high, but the reliability of abnormal behavior detection is insufficient
Solution Approach 1:
The patent replaces subjective human experience with objective sensor measurements and standardized algorithms. The acceleration sensors provide reliable, quantifiable data about pig behavior, and the embedded processing algorithms consistently apply detection criteria, eliminating the variability and unreliability of human judgment while maintaining ease of operation through automated processes.
Solution Approach 2:
The system incorporates feedback mechanisms where detection results are immediately communicated through alerts and notifications. When abnormal behaviors are detected, the system provides real-time feedback to farmers, enabling timely responses. This feedback loop enhances detection reliability by ensuring that detected abnormalities are actually addressed, while the automated nature maintains operational simplicity.
Data Source
AI summary
The disclosure provides an intelligent method and system for monitoring pig behavior abnormality. The method comprises: acquiring an instantaneous acceleration of a pig; calculating an instantaneous acceleration variation according to the instantaneous acceleration; calculating a sampling characteristic value according to the instantaneous acceleration and the instantaneous acceleration variation; calculating a threshold according to historical data; drawing a box diagram according to the sampling characteristic value and the threshold; judging whether the sampling characteristic value exceeds the threshold according to the box diagram; if not, reacquiring the instantaneous acceleration of the pig and calculate the instantaneous acceleration variation; and if so, sending an alarm signal. An alarm signal is sent out after an abnormal behavior is detected by comparing the sampling characteristic value and the threshold, so that the abnormal behavior of the pig can be found in time, and the feeding safety is improved.