基于陀螺仪三轴角速度信号的牛只姿态识别数据集

本数据集利用植入式牛瘤胃胶囊（IOT设备）采集的高频三轴角速度信号，实现对肉牛姿态的精准识别与行为量化。该算法模块深度集成于现有的5G智慧育牛监测体系中，通过对原始生理数据流中姿态三轴数据（x/y/z）的实时解析，结合肉牛运动学特征模型，将非结构化的传感器信号转化为结构化的行为状态数据。通过高精度的姿态解算，为疫病早期防控、应激状态监管及异常行为分析提供无可替代的数据支撑，推动牧场管理从“群体粗放”向“个体精准”转型。

This dataset utilizes high-frequency three-axis angular velocity signals collected by implantable bovine rumen capsules (IoT devices) to achieve accurate recognition and behavioral quantification of beef cattle postures. This algorithm module is deeply integrated into the existing 5G intelligent cattle breeding monitoring system. Through real-time analysis of the three-axis posture data (x/y/z) in the original physiological data stream, combined with the kinematic characteristic model of beef cattle, it converts unstructured sensor signals into structured behavioral state data. Through high-precision attitude solution, it provides irreplaceable data support for early epidemic prevention and control, stress state monitoring and abnormal behavior analysis, promoting the transformation of pasture management from "extensive group-based management" to "precision individual-based management".

搜集汇总

背景与挑战

背景概述

该数据集通过植入式物联网设备采集牛只的高频三轴角速度时序信号，利用算法模型将原始传感器数据转化为结构化的姿态与行为状态信息，旨在实现肉牛姿态的精准识别与行为量化。它主要应用于畜牧业中的精准牧场管理，为疫病早期防控、应激监管和异常行为分析提供数据支撑，推动养殖管理向个体化、精细化转型。