首頁 資訊 基于機器人的生豬健康養(yǎng)殖智能監(jiān)控系統(tǒng)設計

基于機器人的生豬健康養(yǎng)殖智能監(jiān)控系統(tǒng)設計

來源:泰然健康網(wǎng) 時間:2024年12月01日 14:59

摘要: 為提高生豬養(yǎng)殖環(huán)境質量和行為識別率,克服規(guī)?;B(yǎng)殖過程中采用人工巡檢生豬異常行為特征和監(jiān)測養(yǎng)殖環(huán)境參數(shù)存在識別效率低、準確性差和勞動強度大等問題,設計一種以軌道式機器人為采集終端的生豬健康養(yǎng)殖智能監(jiān)控系統(tǒng)。系統(tǒng)以FPGA控制器為硬件核心,結合豬只體表特征與環(huán)境感知傳感器、智能控制、圖像處理和無線通信技術,構建生豬異常行為與異常環(huán)境全景和局部兩級聯(lián)動監(jiān)測平臺,實現(xiàn)對生豬異常行為和環(huán)境參數(shù)的全方位觀察、識別和數(shù)據(jù)采集功能,提高生豬養(yǎng)殖過程的智能化管理水平。試驗結果表明,該系統(tǒng)能夠按照預設指令自動、快速地依次對選取豬舍豬只個體的生長情況、行為特征和養(yǎng)殖環(huán)境信息進行自動采集,異常行為識別率可達93.5%,停車定位精度誤差為±12 mm。該研究有利于技術人員快速、準確獲取生豬生長環(huán)境和健康狀況信息,為生豬異常環(huán)境及時調(diào)控、異常行為快速診斷、疫病防治和疫情預警提供科學依據(jù)。

關鍵詞: 機器人, 健康養(yǎng)殖, 智能監(jiān)控, FPGA, 行為識別

Abstract: In order to improve the quality of pig breeding environment and behavior recognition rate, and overcome the problems of low recognition efficiency, poor accuracy, and high labor intensity in largescale breeding using manual inspection of abnormal behavior characteristics of live pigs and monitoring of breeding environment parameters, an intelligent monitoring system for pig health breeding based on the orbital robot was designed. The system consisted of an FPGA controller as the hardware core, combined with pig body surface characteristics and environmental sensing sensor, intelligent control, image processing, and wireless communication technology to construct a panoramic and local twolevel linkage monitoring platform for abnormal behavior and abnormal environment of pigs. The omnidirectional observation, identification, and data collection functions of abnormal pig behavior and environmental parameters improved the intelligent management level of the pig breeding process. The experimental results showed that the system can automatically and quickly collect the growth, behavior characteristics, and breeding environment information of individual pigs in the selected pig house according to the preset instructions. The abnormal behavior recognition rate reached 93.5%, and the parking positioning accuracy error was ±12 mm. The research was conducive for technical personnel to quickly and accurately obtain information about the growth environment and health status of pigs and provide a scientific basis for timely regulation of abnormal environments, rapid diagnosis of abnormal behaviors, disease prevention, and early warning of pigs.

Key words:  robot, healthy breeding, intelligent monitoring, FPGA, behavior recognition

中圖分類號: 

TP277

S828

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