Buffalo precise feeding system and method based on internet of things

By employing multimodal biometrics based on infrared nasal print images, voiceprint signals, and body temperature data, combined with the GRU dynamic nutrition model and mixed integer programming optimization algorithm, the problems of individual identification failure, static and inefficient nutrition models, and slow system response in buffalo farming have been solved. This has enabled individualized, real-time optimization of nutrition formulas and health management, thereby improving farming efficiency and economic benefits.

CN122397633APending Publication Date: 2026-07-17广西壮族自治区畜禽品种改良站 +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
广西壮族自治区畜禽品种改良站
Filing Date
2026-06-04
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

In existing buffalo farming technologies, individual identification methods are prone to failure, nutritional models are static and crude, feeding optimization results lack practicality, system response speed is slow, and health monitoring mechanisms are lacking, making it difficult to meet the dynamic needs of individuals and identify them around the clock.

Method used

Employing multimodal biometrics using infrared nasal print images, voiceprint signals, and body temperature data, combined with the GRU dynamic nutrition model and mixed integer programming optimization algorithm, and through edge computing and cloud collaboration, it achieves individual identification, real-time optimization of nutritional formulas, and detection and compensation for health abnormalities.

Benefits of technology

It improves the accuracy and stability of individual identification, enables personalized and real-time nutritional formulation, enhances the system's response speed and health management capabilities, and improves the intelligence level and economic benefits of the breeding process.

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Abstract

The application discloses a kind of based on Internet of Things's water buffalo precise feeding system and method. Including biological feature acquisition terminal, edge computing device, cloud intelligent platform and execution control module, it is applicable to the intelligent management scene of large-scale water buffalo breeding. The method is by collecting the nose print image of water buffalo, voiceprint signal and temperature data, fusion multi-modal biological feature realizes individual identity recognition;On the basis of identification, call the dynamic nutrition model constructed based on GRU neural network, combine weight, exercise amount, environmental parameter and other characteristics to generate individualized feeding formula;Adopt mixed integer programming algorithm to optimize feed proportioning, give consideration to nutrition, cost and palatability Multiple constraints;It also includes abnormal detection and nutrition compensation mechanism, for identifying healthy abnormal individual and adjusting feeding scheme. The system is based on Internet of Things technology to realize edge inference and cloud cooperation, improve the identification accuracy, response speed and feeding intelligent level.
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