Precise and automatic pig feeding method and system based on brain wave analysis

By using a precise automatic feeding method for pigs based on electroencephalogram (EEG) analysis, the system identifies the hunger state of pigs through EEG acquisition and machine learning, and constructs a closed-loop feeding system. This solves the problem of lack of physiological feedback in existing feeding methods and achieves precise and intelligent pig farming management.

CN122074411APending Publication Date: 2026-05-26NORTHEAST AGRICULTURAL UNIVERSITY
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Patent Information

Application Number
CN202610512408.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-17
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Current pig farming technologies lack physiological feedback in feeding methods, resulting in low precision, significant feed waste, high labor costs, and severe environmental pollution, failing to meet the precision and intelligent requirements of pig farming.

Method used

Wearable EEG acquisition devices are used to acquire real-time EEG signals from pigs. Hunger status is identified through preprocessing and feature extraction. Combined with machine learning models, precise feeding is achieved. Feedback is used to optimize and adjust feeding parameters, thus constructing a closed-loop feeding system.

Benefits of technology

It enables personalized feeding based on the physiological needs of pigs, reduces feed waste and labor costs, minimizes stress response, improves growth efficiency and animal welfare, and is suitable for large-scale pig farm management.

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Abstract

The invention relates to the technical field of livestock and poultry breeding intelligent feeding, in particular to a precise and automatic pig feeding method and system based on brain wave analysis, and the method comprises the steps: obtaining original brain wave signals of a pig in different states in real time through a wearable brain wave collection device; performing preprocessing and feature extraction on the original brain wave signal, and inputting the processed feature data into a starvation state recognition model for recognition; when the recognition result is that the pig fence is in the hungry state, a feeding instruction is sent to a corresponding pig fence feeder, and the feeder completes feeding according to the preset basic feeding amount; feeding parameters are dynamically adjusted according to feeding feedback after feeding, and closed-loop precise feeding is achieved. According to the invention, the feed waste rate and the breeding labor cost are greatly reduced.
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