Poultry food intake parallel anomaly detection method based on BIM and artificial intelligence

A poultry and poultry house technology, applied in character and pattern recognition, image data processing, instruments, etc., can solve the problems of low statistical accuracy of eating time, weak representation ability, and low detection accuracy

Inactive Publication Date: 2020-10-20
郑州市鼎晶信息技术有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

First of all, the intersection ratio cannot well represent whether the animal is eating or not, so the detection accuracy is not high
Due

Method used

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  • Poultry food intake parallel anomaly detection method based on BIM and artificial intelligence

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Experimental program
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Effect test

Embodiment 1

[0039] First build the current poultry house area building information model BIM (Building Information Modeling) and its information exchange module.

[0040] The poultry house area BIM and its information exchange module is a BIM-based information processing and data exchange platform. The poultry house area BIM includes the geographic location information of the poultry house area, the poultry house area fence information, the poultry house area aisle information, the poultry cage placement information, the poultry cage geometric structure information, etc. It is used for BIM three-dimensional space model modeling of the poultry house area. required information. The poultry house area BIM also includes the image sensor model, resolution, quantity and their respective number information inside the poultry house used in the current area.

[0041] The BIM in the poultry house area can receive the data sensed by all sensors in the current area through the information exchange m...

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Abstract

The invention discloses a poultry food intake parallel anomaly detection method based on BIM and artificial intelligence. The poultry food intake parallel anomaly detection method comprises the stepsof: splicing and fusing poultry house images to obtain a poultry house panoramic image, and carrying out projection transformation on the poultry house panoramic image to a poultry house building information model; conducting poultry detection on the poultry house panoramic image; carrying out head key point detection on a region-of-interest image of each poultry in a period of time after the foodis fed; carrying out heat map superposition on the poultry head key point thermodynamic diagrams of which the poultry head key points fall into the a feeder region-of-interest within a period of timeafter the food is fed; inputting a superposition result into a poultry abnormal food intake analysis neural network to obtain a poultry abnormal food intake grade, and generating an abnormal food intake signal; and visualizing various kinds of information in the poultry house building information model. According to the poultry food intake parallel anomaly detection method, automatic poultry foodintake state monitoring is realized, the detection efficiency is high, and the detection accuracy is high.

Description

technical field [0001] The invention belongs to the technical fields of artificial intelligence, BIM and intelligent animal husbandry, and in particular relates to a parallel abnormality detection method for poultry eating based on BIM and artificial intelligence. Background technique [0002] With the rapid development of my country's economy, my country's livestock and poultry breeding industry has developed rapidly. Correspondingly, great changes have taken place in the breeding scale and breeding methods of the livestock and poultry breeding industry. The traditional farming methods and empirical methods are not suitable for the current industry development due to their high cost and chaotic management. Therefore, the livestock and poultry breeding industry urgently needs to rely on cutting-edge scientific and technological means to establish its digital, refined and intelligent industrial breeding management model. If the poultry is sick, the most obvious manifestatio...

Claims

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Application Information

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IPC IPC(8): G06K9/32G06K9/46G06K9/62G06F30/13G06T17/00G06Q50/02
CPCG06F30/13G06T17/00G06Q50/02G06V10/25G06V10/40G06F18/25
Inventor 李文倩张越
Owner 郑州市鼎晶信息技术有限公司
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