Livestock animal fence entry detection method based on gun-ball linkage and BIM

Abstract

The invention discloses a livestock animal fence entry detection method based on gun-ball linkage and BIM. The method comprises the following steps: carrying out animal detection on an animal image ofa large-range free-ranging area acquired by a gunlock; carrying out coordinate regression to obtain animal key point coordinates; when the distance between the animal and the fence is smaller than aset threshold value, calling the gunlock; enabling the gunlock to collect a fence entrance image and process the fence entrance image to obtain a fence entrance animal thermodynamic diagram; superposing thermodynamic diagrams of animals at the entrance of the fence, and adjusting the pose of the dome camera after the track disappears; acquiring an animal image of an internal area of the fence, andprocessing to obtain an animal thermodynamic diagram in the fence; counting the number of peak points of animal thermodynamic diagram hot spots in the fence; and combining the WebGIS technology to visualize the livestock breeding area building information model. By means of the animal husbandry in-fence detection system and method, automatic animal husbandry in-fence detection is achieved, the animal husbandry in-fence detection efficiency and precision are improved, and the safety in the data processing and transmission process is improved.

Description

Technical field [0001] The invention relates to the technical fields of artificial intelligence, BIM, blockchain, and smart animal husbandry, and in particular to a method for detecting the entry of livestock animals based on gun-ball linkage and BIM. Background technique [0002] In the livestock industry, in order to obtain better meat products and dairy products, it is often necessary to combine captive and free-range breeding in animal and plant breeding. The number of animals kept in captivity is generally very large. When the animals enter the fence after grazing and free-range and perform statistics, the traditional statistical method that relies on the farmers to observe is no longer suitable for the current situation of the animal husbandry industry. [0003] In the current statistics on the number of animals raised, some methods realize the statistics by installing a position sensor on each animal. However, in the actual breeding process, since the number of animals will...

AI Technical Summary

Problems solved by technology

However, in the actual breeding process, since the number of animals will change at any time with the slaughter, reproduction, etc., the method of sensor statistics requires the implementer to install sensors for the animals in time according to the situation, which not only costs high but also brings inconvenience to the implementation

Also, sensor detachment can cause statistical bias and reduce accuracy

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