Animal drinking monitoring system and drinking state recognition method based on neural network

Abstract

The invention discloses an animal drinking monitoring system and a drinking state recognition method based on a neural network. The animal drinking monitoring system comprises an acquisition device and an intelligent terminal application, and the acquisition device acquires contact pressure, animal drinking sound frequency and drinking duration information of monitored animals and judges whether effective contact occurs or not according to the magnitude of the contact pressure; the intelligent terminal application receives effective animal data of the acquisition device and recognizes the effective animal data into the animal drinking state. By means of the recognition method, based on a neural network model, a sample set can be trained and learned, and based on the trained model, the drinking state of the animals is recognized. By means of the system, animal drinking situations can be automatically detected and remotely monitored in real time, manual detection or recording is not needed, and a lot of manpower can be saved; by means of the method, the difference like the type, the age, the individual and the motion state of the animals can be eliminated, all monitored objects are truly customized, and the purpose of precisely and effectively detecting drinking is achieved.

Description

technical field [0001] The invention relates to the field of animal health monitoring, in particular to an animal drinking water monitoring system and a neural network-based drinking water state identification method. Background technique [0002] The amount of drinking water is an important health indicator of animals. Drinking water monitoring is one of the important ways to evaluate the health status of animals. The timeliness, accuracy and reliability of drinking water monitoring directly affect the prevention, diagnosis, treatment and postoperative recovery of diseases. [0003] Traditional animal drinking water testing uses a single drinking water sample point, which is very inconvenient to track changes in animal drinking water status. At present, the measurement of animal drinking water is mainly done manually. The owner needs to manually observe and record the animal drinking water every day, and draw the drinking water status curve. A lot of work. Moreover, some a...

AI Technical Summary

Problems solved by technology

[0003] Traditional animal drinking water testing uses a single drinking water sample point, which is very inconvenient to track changes in animal drinking water status. At present, the measurement of animal drinking water is mainly done manually. The owner needs to manually observe and record the animal drinking water every day, and draw the drinking water status curve. heavy workload

Moreover, some animals, such as grazing cattle, cannot observe the specific drinking water conditions, and often need to be tracked and positioned continuously to achieve this. For such animals, traditional drinking water detection methods cannot implement high-frequency detection

[0004] In addition, different kinds of animals, different age groups of the same kind of animals, different individuals of the same kind of animals at the same age, and different exercise states of the same individual animals often have different drinking water conditions. Therefore, the monitoring of animal drinking water should consider the type, age, individual , sports status and other differences, but it is difficult to fully achieve the traditional method

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