Goat Health Status Identification Based On Smart Wear And Information Fusion

With the development of China's economy,the continuous progress of society,the people's living standards have improved significantly,especially in the diet,people began to favor healthy food.Goats due to delicious meat,low cholesterol,nutrient-rich to become the first choice for consumers,the domestic goat farming scale also increased.As the goat suitable for living in a dry,moderate growth environment,and humid,hot environment easily lead to goat sickness,seriously affecting its growth and development,resulting in economic losses of farmers.Therefore,the prevention and diagnosis of sheep disease need to be strengthened,through the goat ontology parameters and breeding environment for wireless,real-time,accurate monitoring,for farmers to quickly take preventive measures to reduce damage is of great significance.In this paper,smart wearable technology is used to realize the real-time monitoring of goat's health status under the condition of large-scale breeding,and the problem of low and low efficiency of sheep disease is caused by the level and experience of the farmer.The intelligent wear equipment integrates a variety of sensors,wearing location,sensor type,number of equipment and other factors,monitoring data in a variety of forms,large amount of data,real-time processing and so on.To this end,the introduction of multi-sensor data fusion technology,and then proposed based on the neural network of goat health monitoring data fusion method to achieve the identification of goat health status.The main research contents and conclusions are as follows:(1)This paper first elaborates the background and key technologies of goat health monitoring,and discusses the development of intelligent wear technology and the origin and application of data fusion technology,and analyzes the situation of multi-sensor acquisition The data fusion technology and processing flow.(2)The goat health monitoring system based on wearing equipment was established,and the wearable equipment for goat characteristics was designed,and the physiological information of goat's body and the environmental information of goat's house were realized,including weather,temperature and real-time collection of current season information,And the data transmission to the server,the data fusion processing to provide the basis.(3)The principle of neural network and the application of BP neural network arestudied.On this basis,the model of goat health monitoring data fusion based on BP neural network is constructed.In addition,the problem of slow convergence rate of BP neural network is expounded and analyzed.The BP neural network is improved by using the global optimization of genetic algorithm,and the program flow of the improved algorithm is listed.The experimental results show that the improved BP neural network based on genetic algorithm can greatly improve the training speed and accuracy of the system,and make a more accurate identification of goat health.