Design Of Body Temperature Non-Contact Monitoring System For Broiler Based On Android Platform

Broilers are not only the most popular poultry in China,but also their consumption as food ranks second in the world.Body temperature is one of the essential health physiological indicators in animals.Additionally,Body temperature can be used to monitor animal welfare related observations and metabolism.Presently,the acquisition of broiler body temperature is achieved by manual sensing or manual contact measurement,which not only consumes a lot of workforces but also affects the body temperature distribution.The contact measurement methodology often has a significant amount of errors which eventually affect the quality of broiler production.By failing to discriminate unhealthy broilers in time,whole breed of infected broilers will need to be disposed of,thus,an enormous loss with regard to farm economy and animal welfare will be happened.In this paper,the broilers were used as the research object and designed a mobile platform which based on Android for broiler temperature and thermal infrared imaging detection system.The primary research contents are as follows:(1)Obtained the broiler's head as the area of interest.The thermal infrared movement camera captured the thermal infrared image of each broiler's whole body.However,the focus of this article is on the temperature value of the broiler's head in the high-temperature region.Therefore,the local high-temperature region was sub-divided by the region growing method.It is set as a region of interest and focuses on the average temperature of the region of interest.(2)Designed multiple linear regression models to correlate to the real broiler body temperature.To establish a regression model,two temperature data was used.First,temperature data for the region of interest and second,temperature data for the lower wing.The temperature under the broiler's wing is the temperature that best reflects its physiological condition.During imaging,the wireless thermometer is manually tied under the wings of the broilers,and the temperature under the wings is read in real time through the mobile phone client provided by the wireless thermometer.Through a multiple linear regression model,considering the influencing factors of ambient temperature and air humidity,an inversion relation model was established to predict the temperature under the ROI and predict the lower wing temperature.(3)Developing an Android mobile client based on a multiple linear regression model.Using Android Studio as a platform to develop a broiler temperature detection system.The proposed system used Java language and migrates the work done in the previous period to the Android platform.Through the cloud server and middleware,data transmission was realized.The entire system completes the acquisition of thermal infrared image,temperature of the ROI,and temperature display after regression modeling,and provides users with features and treatment methods of common febrile-type fever diseases.