Embedded Imaging System Based Behavior Analysis of Dairy Cow

Abstract

It is essential to develop ambient environmental conditions for counteracting the heat stress in dairy cows by efficient and reliable monitoring of the activities of the cow and existing environmental conditions. For this purpose, we present a system with an array of integrated sensor modules that continuously measure and record humidity and ambient temperature while simultaneously monitoring the dairy cows drinking behavior using a cost-efficient embedded imaging system. Video streams are collected by installing embedded imaging modules over the drinking troughs for testing and experimentation in the dairy farm. Convolutional neural network (CNN) model using deep learning techniques is used for analysis of the video stream by detection of the head of the dairy cow above the drinking trough. The values obtained as true positive rate and F1 score of the detection of the head of the cow are both 0.98. The dairy cows drinking behavior and the effect of heat stress is analyzed and recorded for varied environmental conditions over a period of twelve months. Based on the results of analysis, it is evident that the temperature and humidity index (THI) greatly influence the total frequency and length of everyday drinking habits of dairy cows. The drinking behavior of dairy cows and the effects of heat stress is demonstrated clearly using the automated imaging system with long-term monitoring and data collection. Quantitative assessment and automation are possible using this novel monitoring system to be implemented in dairy farms.