Internet of Things (IoT) and Machine Learning (ML) enabled Livestock Monitoring

Abstract

Livestock monitoring is one of the growing concerns in the present era mainly owing to the ever- increasing population and the ascending demand for dairy products. Further, to prolong the lifecycle and sustain the quality of livestock, the regular monitoring of cattle health is essential. Several diseases are transmitted from animals to humans, therefore, an early prognosis regarding the cattle health and disease is required. This paper reviews the existing technology-based solutions and related equipment and provides a comparison of the features offered by these systems and their limitations. In addition, we have proposed an Internet of Things (IoT) based real-time system for livestock health monitoring. The proposed system will consist of a custom-designed multi-sensor board to record several physiological parameters including skin temperature, heart rate, and rumination w.r.t surrounding temperature, humidity, and a camera for image analysis to identify different behavioral patterns. The measured data will be sent to the server using Wi-Fi/GSM technology, where data analytics will be performed using machine learning (ML) models to detect sick animals and predict cattle health overtime for providing early and timely medical care. For data visualization, a web portal and a mobile app will be developed, providing a dashboard of services to analyze and display the sensed data.