A Data Analytics of Environmental Footprints and Greenhouse Effect of Cattle Production Using a Random Forest Algorithm

Abstract

Due to the significant effects that analytical footprints and feeding mechanism have among cattle which affects production effectiveness and general quality of farming. Which has drawn more attention in recent years. For example, greenhouse gas effects and grazing are a common problem that frequently remains untreated, with serious negative consequences. Thus, this research has developed a digital solution that uses sensors to monitor cattle grazing in order to address health related issues that may frequently arise affecting the overall health condition of cattle. The proposed solution employed an intelligent internet of things (IoT) device with Global Positioning System (GPS) monitoring features to let cattle owners log and track all important updates and concerns. Furthermore, the developed device includes functionalities such as heart rate sensor, temperature sensors, ESP32, to offer valuable insights into cattle health status and enable timely intervention when needed.