Advanced contribution of IoT in agricultural production for the development of smart livestock environments

Abstract

Many areas of contemporary life need the use of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) for analysis and comprehension. The application of AI and ML in livestock farming has led to an improved understanding of animal behavior and discomfort, the prevention and management of diseases, and the efficiency of the farmer's economic choices. Digital twin technology is a particularly promising field that builds on AI and is already being utilized to increase efficiency and decrease costs in cattle livestock agriculture. A Digital Twin (DT) is a constant-update numerical copy of smart livestock environments. The proposed research is IoT, and Digital Twins in Livestock Farming (DTLF) might expand extensive Precision Livestock Farming (PLF), technology and tools use, and farm animal health and well-being. Global Positioning Satellite (GPS), Radio Frequency IDentification (RFID), AI, and even ML are only some current technologies that may be used for automated tracking of individual animal whereabouts. There is promise in using these methods and innovations to monitor and evaluate animal welfare, but these techniques are difficult. Just like other revolutionary innovations, the utilization of the DT mechanism will improve disease analysis prediction for individual farms by a factor of 92%. The responsiveness of DTLF will be a 92% response rate in analyzing the Heartbeat, a 94% effectiveness rate in analyzing the Temperature Range, and a 94% overall effectiveness in evaluating the Humidity Range.