Abstract
Abstract: Digital Twin Technology is an emerging concept that has captured the attention of both industry and academics in recent years. The advancement in industry 4.0 context requires strong and reliable anomaly detection techniques. The Digital Twin is expressed in a variety of ways, but it is best described as the seamless integration of data between a physical and virtual system in any state. Realistic models of complex equipment are now possible because to advances in Digital Twin technology. AI, IoT, and Digital Twins today has huge spectrum for use, and supported by various aiding technologies, although we still have a long way to go. A review of recent studies on Digital Twins is conducted, resulting in a categorical review. The study assesses the enabling technologies, difficulties, and ongoing research in the field of Digital Twins particularly in healthcare domain.
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