Intelligent digital twin for energy industry in AIoT networks
Keywords:Industry 4.0, Internet of Things, Artificial Intelligence, Machine Learning, Digital Twins
After industrial revolution the demand for the capacity and reliability of optical networks has continued to grow. Industries have become sources of numerous heterogeneous data. In order to handle these data/challenges, many issues need to be resolved, among which the low-margin optical networks design, power optimization, routing and wavelength assignment (RWA), failure management are quite important. Today Artificial Intelligence (AI), especially Machine Learning (ML), Digital Twins (DT) are regarded as one of the most promising methods to overcome the errors/problems that occurred at site. Intelligent systems make it possible to predict the behavior of highly complex production systems. Internet of Things -IoT- represents a new production reality. In the study interviews with experts on “Intelligent digital twin for Energy Industry in AIoT networks” are performed and Fuzzy MCDM based approach is developed. In the study 6 main criteria, i.e., Process Monitoring and Resource Optimization, Advanced Analytics, New Opportunities, Intelligent Grid, Cost-savings and Data Management, Sustainability and 34 related sub-criteria are evaluated by experts. Active digital twin is a solution that is carrying out a certain task on behalf of an object or under user assignment. Such form of digital twin is called intelligent information agent since it is already equipped with a certain form of artificial intelligence. It uses sensor devices and gateway connectivity to derive actionable insights and use them to develop new and advanced services for enhanced productivity.
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