Biography
Djordje Dihovicni is a full professor at The Academy of Applied Studies Polytechnic, Belgrade, Serbia, and currently the Head of the Department of Electrical and Computer Engineering. He received his Ph.D in Mechanical Engineering, and he is scientific researcher verified by Serbian Ministry of Science and Technology. Professor Dihovični published parts and chapters in 7 international monographs, more than 4 national scientific monographs, more then 10 papers in a leading international journals (SCI, ESCI, and SCIE list), several papers published in a leading international conferences, more then 10 papers in international journals, more then 60 papers published in proceedings and presented at the international meetings, conferences and symposiums, more then 23 papers published in leading national journals, more then 50 papers published in proceedings and presented at the national meetings, conferences and symposiums, and more then 15 textbooks. His research interests include control systems, informatics, mechatronic systems, smart production systems and energy efficiency.
Conference contributions 1
AI IN DIGITAL TWINS
Digital twin is a dynamic, virtual replica of a physical object, process, or systems. AI (Artificial Intelligence) represents the capability of computer systems to perform tasks that typically require human cognition, as reasoning, problem-solving and learning. It operates by processing large amounts of data through complex algorithms to identify patterns, make predictions and automate processes. AI combined with digital twins creates specific added value. The use of generative AI increases the power of the digital twin technology. By leveraging AI algorithms like machine learning (ML), neural networks and generative AI, these digital, virtual replicas analyze real-time IoT data, predict future states and behaviors, and autonomously optimize physical assets, simultaneously saving time and resources. The listed transforms digital twins from passive 3D model into active, so called autonomous problem-solvers. AI-powered digital twins technology is revolutionizing cloud computing by providing dynamic, intelligent models, that replace real physical systems. By connecting real-time IoT sensor data with ML, AI enables these digital replicas to predict equipment failures, optimize workflows, simulate "what-if" scenarios, dramatically reducing downtime and costs across industries. With ML, as the field od AI, and generative AI systems can continuously learn, predict equipment failures, compare various scenarios and suggest demand optimizations. Agentic AI can independently monitor conditions and execute control signals. Key industry applications of mentioned technology include: intelligent manufacturing, smart cities, robotics, logistics, energy and power grids, aerospace, healthcare.