FUTURE TECH CORE PROGRAM (2023 - 2026)

Contributions to the consolidation of emerging technologies specific to the Internet of Things and Complex Systems

Project Coordinator: Dr. Eng. Radu Marius BONCEA – Scientific Researcher III

The project aims to identify outstanding issues in the adoption and integration of IoT systems and provide advanced solutions in terms of efficiency, reliability, scalability, interoperability and security. The developed methods, models and algorithms will be demonstrated experimentally using a use case with an impact in increasing the quality of life, such as intelligent environmental monitoring. In this sense, the project team will develop IoT devices and an IoT platform, based on a SIOC (Smart Integrated Operation and Control) platform, which has been developed within the previous core program.


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Architecture – platform of an intelligent system for monitoring Internet domains by developing a dynamic reputation establishment system (TLDRep)

Project Coordinator: Dr. Eng. Ionuț Eugen SANDU – Scientific Researcher III

The project aims to create an architecture of an automatic monitoring platform, using AI/ML technologies, to create a dynamic system for establishing the reputation of each .ro domain. Based on the mentioned architecture, an experimental model will be developed that will act on the anonymized data set from the RoTLD domain register. The prototype developed within the project will be used to detect and monitor malicious domains registered in the "black list" of the .ro Registry database.


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Resilient and interoperable communication systems based on distributed technologies and self-sovereign digital identity (RoDID)

Project Coordinator: Dr. Eng. Adrian Victor VEVERA – Scientific Researcher II

The project proposes the introduction of a new standard of interoperability and communication in the issue of identity management and new methods of securing existing cyber spaces.


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Advanced Artificial Intelligence Techniques in Science and Application Domains

Project Coordinator: Dr. Eng. Liviu BADEA – Scientific Researcher I

The project aims at investigating the latest Artificial Intelligence (AI) techniques, with the development of applications in some high-impact fields, such as the biomedical domain as well as the field of artificial vision for cognitive agents, respectively.


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Metaverse advanced research and emerging technologies for the digital transformation of society

Project Coordinator: Dr. Eng. Ionuț PETRE – Scientific Researcher II

The project aimed to explore the intrinsic characteristics of the Metaverse concept, analyze its most important dimensions and experiment with the most important existing technologies, in order to develop innovative theoretical and applied results, in the form of studies, technical reports, theoretical and experimental models, with an emphasis on proprietary architectural solutions for applications in the field of public services and education.


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Multifunctional portable unit for combating digital crime

Project Coordinator: Deniss-Bogdan Onofrei-Riza

The main goal is the design and implementation of a complex system of software-assisted hardware equipment capable of covering (in a portable / field form) the vast majority of the needs generated by the main sectors of digital crime: computer forensics, mobile device forensics, forensics of data transiting a computer network, forensic investigation of data stored in cloud structures, forensic investigation of encrypted flows, data and / or devices, forensic investigation of wireless flows and equipment, forensic investigation of GSM flows and equipment, and forensic investigation of cryptocurrency transactions.


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Intelligent system for predicting energy consumption in buildings (PRECONERG)

Project Coordinator: PhD. Eng. Eleonora TUDORA – Scientific Researcher III

The "Intelligent system for predicting energy consumption in buildings (PRECONERG)" project aims to develop, test and validate an energy consumption prediction system using advanced prediction techniques with the help of energy consumption prediction models based on artificial intelligence.


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