Scientific Projects

The Industry 4.0 National Technology Platform was established under the leadership of the Institute for Computer Science and Control (SZTAKI), Hungarian Academy of Sciences, with the participation of research institutions, companies, universities and professional organizations having premises in Hungary, and with the full support and commitment of the Government of Hungary, and specifically that of the Ministry of National Economy.

The activities of the National Laboratory are focused on fundamental and applied research on the autonomous functionality and the control of road vehicles, aircraft and drones, robots and cyber-physical manufacturing systems. The main fundamental research topics are modelling, model reduction and identification, adaptive, robust, distributed and networked systems control. These areas are closely related to the applied research areas, which include environment perception and situation assessment, vehicle dynamics modelling and control, as well as testing and validation.

Introduction

One of the cornerstones of the development of autonomous vehicles nowadays increasingly focused on research is that the vehicle control system is able to plan the path of the vehicle taking into account the static and dynamic objects of the environment. Environmental sensing is based on sensors based on a variety of principles, such as ultrasound, radar, lidar, or machine vision based camera systems.

With new hardware and artificial intelligence against skin cancer

The HydroCobotics H2020 cascade consortium is coordinated by industrial robotics company Hepenix kft., while hydroponics company Green Drops Farm kft. is also a member. Within ELKH SZTAKI, the project is coordinated by Research Laboratory on Engineering & Management Intelligence research fellow Imre Paniti. The research and development project starts on the 1st of January, 2021 and presumably concludes on the 30th of September, 2021.

In the fight against COVID-19, manufacturing and distributing vital medical equipment became a major challenge. Unforeseen spikes in demand for essential medical supplies have been causing a greater urgency for supply chain optimisation and for deploying innovative approaches to scale up flexible and sustainable production methods.

Knowledge graphs have become the most important tools of sharing and connecting research or industry information and contacts.  These graphs enable, in a flexible way, the access, use and publication of data as a distributed system.

The DIGITbrain project aims to enable customised industrial products and to facilitate cost-effective distributed and localised production for manufacturing SMEs, by means of leveraging edge-, cloud- and HPC-based modelling, simulation, optimisation, analytics, and machine learning tools and by means of augmenting the concept of digital twin with a memorising capacity towards a) recording the provenance and boosting the cognition of the industrial product over its full lifecycle, and b) empowering the network of DIHs to implement the smart business model "Manufacturing as a Service".

Introduction

‘Connected’, ‘cooperative’, ‘smart’, ‘intelligent’ and ‘autonomous’ are labels that appear these days in nu­merous scientific pub­li­ca­tions and in many commercial advertisements in conjunction with up-to-date road vehicles.

Higher education has to keep pace with the global market needs for the necessary ICT(Information and Communications Technology) skills and the overall understanding of the complexity of industries in the 21st century. Global market companies have to effectively deal with the constant evolution of products, processes and production systems (and all in parallel) that can be more easily monitored, developed and up-graded using digital applications based on the concept of digital twin and taking advantage of Virtual Reality (VR) and Augmented Reality (AR) simulations.