Development Projects

Recent disaster events, like the 2021 flood in Germany showed clearly, that even the best alert systems and top first responder organisations can not prevent fatalities and serious damage on property without having prepared the citizens how to act and react during disaster situations and crises, understand alerts and follow instructions. B-prepared offers a cost-effective solution for building a culture of disaster preparedness with a multi-actor approach in realistic historical scenarios.

The project will further develop and optimise the road defect detection algorithm developed within ARNL. The algorithm uses a self-learning neural network, LiDAR and camera fusion to determine road surface deviations in front of vehicles that are important for vehicle speed. The resulting system warns the driver if a speed reduction is required, or generates an intervention signal to the vehicle control system in the case of a self-driving vehicle.

The Multinational Capability Development Campaign (MCDC) Artificial Intelligence Supported by Sensor Fusion project was jointly organised by HUN-REN SZTAKI (Hungarian Research Network Computer and Automation Research Institute), the MH Military Modernisation and Transformation Command (MH HTP) and the HVK Capability Development Office.

PREdictor for HUman-RObot COllaboration (PREHUROCO) utilizes interactive technologies in a new innovative way to create a cobot independent pre-collision approach for reducing these cumulative delays. PREHUROCO technology creates a shared virtual reality workspace over the Internet/Intranet for humans and robots. The human operator will be digitally immersed into the real-time digital twin of the manufacturing cell by XR visualization and/or haptic feedback.

In this project we address a new and very important issue: the observation of small backcountry wetland areas surrounded by different areas, hosting important species and delivering essential ecosystem services and biodiversity. Although these patches are small one by one, but together they can contribute to the wetland cover area with a very high rate – their protection and mapping is a need.

European Defence Agency Ad-Hoc Research and Technology Category B Project
2014/12-2017/12

Based on the APIS project, with extended goals: "To study, define, analyse a new system concept for implementing and demonstrating ISAR imaging capability in a plug-in multistatic array passive radar finalized to target recognition."

The main goal of ProActive is to research a holistic citizen-friendly multi sensor fusion and intelligent reasoning framework enabling the prediction, detection, understanding and efficient response to terrorist interests, goals and curses of actions in an urban environment.To this end, ProActive will rely on the fusion of both static knowledge(i.e. intelligence information) and dynamic information (i.e. data observed from sensors deployed in the urban environment).

The integrated4D (i4D) project of MTA SZTAKI is a joint mission of the Distributed Events Analysis Research Laboratory (DEVA) and the Geometric Modelling and Computer Vision Laboratory (GMCV). The main objective of the project is to design and implement a pilot system for the reconstruction and visualisation of complex spatio-temporal scenes by integrating two different types of data: outdoor 4D point cloud sequences recorded by a car-mounted Velodyne HDL-64E LIDAR sensor, and 4D models of moving actors obtained in an indoor 4D Reconstruction Studio.

The CrossMedia e-science platform supports collaborative research communities by providing a comfortable solution to jointly develop semantic- and media search algorithms on common and challenging datasets processed by novel feature extractors. Users form communities on the CrossMedia portal where they can jointly create, build and share search algorithms and media datasets in an iterative way.