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Current

Decentralized artificial intelligence in a distributed virtualized computing environment.
Duration:	1. 1. 2026 - 31. 12. 2029
Evidence number:	2/0081/26
Program:	VEGA
Project leader:	Mgr. Bobák Martin, PhD.
SAS cosolvers:	Ing. Astaloš Ján, Ing. Dlugolinský Štefan, PhD., Ing. Dobrucký Miroslav, Ing. Dora Jean Rosemond, PhD., doc. Ing. Forgáč Radoslav, PhD., Ing. Habala Ondrej, doc. Ing. Hluchý Ladislav, CSc., Ing. Hucko Michal, Ing. Javurek Martin, PhD., Ing. Krammer Peter, Milivojevic Marko, PhD., doc. Ing. Očkay Miloš, PhD., Ing. Skaličan Michal, Ing. Skovajsová Lenka, PhD., Ing. Staňo Michal, Mgr. Šeleng Martin, PhD., prof. Ing. Štich Ivan, DrSc., Ing. Tran Viet, PhD.
Annotation:	Artificial Intelligence (AI) currently represents one of the main pillars of technological progress. From healthcare toindustry, education, and other industrial and scientific sectors, AI offers revolutionary solutions that arefundamentally changing how we approach new challenges. A key aspect of innovation in this field is data, and itsexponential growth brings significant challenges in terms of processing and security.Addressing the aforementioned issues cannot rely on a centralized approach. Therefore, the methodology wepropose is based on the concepts of decentralized AI, including federated, distributed, and split learning, withtrained models being multi-task and enabling multi-criteria optimization. This kind of concept has specificrequirements for the software system, which must fully support the lifecycle not only of the AI itself but also ofindividual models. The research outcomes will contribute to the development of scalable and secure AI solutionsin distributed environments.

Next-Generation Gas Sensors Integrating Advanced 2D Materials and Neural Networks for Enhanced Detection of Gases in the Environment.
Duration:	1. 1. 2026 - 31. 12. 2029
Evidence number:	2/0140/26
Program:	VEGA
Project leader:	Ing. Mgr. Andok Robert, PhD.
SAS cosolvers:	Agu Friday, M.Sc., Ing. Barák Vladislav, RNDr. Bardošová Mária, CSc., Ing. Benčurová Anna, prof. Ing. Hotový Ivan, DrSc., Ing. Hrkút Pavol, CSc., Ing. Klarák Jaromír, PhD., Ing. Kliuchka Anatolii, Ing. Konečníková Anna, RNDr. Kostič Ivan, Ing. Nemec Pavol, Ing. Predanocy Martin, PhD., Ing. Ritomský Adrian, Ing. Ritomský Mário, Ing. Škriniarová Jaroslava, CSc.
Annotation:	The project aims to conduct fundamental research in the field of gas sensors, focusing on the integration of advanced 2D materials using neural networks for better detection of reducing and oxidizing gases in common operating environments. The project implements knowledge on new advanced nanostructured semiconducting materials. It aims to investigate the properties of selected 2D nanostructured materials from the point of view of their application in microelectronics. We will focus on the application of mechanical and chemical exfoliation methods to layers of nanostructured disulfides (WSe, WS2, MoS2) and their transfer to a microelectronic element on a substrate. The results will be compared with other materials such as TiO2, NiO and their combinations. We will connect the selected gas sensors to a neural network, which will be trained on a large number of cases in order to identify a given detected gas and determine its concentration as accurately as possible.

EXICOM - Experimental investigation and computer modelling of airflow during road tunnel fire
Duration:	1. 9. 2025 - 31. 8. 2029
Evidence number:	APVV-24-0429
Program:	APVV
Project leader:	Mgr. Weisenpacher Peter, PhD.
SAS cosolvers:	RNDr. Glasa Ján, CSc., Mgr. Kubišová Tatiana, doc. Ing. Papán Daniel, PhD., Ing. Valášek Lukáš, PhD.
Annotation:	The research project will contribute to the verification of the computer simulation of the airflow and smoke spread in road tunnels and to the increase of fire safety of tunnels in Slovakia. The project aim is to investigate the interaction of emergency ventilation operation, meteorological factors and fire in a real tunnel and to create a series of computer simulations of customer-designed fire scenarios in two motorway tunnels, which will be verified by in situ measurements. Detailed studies on the course of fires and the efficiency of emergency ventilation will be developed. The simulations will be carried out on the HPC infrastructure at the Slovak Academy of Sciences. In order to validate the results of the created simulations, full-scale experiments and measurements of airflow and meteorological factors will be carried out by the customer of the project results. Modifications to the Tunnel Traffic & Control Simulator (TTOS) at the University of Zilina in Zilina will be designed and implemented in accordance with current legislation, which will strengthen its uniqueness in the Central European area and improve its use for training and testing tunnel control operators in Slovakia. Part of the solution will be the recording and evaluation of emergency events in tunnels in Slovakia and the development of a series of visualizations of the course of fires based on computer simulations for TTOS, which will serve as a visualization didactic tool in the education of tunnel control operators and university students. The project solution will make it possible to intensify and streamline the research cooperation of the project solvers, to create a strong partnership of research organizations with important customers of the project results, and to effectively use the modern research infrastructure of the participating organizations to create innovative solutions to increase the safety of road tunnels.

Human-machine voice communication interface for non-standard and extreme use cases
Duration:	1. 1. 2025 - 31. 12. 2028
Evidence number:	2/0092/25
Program:	VEGA
Project leader:	prof. Mgr. Beňuš Štefan, PhD.
SAS cosolvers:	Ing. Černáček Tomáš, Mgr. Čiernik Kevická Viktória, PhD., Ing. Darjaa Sakhia, PhD., Ing. Mladý Michal, Ing. Rusko Milan, PhD., Mgr. Sabo Róbert, PhD., Ing. Trnka Marian
Annotation:	A voice interface for human-machine communication is an alternative to keyboard, touch or mouse interaction. Currently, voice interfaces are designed and tuned for "standard" use: communicating in a normal, calm, voice, mostly in a non-excited, announcing style, the target group is the majority of the economically active population, i.e. young and middle-aged adults. However, the research of non-standard, atypical, marginal and extreme cases of communication is gaining importance due to the increase in the robustness of a) formal models of the cognitive system of human-machine communication, as well as b) IT applications that use voice interfaces for wide target groups and communication situations. The presented project aims to research and optimize approaches to communication with seniors, pre-adolescent children, to affective communication (with high but also low emotional arousal), to communication with persons affected by neurodegenerative diseases, and to open the possibility of communication in Romani.

Chemiresistive gas microsensors based on a combination of nanostructured transition metal sulfides and oxides
Duration:	1. 1. 2025 - 31. 12. 2028
Evidence number:	VEGA 1/1480/25
Program:	VEGA
Project leader:	RNDr. Kostič Ivan
SAS cosolvers:	Ing. Mgr. Andok Robert, PhD., RNDr. Kostič Ivan, Ing. Ritomský Mário
Annotation:	The project aims to conduct basic research in the field of discovering new, progressive semiconductor materials based on metal oxides and disulfides, as well as in the field of electrode material technology utilizing boron-doped diamond layers. We anticipate that our activities will focus on the preparation and investigation of the properties of TiO₂, NiO, and WS₂ layers, as well as their selected combinations and doping. These nanostructured semiconductor materials will be integrated into chemoresistive gas sensors placed on thin electro-insulating membranes. Attention will also be devoted to research into the technology of an integrated voltammetric sensor with a protective Nafion polymer layer for the simultaneous determination of trace concentrations of heavy metals.
Project website:	https://ui.sav.sk/oddelenia/senzorickych-informacnych-systemov-a-technologii/projekty-oddelenia-senzorickych-informacnych-systemov-a-technologii/

Structures S3PR, ES3PR and S4PR of mathematical models of resource allocation in discrete production systems based on Petri nets and their use for deadlock prevention.
Duration:	1. 1. 2025 - 31. 12. 2028
Evidence number:	2/0005/25
Program:	VEGA
Project leader:	doc. Ing. Čapkovič František, CSc.
Annotation:	Discrete systems remain in a certain state until they are forced to change this state due to the occurrence of some discrete event. They are called DES (Discrete-Event Systems). They include a wide class of real systems – flexible (alias automated) manufacturing systems, robotic cells, communication systems, transport systems, etc. Petri nets PN are very suitable for mathematical modelling of DES. RAS (Resource Allocation Systems) in DES tend to deadlocks. PN-based DES models can be used to eliminate deadlocks. Three model paradigms, namely S3PR, ES3PR and S4PR, will be investigated using two approaches: (i) structural analysis of PN RAS models, specifically using siphons and traps, without the need to know the initial state, (ii) P-invariants PN models of RAS and reachability tree (RT) of states. Both approaches will be applied to all model paradigms, compared and evaluated using simulations in Matlab (or SciLAB).

DyMAX - Dynamic malware analysis with explainable AI
Duration:	1. 9. 2024 - 30. 6. 2028
Evidence number:	DyMAX
Program:	APVV
Project leader:	Ing. Budinská Ivana, PhD.
SAS cosolvers:	Ing. Kenyeres Martin, PhD., Ing. Leľová Michaela, Mgr. Mojžiš Ján, PhD.
Annotation:	Machine learning allows processing large volumes of data and achieving high success rates in classification tasks in various areas, including malware analysis. The main disadvantage of many machine learning methods lies in their non-transparency: they are unable to provide human users with a comprehensible justification for their outputs. The field of explainable artificial intelligence (eXplainable AI – XAI) is currently very relevant, providing a number of new methods that allow overcoming this problem. Unfortunately, many XAI methods still do not reach the level of success and efficiency of traditional non-transparent machine learning. The aim of this project is to improve the usability of XAI in malware analysis by creating more sophisticated malware datasets based on dynamic malware analysis built on semantic representation, examining the most suitable XAI methods applicable in this context and their comparative analysis, and examining the possibilities of using symbolic outputs from XAI methods in distributed detection systems in combination with distributed consensus search algorithms.

REPRIKOM - Speech alignment for L2 communicative competence
Duration:	1. 9. 2024 - 30. 6. 2028
Evidence number:
Program:	APVV
Project leader:	prof. Mgr. Beňuš Štefan, PhD.
SAS cosolvers:	Ing. Trnka Marian
Annotation:	Spoken interactions taking place in English as a non-native (L2) language are becoming a prevalent mode of dialogue in many spheres of professional discourse. Previous studies show that alignment among interlocutors during L1 interactions, i.e. their tendency to adjust their speaking behaviour to the interlocutor, correlates with multiple positive social aspects linked to the success of the interaction, rapport and engagement of the speakers, or their mutual evaluations in trust, attractiveness, or competence. Yet, due to the inherently complex nature of alignment stemming from multiple, potentially inter-relating factors affecting alignment, our understanding of the cognitive mechanisms and potential applicability in a language learning environment is limited. The proposed research aims at improving our understanding of key factors affecting alignment, such as the effect of native (L1) vs. non-native (L2) language, the relationship between non-verbal (e.g. intonation, speech rate) and verbal (syntactic structure, lexical choices) aspects of spoken interactions, the degree of L2 proficiency of the interlocutors, or their emotional and social state. Knowledge gained from a better understanding of the relationships between these factors and interpersonal alignment strategies generates testable predictions and hypotheses for applied research in which intervention approaches facilitating alignment might be proposed and tested for their hypothesized positive effect on the communicative competence in L2 interactions in both educational and professional settings. We aim to gain this knowledge by 1) creating a spoken corpus of semi-spontaneous dialogues in both L1 and L2 with a novel design varying the factors mentioned above, and 2) subsequently analysing the alignment strategies and the effect of these factors on the alignment behaviour of the interlocutors in the corpus.

AFAROB - Therapy of Aphasia Using Social Robotics and Artificial Intelligence
Duration:	1. 3. 2025 - 30. 6. 2028
Evidence number:	VV-MVP-24-0072
Program:	APVV
Project leader:	Mgr. Čiernik Kevická Viktória, PhD.
SAS cosolvers:	Ing. Darjaa Sakhia, PhD., Ing. Rusko Milan, PhD., Mgr. Sabo Róbert, PhD., Ing. Trnka Marian
Annotation:	The project focuses on innovative approaches in aphasia therapy, specifically on the integration of social roboticsand artificial intelligence into therapeutic procedures. Aphasia is a disorder of speech production andcomprehension caused by brain damage, often as a result of stroke, which leads to serious communicationproblems and social isolation. Current therapeutic methods emphasize intensive and authentic communication, butthis is not always possible due to limited access to speech therapy. The project has three main objectives: todesign an innovative therapeutic approach at the level of discourse - spontaneous speech, to verify the usability ofa social robot within the framework of the created therapeutic approach, and to verify the usability of largelanguage models in therapy. The applicability of the therapeutic approach using social robotics and large languagemodels is initially tested on a sample of healthy participants, and then on a sample of participants with aphasia.The result of the project is the evaluation of usability of a social robot and large language models in therapy in theclinical group of people with aphasia. The benefit of the project is its long term potential to increase the availabilityof therapy and the frequency of therapeutic sessions and to simulate the natural course of speech therapy, whichcontributes to the functionality of communication and to improving the quality of life of patients.

Computer simulation of airflows and fire smoke spread in critical structures
Duration:	1. 1. 2024 - 31. 12. 2027
Evidence number:	VEGA 2/0096/24
Program:	VEGA
Project leader:	Mgr. Weisenpacher Peter, PhD.
SAS cosolvers:	RNDr. Glasa Ján, CSc., Mgr. Kubišová Tatiana, Ing. Valášek Lukáš, PhD.
Annotation:	Research in the proposed project is focused on formulation of new scientific knowledge on computer simulation ofairflows and fire smoke spread in critical structures. Motorway tunnels were selected as the main subject ofresearch interest based on discussions with specialists on fire safety in Slovakia. Tunnels belong to inteligentstructures with high safety requirements due to potentially huge losses in case of fire. Natural airflows, airflowscreated by emergency ventilation, airflows induced by fire and fire smoke spread will be analyzed with focus onvelocity fields, velocity profiles and smoke stratification. Computational aspects of efficient parallel realization ofcomputer simulation on HPC systems will be investigated as well. The previous research results, experience andobtained experimental data will be utilized. The research is in line with current research trends and requirementsof the fire researchers’ and simulators developers’ community and has potential to have significant social impact.

Supercomputer modeling of the properties of 2D nanomaterials using first-principle methods with the support of artificial intelligence: 2D-AIMAT
Duration:	1. 1. 2025 - 31. 12. 2027
Evidence number:	2/0133/25
Program:	VEGA
Project leader:	Mgr. Brndiar Ján, PhD.

SPICE - Smart Data PIpelines for the Cognitive ComputE Continuum (SPICE)
Duration:	1. 4. 2025 - 30. 9. 2027
Evidence number:	09I02-03-V01-00012/2025/VA/PZ
Program:	Plán obnovy EÚ
Project leader:	doc. Ing. Hluchý Ladislav, CSc.
SAS cosolvers:	Ing. Astaloš Ján, Mgr. Bobák Martin, PhD., Ing. Dlugolinský Štefan, PhD., doc. Ing. Forgáč Radoslav, PhD., Ing. Habala Ondrej, Ing. Krammer Peter, doc. Ing. Očkay Miloš, PhD., Ing. Staňo Michal, Mgr. Šeleng Martin, PhD.
Annotation:	The growing scale and complexity of the Cloud led to the emergence of Edge and IoT computing in the "computecontinuum" for applications relying heavily on sensor data and time-critical AI-assisted data processing. Its primarygoal is to enable intelligent decision making and gain deeper insights across the continuum. At the same time,assembling and maintaining well-designed data pipelines involves addressing numerous technical, operational andorganizational challenges. These hurdles and expertise/resource constraints act as a barrier for wider adoption of datapipelines. Our goal is to provide: (1) AI-assisted composition of smart data pipelines to radically simplify complexand distributed data processing, (2) a highly optimized execution environment and resource management that enablesecure and smart data processing for the compute continuum. The results of our project will be made available as aninnovation transformation incubator for others to exploit.

STICS - Smart transformation & Innovation Consortium Slovakia
Duration:	1. 4. 2025 - 30. 9. 2027
Evidence number:	09I02-03-V01-00011
Program:	Plán obnovy EÚ
Project leader:	Ing. Balogh Zoltán, PhD.
SAS cosolvers:	Ing. Budinská Ivana, PhD., doc. Ing. Čapkovič František, CSc., Ing. Gatial Emil, PhD., Ing. Gatial Milan, RNDr. Glasa Ján, CSc., Ing Hassankhani Dolatabadi Sepideh, PhD, Ing. Kasanický Tomáš, Ing. Kenyeres Martin, PhD., Ing. Klarák Jaromír, PhD., Ing. Lovíšková Jana, PhD., Mgr. Mojžiš Ján, PhD., Ing. Valášek Lukáš, PhD., Mgr. Weisenpacher Peter, PhD., Ing. Zelenka Ján, PhD.
Project website:	https://stics.umb.sk/

AI4CC - AI-Driven Self-awareness and Cognition for Compute Continuum (AI4CC)
Duration:	1. 7. 2024 - 30. 6. 2027
Evidence number:	APVV-23-0430
Program:	APVV
Project leader:	doc. Ing. Hluchý Ladislav, CSc.
SAS cosolvers:	Ing. Balogh Zoltán, PhD., Mgr. Bobák Martin, PhD., Ing. Dlugolinský Štefan, PhD., Ing. Dora Jean Rosemond, PhD., doc. Ing. Forgáč Radoslav, PhD., Ing. Gatial Emil, PhD., Ing. Habala Ondrej, Ing. Krammer Peter, Milivojevic Marko, PhD., doc. Ing. Očkay Miloš, PhD., Ing. Staňo Michal, Mgr. Šeleng Martin, PhD., Ing. Tran Viet, PhD.
Annotation:	AI4CC aims to contribute with new AI-based methods and algorithms to the development of modern computingcontinuums, addressing some of the key challenges of this domain. These challenges include enhancing theautonomy and self-adaptation capabilities of compute continuum platforms to optimize decision-making andresponsiveness; adapting to changing conditions, necessitating flexible and adaptive computing models fordynamicity; efficiently managing vast amounts of data, considering factors like decentralization, scalability, andreal-time processing for effective Data Management; ensuring transparency, explainability, and accountability in AIand machine learning models within compute continuums; achieving seamless interoperability between diversedevices and platforms within the continuum, impacting data exchange and communication for Interoperability, anddealing with resource heterogeneity—variability in computing resources across the continuum, including edge andcloud environments, posing challenges in optimizing performance and resource utilization. By systematicallyaddressing these challenges and pioneering advancements in these key areas, AI4CC aims not only to bridgeexisting gaps but to propel compute continuums into a new era of efficiency, adaptability and security. The projectenvisions a future where compute continuums seamlessly integrate into various domains, fostering a holistic andintelligent computing environment that adapts to the ever-evolving demands of the digital landscape.

BioStimul - Experimental System for Wireless Stimulation and Monitoring of Selected Biological Properties and Cognitive Abilities of Drosophila melanogaster.
Duration:	1. 9. 2024 - 30. 6. 2027
Evidence number:	APVV-23-0173
Program:	APVV
Project leader:	Ing. Mgr. Andok Robert, PhD.
SAS cosolvers:	Ing. Mgr. Andok Robert, PhD., Ing. Benčurová Anna, Mgr. Gáliková Martina, PhD., Ing. Hricko Jaroslav, PhD., Ing. Klarák Jaromír, PhD., Mgr. et Mgr. Klepsatel Peter, PhD., Mgr. Knoblochová Diana, Ing. Konečníková Anna, Ing. Nemec Pavol, Ing. Predanocy Martin, PhD., Ing. Ritomský Mário
Annotation:	The fruit fly Drosophila melanogaster serves as one of the most versatile models for studying human diseases, including neurodegenerative or learning disorders. Thanks to the unique genetic tools available exclusively in the fly model, Drosophila considerably contributed to discoveries of genetic regulations behind processes such as learning and behavior. Nevertheless, progress in this research area is limited by available technologies for the stimulation and tracking fruit flies. This project aims to develop novel equipment for wireless stimulation and monitoring of insect behavior. A wireless micro-heater will be installed onto the Drosophila’s body, designed and developed within this project, together with the microsensor of position / force. The fly will be stimulated individually under certain circumstances by locally controlled heat induced in the micro-heater realized by connecting a nanometric diamond film (as a supporting material bilogically compatible with the examined tiny insects, and at the same time a material with excellent thermal conductivity) with a high density micro coil consisting of a closed LC resonant circuit with a high-k dielectric material (ZrO2, SrTiO3, HfO2) used for the micro-capacitor. By exerting electromagnetic waves of certain resonant frequency related to the size of the coil, electromagnetic induction will occur and the device will heat up stimulating the insect. The project aims to optimize and utilize this technology for the study of olfactory and social learning. The technology will nonetheless have a broad impact in other areas of Drosophila neuroscience, ethology and physiology. The system can be, for example, used also for wireless stimulation of flies in various types of learning experiments, for tracking fly behavior in complex environments, or for studies of behavioral roles of diverse genes and environmental factors. The suggested technology will have broad implications in both primary research and biomedicine.

INFOTICK - Getting the right info on ticks (INFOTICK)
Duration:	1. 7. 2023 - 30. 6. 2027
Evidence number:	APVV-22-0372
Program:	APVV
Project leader:	Ing. Gatial Emil, PhD.
SAS cosolvers:	Ing. Balogh Zoltán, PhD., MVDr. Derdáková Markéta, PhD., MVDr. Didyk Yuliya, PhD., Ing. Gatial Emil, PhD., Mgr. Chvostáč Michal, PhD., RNDr. Kazimírová Mária, CSc., Mgr. Mangová Barbara , PhD., Mgr. Peresh Yevheniy Yuliy, Mgr. Rusňáková Tarageľová Veronika, PhD., Mgr. Selyemová Diana, PhD., Mgr. Špitalská Eva, DrSc., Mgr. Šujanová Alžbeta, PhD., Mgr. Václav Radovan, PhD., Mgr. Zhovnerchuk Olha, PhD.
Annotation:	Despite the fact that the castor bean tick, Ixodes ricinus has been studied for a century, many questions regardingits ecology remains unanswered. Several aspects of its basic biology and phenology are still unexplored. Globalchanges, including climate shifts, transformation of the landscape and urbanization, contribute to the switch notonly in tick distribution, but also in bionomics and seasonal activity of ticks. The ornate dog tick, Dermacentorreticulatus adapts quickly to changing conditions and its range is expanding. There is the need for detaileddescription of areas where these ticks are found (natural as well as urban habitats), since their ranges havechanged during the last decades. The main risk factor for tick -exposed people in a given area is the density ofinfected questing ticks. In the proposed project, questing activity of ticks will be monitored using the tick -plotmethodology „tick gardens“ in field plots as well as flagging the vegetation for questing ticks. Using the tick-plotmethodology, we will also follow the tick life cycle and the seasonality of various developmental events (especiallymoulting) as well as the longevity of different life stages. Since these two species of ticks are consideredepidemiologically the most important, we will also identify the prevalence and occurrence of both pathogen infectedquesting ticks and infected ticks feeding on animals. Furthermore, with changing conditions, the invasion andoccurrence of „non-native“ species of ticks in Slovakia will be closely monitored since these emerging tick speciescan introduce new pathogens to our area. The information obtained by the research team during the project as wellas during previous studies will be transferred and used in the development of a mobile application for tickidentification and the creation of a website that will bring benefits to the general public and professionals tounderstand the risk of infection with the tick-borne pathogens.

Intelligent sensor systems and data processing
Duration:	1. 1. 2023 - 31. 12. 2026
Evidence number:	VEGA 2/0135/23
Program:	VEGA
Project leader:	Ing. Malík Peter, PhD.
SAS cosolvers:	Ing. Baláž Marcel, PhD., Ing. Bečková Jana, Ing. Budinská Ivana, PhD., Ing. Gatial Emil, PhD., Golestani shishvan Roya, MSc, Ing Hassankhani Dolatabadi Sepideh, PhD, Ing. Havlík Štefan, DrSc., Ing. Hricko Jaroslav, PhD., Ing. Kachman Ondrej, PhD., Ing. Kasanický Tomáš, Ing. Kašková Nikola, Ing. Kenyeres Martin, PhD., Ing. Klarák Jaromír, PhD., Ing. Krištofík Štefan, PhD., Ing. Lovíšková Jana, PhD., Mgr. Mojžiš Ján, PhD., Ing. Osadchyi Hryhorii, Ing. Zelenka Ján, PhD.
Annotation:	The central theme of Industry 4.0 and 5.0 is the digitization, intelligence and decentralization of management, so a key research is the new generation of smart sensors, able to cooperate and adapt to environment changes. This will be achieved by researching new methods of aggregating hyperspectral and multimodal data, as well as algorithms using artificial intelligence. The project is focused on intelligent algorithms for non-contact surface sensing in high-noise environments, which are able to learn the nature and noise distribution from data. This results in higher accuracy and greater noise robustness. The emphasis is on the classification and anomaly detection, which will bring more accurate and robust algorithms for use with the high noise content and long-tailed distribution that dominates in the common industrial environment. Research into aggregation algorithms for heterogeneous and multisensor data will bring new compensation mechanisms to suppress the effects of negative factors on sensor systems.

CFD simulations of tunnel fire and wildland fire using FDS
Duration:	17. 10. 2025 - 16. 10. 2026
Evidence number:	p1561-25-3
Program:	Iné projekty
Project leader:	Ing. Valášek Lukáš, PhD.
SAS cosolvers:	RNDr. Glasa Ján, CSc., Mgr. Kubišová Tatiana, Mgr. Weisenpacher Peter, PhD.

EnviroSens - Environmental sensors based on 2D nanomaterials
Duration:	1. 8. 2024 - 31. 7. 2026
Evidence number:	SK-BG-23-0017
Program:	APVV
Project leader:	RNDr. Kostič Ivan
SAS cosolvers:	Ing. Mgr. Andok Robert, PhD., Ing. Barák Vladislav, Ing. Benčurová Anna, Ing. Hrkút Pavol, CSc., Ing. Klarák Jaromír, PhD., Ing. Konečníková Anna, Ing. Predanocy Martin, PhD., Ing. Ritomský Mário, Ing. Škriniarová Jaroslava, CSc.
Annotation:	The objective of this project proposal is the research of new semiconducting 2D materials for application in environmental sensors. 2-dimensional (2D) materials have been at the forefront of materials research in recent years due to their unic electrical and optical properties and interesting mechanical properties deriving from their atomically thin dimensions. One of promising applications of 2D materials are chemical, environmental, and biological sensor devices based on such 2D materials. In this project, we will focus on the development of environmental sensors based on 2D materials with concentration on gas sensors.
Project website:	https://www.ui.sav.sk/w/odd/senzor/projekty/

ENEFS - Electrically enhanced wireless method for sensing mechanical quantities
Duration:	1. 1. 2024 - 30. 6. 2026
Evidence number:	09I05-03-V02-00041
Program:	Plán obnovy EÚ
Project leader:	Ing. Hricko Jaroslav, PhD.
SAS cosolvers:	Ing. Barák Vladislav, Ing. Bešina Ivan, Ing. Havlík Štefan, DrSc., Ing. Hricko Jaroslav, PhD., Ing. Klarák Jaromír, PhD., RNDr. Kostič Ivan, Ing. Mášiková Paulinová Marta, Ing. Ritomský Adrian, Ing. Ritomský Mário
Annotation:	Sensing physical quantities using sensors is a current topic for various research sectors, especially for industry, medicine, environmental research, etc. A special problem is sensing in inaccessible/dangerous environments, or where it is not possible to connect the sensor and the evaluation electronics using wires. The project focuses on the design of a sensor system for measuring mechanical quantities (force, vibration, pressure, deviations, etc.) using the principle of conversion to an electromagnetic quantity, especially for these applications. The basic principle of this new wireless sensor assumes a sensor that will consist of a deformable body, an active oscillator and an energy harvesting system, with which the active well will be excited. The inherent functionality of the active oscillator will create an electromagnetic field with its resonant frequency in its surroundings, which transmits information about the acting mechanical quantity. This electromagnetic field can then be captured using evaluation electronics.

Neuralsens - Smart gas and temperature sensors with neural-network-based low-level in-sensor data processing capability
Duration:	1. 1. 2024 - 30. 6. 2026
Evidence number:	09I05-03-V02-00058
Program:	Plán obnovy EÚ
Project leader:	Ing. Mgr. Andok Robert, PhD.
SAS cosolvers:	Ing. Mgr. Andok Robert, PhD., Ing. Nemec Pavol, Ing. Predanocy Martin, PhD., Ing. Škriniarová Jaroslava, CSc.
Other cosolvers:	p
Annotation:	A large number of sensing elements communicating with each other or with central control units is an integral part of the Internet of Things. The associated transmission and processing of an extreme amount of produced data is problematic. One of the solutions is processing of sensory data in close proximity to the sensor (near-sensor computing) or directly in the sensor (in-sensor computing), which radically reduces the requirements for their subsequent transmission and processing. In this project, we focus on the development of resistive gas and temperature sensors implemented into synaptic matrix of a hardware neural network, enabling low-level processing of measured sensory data directly in this network using a hardware algorithm. In the project, we will develop a methodology to calculate this algorithm and to encode it into the sensor matrix. This methodology will be one of the outputs of the project with the potential for wider application in hardware neural networks.
Project website:	https://neuralsens.org/

SILVANUS-SK - Research and development of selected innovative technologies for a forest fire management platform
Duration:	1. 1. 2025 - 30. 6. 2026
Evidence number:	09I01-03-V04-00107
Program:	Plán obnovy EÚ
Project leader:	Ing. Balogh Zoltán, PhD.
SAS cosolvers:	Ing. Darjaa Sakhia, PhD., Ing. Gatial Emil, PhD., Ing Hassankhani Dolatabadi Sepideh, PhD, Ing. Kasanický Tomáš, Ing. Rusko Milan, PhD., Mgr. Sabo Róbert, PhD., Ing. Trnka Marian, Ing. Zelenka Ján, PhD.
Annotation:	The project deals with the extended research and development of selected concepts and technology approaches for an integrated information platform for forest fire management, originally developed within the H2020 project SILVANUS.

Low Cost Oxides - Research into the technology for manufacturing low-cost oxide-based semiconductor electronic devices for IoT and sensor applications
Duration:	1. 1. 2024 - 1. 6. 2026
Evidence number:	09I05-03-V02-00030
Program:	Plán obnovy EÚ
Project leader:	Ing. Mgr. Andok Robert, PhD.
SAS cosolvers:	Ing. Mgr. Andok Robert, PhD., Ing. Barák Vladislav, Ing. Benčurová Anna
Annotation:	Sol-gel inkjet printing and chemical vapor deposition are low-cost techniques for the deposition of thin oxide semiconductor films and the preparation of electronic devices. They offer several advantages over standard techniques, including simplicity, low manufacturing costs, scalability, and the ability to deposit layers even at low temperatures and without the need for a vacuum. These techniques have the potential to revolutionize the production of oxide semiconductor devices and enable their application in a wide range of applications. The proposed project investigates these advanced deposition techniques and results in proof-of-concept oxide semiconductor devices. Low-cost deposition techniques can be optimized to be more energy-efficient and environmentally friendly, contributing to more sustainable semiconductor production. As costs decrease, previously expensive technologies can become more accessible to marginalized or developing regions.

DICRIS - Digital Technologies for Critical Infrastructures (DICRIS)
Duration:	1. 8. 2024 - 31. 3. 2026
Evidence number:	09I05-03-V02-00055
Program:	Plán obnovy EÚ
Project leader:	doc. Ing. Hluchý Ladislav, CSc.
SAS cosolvers:	Ing. Astaloš Ján, Ing. Balogh Zoltán, PhD., prof. Mgr. Beňuš Štefan, PhD., Mgr. Bobák Martin, PhD., Ing. Budinská Ivana, PhD., Ing. Darjaa Sakhia, PhD., Ing. Dlugolinský Štefan, PhD., Ing. Dora Jean Rosemond, PhD., doc. Ing. Forgáč Radoslav, PhD., Ing. Gatial Emil, PhD., RNDr. Glasa Ján, CSc., Ing. Habala Ondrej, Ing. Javurek Martin, PhD., Ing. Kachman Ondrej, PhD., Ing. Kasanický Tomáš, Ing. Klarák Jaromír, PhD., Ing. Krammer Peter, Ing. Krištofík Štefan, PhD., Mgr. Kubišová Tatiana, Ing. Malík Peter, PhD., Ing. Mášiková Paulinová Marta, Mgr. Mojžiš Ján, PhD., doc. Ing. Očkay Miloš, PhD., Ing. Rusko Milan, PhD., Mgr. Sabo Róbert, PhD., Ing. Skovajsová Lenka, PhD., Ing. Staňo Michal, Mgr. Šeleng Martin, PhD., Ing. Tran Viet, PhD., Ing. Trnka Marian, Ing. Valášek Lukáš, PhD., Mgr. Weisenpacher Peter, PhD., Ing. Zelenka Ján, PhD.
Annotation:	To advance foundational scientific knowledge and design methodologies necessary foraccelerating the digital transformation of the Slovak power industry. This comprehensive research anddevelopment effort aims primarily at creating and integrating digital twin technology for criticalinfrastructure components of the Slovak electric transmission system. Additionally, it includes thedevelopment of predictive analytical models and a context-aware decision support empowered with humanvoice processing capabilities in Slovak. The ultimate goal is to enhance the safety, security, and reliability ofthe electric power grid while driving broader digital transformation across various economic sectors.

Pefect AI Sommel - -
Duration:	27. 1. 2025 - 31. 3. 2026
Evidence number:	09I05-03-V03-00022
Program:	Plán obnovy EÚ
Project leader:	Ing. Budinská Ivana, PhD.
SAS cosolvers:	Ing. Bečková Jana, Ing. Benčurová Anna, doc. Ing. Čapkovič František, CSc., Ing. Hricko Jaroslav, PhD., Ing. Hrkút Pavol, CSc., Ing. Kasanický Tomáš, Ing. Kenyeres Martin, PhD., Ing. Krištofík Štefan, PhD., Ing. Lovíšková Jana, PhD., Ing. Malík Peter, PhD., Mgr. Mojžiš Ján, PhD., Ing. Nemec Pavol, Ing. Ritomský Mário, RNDr. Svíteková Danica, Ing. Valášek Lukáš, PhD., Ing. Zelenka Ján, PhD.
Annotation:	The project provides a set of tools with potential to promote and facilitate awareness issue adulterationand counterfeiting of wine. New applied methods for testing with a cloud- solution (robust library andmobile app) will make testing and detecting more affordable. More testing and more successfuldetection shall be of benefits not only on corporate level (direct impact on profitability of esp. smallwine producers) but even on policy making level (detection and taking measure against economiclosses caused by adulteration and counterfeiting). Bearing in mind new generation of wine producers,more open to use new technologies and apply data into their business, the mobile app is an idealsolution. There is special attention given to small wine producers, because their economic loses hasdirect impact on local economy and local employment. By providing them with affordable tool howto prove the authenticity of their products, the new possibility in building their name with particularemphasis on the local production and tradition has potential to win their share within the market. So,the profitability of small wine producers is key to local development, and the positive elements canbe recognized among wine associates and even among the food sector as such.

SCDI - Slovac Digital Innovation Hub
Duration:	1. 4. 2024 - 31. 3. 2026
Evidence number:
Program:	Plán obnovy EÚ
Project leader:	Ing. Budinská Ivana, PhD.
Project website:	https://www.scdi.tech/