We have implemented a very successful round table event with panel discussions on HPC/AI and its relation to priorities identified in Montenegrin S3, namely agriculture and food production, health and tourism, and energy. We had panelists from Slovenia, Bosnia, Serbia and Montenegro. The event is organized by EuroCC NCC Monteengro in collaboration with NCC Slovenia. The agenda is available by clicking the following link.
Round Table on HPC/AI and Montenegrin S3
The event took place at the UDG, in a full amphitheater AS on Saturday, 26.02.2022. The panelists gave interesting presentations, considerations, presented project results, and there was a very interesting discussion and Q&A session at the end. The event was attended by students, professors, and industry representatives. The event was advertised locally and nationally via national news portals.
Round Table: HPC/AI and Montenegrin S3Panelist gave talks, presented project results, and participated in Q&AFinally, face 2 face events, amphitheater AS
University of Donja Gorica (UDG) will organize a round table which will be held on Saturday 26.02.2022. at 10:00 at the University of Donja Gorica (UDG) in amphitheater AS. The round table will be organized on the topic of Driving the future with HPC and AI innovations in Smart Specialization Areas in Montenegro in the framework of the project“EuroCC – National Competence Centre in the area of high-performance computing (HPC)” which aims to establish a network of national centres of competence for high-performance computing in 33 member states of the Joint Undertaking for European High Performance Computing (EuroHPC JU) within Horizont2020 programme.
Click on image to open Agenda
The aim of the round table is to awake interest in this area among participants, companies and students who are interested in learning more, and especially to inform them about the possibilities of using and applying advanced HPC (High Performance Computing) technologies and AI in various fields such as agriculture, tourism and medicine.
The round table will be opened by Rector of UDG, prof. dr Veselin Vukotic, while prominent experts in this field, as well as students of doctoral and postgraduate master’s studies, will have their presentations on this topic. The round table will be held on Saturday, 26.02.2022. starting at 10:00 at the University of Donja Gorica, amphitheater AS and detailed information can be found in the Agenda attached (link).
IT2022 Conference and EuroCC Workshop on HPC and AI were featured in national news portals today. Most notably we got coverage in CDM and AntenaM. For that purpose EuroCC Montenegro prepared a short video covering the conference and workshop activities.
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EuroCC Montenegro and UDG took part in the organization of the 26th International Conference on Information Technology, IEEE IT2022. The conference was organized in a virtual setting this year. More information about the conference is available here.
EuroCC project was presented by Dr Luka Filipovic in the session dedicated to presentation of project results for the projects implemented in Montenegro and the region. Besides EuroCC itself, in this session Mr Stevan Cakic gave a presentation of AIMHiGH project that is done in the context of H2020 FF4EuroHPC experiments and EuroCC/UDG is a partner. This session took place on 16 February 2022.
Successful wrap up of the 26th IEEE IT conference IT2022
Also, the 2nd EuroCC Workshop on High-Performance Computing, High-Performance Data Analytics, and Artificial Intelligence. We had presenters from Slovenia, Croatia, Cyprus, Czechia, Netherlands , Serbia, and Montenegro. This event was organized in a hybrid setting where we had around 10-15 attendees at the UDG (EuroCC Montenegro), and over 40 attendees via Zoom. The workshop was split into 4 afternoon sessions spread over two days on 17-18 February. The workshop was attended by the representatives of Montenegrin academia and students (UDG, UCG), industry, and partners More details on the workshop will follow soon. The program agenda is available here.
Hybrid setting of the EuroCC Workshop during IEEE 2022
In four sessions dedicated to paper presentations, there was over 30 papers presented, several of which were related to AI and machine learning. Ms Zoja Scekic, a young researcher and student from UDG, presented a paper on the use of AI/ML for computer vision applications in Smart Parking.
Paper on the use of AI/ML for Parking Occupancy Detection
The day-ahead energy market lets market participants commit to buy or sell wholesale electricity one day before the operating day, to help avoid price volatility. Forecasting day-ahead electricity prices and loads creates basis for decision making in this process. Mr. Milutin Pavićević, a young researcher from the University of Donja Gorica , explored the possibility to utilize artificial neural networks in order to improve the forecasting day-ahead electricity prices and loads based on the historical data. This was the topic of his Master thesis research work done under supervision of professor Tomo Popovic, which finally resulted in a scientific article published in MDPI journal Sensors. The paper is titled ”Forecasting Day-Ahead Electricity Metrics with Artificial Neural Networks” within the Special Issue Complex Data Processing Systems and Computing Algorithms: New Concepts and Applications.
During this research effort the researchers engaged the domain experts which provided us with generous help in obtaining datasets and understanding the problem of day-ahead consumption, spot price prediction, and the electricity market. The results show the promising efficiency of AI and machine learning for the task of short-term prediction of electricity metrics. With the support of EuroCC Montenegro, the future work will include experimenting on the HPC infrastructure and creation of an industry pilot demonstration for the energy sector.
Forecasting Day-Ahead Electricity Metrics with Machine Learning
ABSTRACT – As artificial neural network architectures grow increasingly more efficient in time-series prediction tasks, their use for day-ahead electricity price and demand prediction, a task with very specific rules and highly volatile dataset values, grows more attractive. Without a standardized way to compare the efficiency of algorithms and methods for forecasting electricity metrics, it is hard to have a good sense of the strengths and weaknesses of each approach. In this paper, we create models in several neural network architectures for predicting the electricity price on the HUPX market and electricity load in Montenegro and compare them to multiple neural network models on the same basis (using the same dataset and metrics). The results show the promising efficiency of neural networks in general for the task of short-term prediction in the field, with methods combining fully connected layers and recurrent neural or temporal convolutional layers performing the best. The feature extraction power of convolutional layers shows very promising results and recommends the further exploration of temporal convolutional networks in the field.
The paper can be accessed at the Sensors website at the following link.
FF4EuroHPC experiment update: How to use AI and ML in agriculture sector? The idea of this experiment is to monitor the number of chickens, their weight and other parameters with the help of AI and a camera in which AI models will be integrated, and placed on poultry farms. Find more information here (based on FF4EuroHPC post on LinkedIn).
Currently developing AI prediction models for object detection and object segmentation
EuroCC Monteengro and UDG are participating in the FF4EuroHPC experiment – AIMHiGH. Currently working on the ML models to be used for the development of IoT edge sensors to count the number of chickens in an image and/or video and estimate growth. The goal of the AIMHiGH experiment is to validate the use of HPC in AI/ML training and evaluate acceleration in the development of these prediction models. Learn more about the FF4EuroHPC project and experiments at the following link.
Development of computer vision for Edge-IoT in agriculture
