Category: Cross-project collaboration

Mr. Luka Jeremic defended his MSc thesis on 23 October 2024. The title of the thesis was AI and applications in medicine. His research was mentored by HPC4S3ME team members and it was done in the context of AI master program at the Faculty for information systems and technologie at UDG. This program and Master students are supporter by EUROCC NCC Montenegro.

ABSTRACT – This research explores the application of artificial intelligence in medicine, with a focus on the classification of brain, liver, and blood cell diseases. The main objective is to evaluate the effectiveness of algorithms in recognizing and classifying diseases of these organs. Through the development of a prototype information system, the study analyzes how artificial intelligence can improve diagnostics and contribute to the advancement of personalized medicine. The methodology includes a literature review, the development of computer vision models, and the assessment of model accuracy using real medical data. The results show that models based on deep neural networks can enhance the accuracy and speed of diagnostics, allowing for more precise disease classification. The paper also highlights the barriers and challenges in implementing these technologies,
including the need for ethical considerations and training of medical staff. The conclusions suggest that this approach has the potential to significantly improve medicine, but further research and refinement are necessary.

Ms. Sara Kovacevic defended her BSc thesis on the use of AI tools to create a hotel chat bot receptionis for smart hospiality. This research was doen in the context of HPC4S3ME with the support from NCC Montengro an HPC4S3ME. The results were pulished at the IEEE IT2024 conference. The future work will include experimenting with HPC to run different AI tools and models. Her fefence took place on 3 October 2024.

ABSTRACT – The aim of this thesis is to examine the advancements and applications of chatbots in hotels to enhance customer experience and operational efficiency in Montenegro, which aspires to become a prestigious tourist destination. Emphasis is placed on the use of artificial intelligence (AI), machine learning (ML), and high-performance computing (HPC) to develop advanced digital solutions. The automation of guest communication through chatbots reduces the burden on staff and increases customer satisfaction, especially during the tourist season when there are significant fluctuations in the number of visitors. The research analyzes key aspects of implementing chatbot technology, including the challenges and benefits of using the Voiceflow platform for development and testing. It studies data on guest preferences and service personalization, contributing to a better understanding of user needs and tailoring hotel offerings to meet their expectations. The thesis advises further optimization of chatbot functionalities, staff training, and regular collection of guest feedback. These recommendations enable Montenegrin hotels to improve their offerings and stand out in the global market competition. This work represents an important contribution to the advancement of digital solutions in Montenegro and can serve as a starting point for future research.

Mr Marko Lasice defended his BSc thesis on AI powered real estate pricing. The future work will include larger datasets and explorig the use of HPC and AI to train more precise price estimation models. The work was supported by the NCC Montenegro and HPC4S3ME team members.

ABSTRACT – The development of generative models and exponential progress in artificial intelligence have opened up new application possibilities in many areas of economic life. One of the possibilities is developing an AI model for predicting market prices based on data extracted from the web. This paper introduces the reader to the technique of automated downloading and grouping of data from the web, known as web scraping, and the development of a predictive model that, based on the collected data, would predict real estate prices. The paper presents the practical part of the work, the implementation of a predictive model developed using the decision tree technique. In conclusion, the work contributes to the understanding of how the combination of these techniques improves decision-making processes in the real estate market.

Ms. Jovana Mitric defended her BSc thesis at the Faculty for information sciences and technologies on 3 October, 2024. The topoc was on AI and machine learning for applications in cultural heritage preservation. This research was done in the context of HPC4S3ME project and was supported by the NCC Montenegro team. The future work will explore the use of HPC and expanded datasets to refine and train better models for monuments detection and providing support for Montenegrin tourism development. This work was also successfully presented at the IEEE IT2024 conference.

ABSTRACT – This thesis presents research on artificial intelligence (AI) and machine learning (ML), and their potential application in the preservation of cultural heritage, with a special focus on Montenegro. Computer vision, as a specific field of artificial intelligence, was explored. The paper addresses the implementation of modern technologies, specifically computer vision, in the field of cultural tourism to enhance the visibility and preservation of cultural monuments. By using available tools such as the Roboflow platform for image annotation and Google Colaboratory for model training, a web application was developed using the Flask framework, which recognizes cultural monuments based on images, powered by the YOLO v8 model. Additionally, the thesis discusses the broader context of AI applications in the preservation of cultural heritage and its promotion for tourism purposes, with particular emphasis on the potential for technological enhancement of Montenegro’s tourism offerings. The importance of digital transformation in tourism for Montenegro and its positioning in the global tourism market is highlighted.