arXiv subjects

Eleftheria Katsiri

Publications and source records attributed to Eleftheria Katsiri.

9 recordsLinked to original sources

arXiv2025

E-polis: Gamifying Sociological Surveys through Serious Games -- A Data Analysis Approach Applied to Multiple-Choice Question Responses Datasets

E-polis is a serious digital game designed to gamify sociological surveys studying young people's political opinions. In this platform game, players navigate a digital world, encountering quests posing sociological questions. Players' answers shape the city-game world, altering building structures based on their choices. E-polis is a serious game, not a government simulation, aiming to understand players' behaviors and opinions thus we do not train the players but rather understand them and help them visualize their choices in shaping a city's future. Also, it is noticed that no correct or incorrect answers apply. Moreover, our game utilizes a novel middleware architecture for development, diverging from typical asset prefab scene and script segregation. This article presents the data layer of our game's middleware, specifically focusing on data analysis based on respondents' gameplay answers. E-polis represents an innovative approach to gamifying sociological research, providing a unique platform for gathering and analyzing data on political opinions among youth and contributing to the broader field of serious games.

cs.HC↗

arXiv2025

Knowledge representation and scalable abstract reasoning for simulated democracy in Unity

We present a novel form of scalable knowledge representation about agents in a simulated democracy, e-polis, where real users respond to social challenges associated with democratic institutions, structured as Smart Spatial Types, a new type of Smart Building that changes architectural form according to the philosophical doctrine of a visitor. At the end of the game players vote on the Smart City that results from their collective choices. Our approach uses deductive systems in an unusual way: by integrating a model of democracy with a model of a Smart City we are able to prove quality aspects of the simulated democracy in different urban and social settings, while adding ease and flexibility to the development. Second, we can infer and reason with abstract knowledge, which is a limitation of the Unity platform; third, our system enables real-time decision-making and adaptation of the game flow based on the player's abstract state, paving the road to explainability. Scalability is achieved by maintaining a dual-layer knowledge representation mechanism for reasoning about the simulated democracy that functions in a similar way to a two-level cache. The lower layer knows about the current state of the game by continually processing a high rate of events produced by the in-built physics engine of the Unity platform, e.g., it knows of the position of a player in space, in terms of his coordinates x,y,z as well as their choices for each challenge. The higher layer knows of easily-retrievable, user-defined abstract knowledge about current and historical states, e.g., it knows of the political doctrine of a Smart Spatial Type, a player's philosophical doctrine, and the collective philosophical doctrine of a community players with respect to current social issues.

cs.MA↗

arXiv2024

Federated Anomaly Detection for Early-Stage Diagnosis of Autism Spectrum Disorders using Serious Game Data

Early identification of Autism Spectrum Disorder (ASD) is considered critical for effective intervention to mitigate emotional, financial and societal burdens. Although ASD belongs to a group of neurodevelopmental disabilities that are not curable, researchers agree that targeted interventions during childhood can drastically improve the overall well-being of individuals. However, conventional ASD detection methods such as screening tests, are often costly and time-consuming. This study presents a novel semi-supervised approach for ASD detection using AutoEncoder-based Machine Learning (ML) methods due to the challenge of obtaining ground truth labels for the associated task. Our approach utilizes data collected manually through a serious game specifically designed for this purpose. Since the sensitive data collected by the gamified application are susceptible to privacy leakage, we developed a Federated Learning (FL) framework that can enhance user privacy without compromising the overall performance of the ML models. The framework is further enhanced with Fully Homomorphic Encryption (FHE) during model aggregation to minimize the possibility of inference attacks and client selection mechanisms as well as state-of-the-art aggregators to improve the model's predictive accuracy. Our results demonstrate that semi-supervised FL can effectively predict an ASD risk indicator for each case while simultaneously addressing privacy concerns.

cs.CY↗

arXiv2024

Streamline Intelligent Crowd Monitoring with IoT Cloud Computing Middleware

This article introduces a novel middleware that utilizes cost-effective, low-power computing devices like Raspberry Pi to analyze data from wireless sensor networks (WSNs). It is designed for indoor settings like historical buildings and museums, tracking visitors and identifying points of interest. It serves as an evacuation aid by monitoring occupancy and gauging the popularity of specific areas, subjects, or art exhibitions. The middleware employs a basic form of the MapReduce algorithm to gather WSN data and distribute it across available computer nodes. Data collected by RFID sensors on visitor badges is stored on mini-computers placed in exhibition rooms and then transmitted to a remote database after a preset time frame. Utilizing MapReduce for data analysis and a leader election algorithm for fault tolerance, this middleware showcases its viability through metrics, demonstrating applications like swift prototyping and accurate validation of findings. Despite using simpler hardware, its performance matches resource-intensive methods involving audiovisual and AI techniques. This design's innovation lies in its fault-tolerant, distributed setup using budget-friendly, low-power devices rather than resource-heavy hardware or methods. Successfully tested at a historical building in Greece (M. Hatzidakis' residence), it is tailored for indoor spaces. This paper compares its algorithmic application layer with other implementations, highlighting its technical strengths and advantages. Particularly relevant in the wake of the COVID-19 pandemic and general monitoring middleware for indoor locations, this middleware holds promise in tracking visitor counts and overall building occupancy.

cs.DC↗

arXiv2023

E-polis: A serious game for the gamification of sociological surveys

E-polis is a multi-platform serious game that gamifies a sociological survey for studying young people's opinions regarding their ideal society. The gameplay is based on a user navigating through a digital city, experiencing the changes inflicted, triggered by responses to social and pedagogical surveys, known as "dilemmas". The game integrates elements of adventure, exploration, and simulation. Unity was the selected game engine used for the development of the game, while a middleware component was also developed to gather and process the users' data. At the end of each game, users are presented with a blueprint of the city they navigated to showcase how their choices influenced its development. This motivates them to reflect on their answers and validate them. The game can be used to collect data on a variety of topics, such as social justice, and economic development, or to promote civic engagement and encourage young people to think critically about the world around them.

cs.CY↗

arXiv2023

Serious Games in Digital Gaming: A Comprehensive Review of Applications, Game Engines and Advancements

Serious games are defined as applied games that focus on the gamification of an experience (e.g., learning and training activities) and are not strictly for entertainment purposes. In recent years, serious games have become increasingly popular due to their ability to simultaneously educate and entertain users. In this review, we provide a comprehensive overview of the different types of digital games and expand on the serious games genre while focusing on its various applications. Furthermore, we present the most widely used game engines used in the game development industry and extend the Unity game machine advantages. Lastly, we conclude our research with a detailed comparison of the two most popular choices (Unreal and Unity engines) and their respective advantages and disadvantages while providing future suggestions for serious digital game development.

cs.SE↗

arXiv2022

A Blockchain Cloud Computing Middleware for Academic Manuscript Submission

One of the most important tasks in scientific publishing is the articles' evaluation via the editorial board and the reviewers' community. Additionally, in scientific publishing great concern exists regarding the peer-review process and how it can be further optimised to decrease the time from submission to the first decision, as well as increase the objectivity of the reviewers' remarks ensuring that no bias or human error exists in the reviewing process. In order to address this issue, our article suggests a novice cloud framework for manuscript submission based on blockchain technology that further enhances the anonymity between authors and reviewers alike. Our method covers the whole spectrum of current submission systems capabilities, but it also provides a decentralised solution using open-source tools such as Java Spring that enhance the anonymity of the reviewing process.

cs.DC↗

arXiv2022

A Method for Counting, Tracking and Monitoring of Visitors with RFID sensors

This publication presents a method responsible for counting tracking and monitoring visitors inside a building. The site examined is Manos Hatzidakis' House, situated in Xanthi. Specifically, we have conducted a study, which provides recommendations, regarding the installation of sensors in the building. We also present the communication protocols of the computer network used in order to ensure the efficient communication between the space examined and the sensor network. Finally, we describe the process of creating a website, which is designed to store and view the data.

cs.SE↗

arXiv2022

Crowd tracking and monitoring middleware via Map-Reduce

This paper presents the design, implementation, and operation of a novel distributed fault-tolerant middleware. It uses interconnected WSNs that implement the Map-Reduce paradigm, consisting of several low-cost and low-power mini-computers (Raspberry Pi). Specifically, we explain the steps for the development of a novice, fault-tolerant Map-Reduce algorithm which achieves high system availability, focusing on network connectivity. Finally, we showcase the use of the proposed system based on simulated data for crowd monitoring in a real case scenario, i.e., a historical building in Greece (M. Hatzidakis' residence).The technical novelty of this article lies in presenting a viable low-cost and low-power solution for crowd sensing without using complex and resource-intensive AI structures or image and video recognition techniques.

cs.DC↗