{"id":39445,"date":"2026-04-17T12:47:15","date_gmt":"2026-04-17T12:47:15","guid":{"rendered":"https:\/\/new.dotsoft.gr\/research_and_development\/"},"modified":"2026-07-01T09:48:15","modified_gmt":"2026-07-01T09:48:15","slug":"research_and_development","status":"publish","type":"page","link":"https:\/\/dotsoft.gr\/en\/research_and_development\/","title":{"rendered":"Research and Innovation Department"},"content":{"rendered":"\t\t
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\n\t\t\t\tWe innovate today for the solutions of tomorrow\t\t\t\t\t\n\t\t\t\t\t\t\t<\/h2>\n\t\t<\/div>\n\t\t\n\t<\/div>\n<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\n\t\t\t\t\t\tDr. Despina Elisavet Filippidou \t\t\t\t\t<\/span>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t

\n\t\t\t\tHead of Innovation Start Hub\t\t\t\t\t\n\t\t\t\t\t\t\t<\/h4>\n\t\t<\/div>\n\t\t\n\t<\/div>\n<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\tinnovation@dotsoft.gr\t\t\t\t\t\n\t\t\t\t\t\t\t<\/h4>\n\t\t<\/div>\n\t\t\n\t<\/div>\n<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n <\/i> <\/div>\n \n
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The Research and Innovation Department ensures that DOTSOFT remains at the forefront of technological developments, strengthening its long\u2011term competitiveness and laying the foundations for the company\u2019s sustainable growth.<\/div>\n
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DOTSOFT\u2019s Research and Innovation Department is the key driver of the company\u2019s technological advancement and differentiation, shaping the future of the solutions it offers. Through continuous participation in European and international research programs, the company maintains an active presence in the innovation ecosystem and integrates the latest technological developments into its services. <\/p>

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The Department operates as a dynamic knowledge hub, where research, technology, and business application come together to create new products and services. Through collaborations with universities, research institutions, and international organizations, access to cutting\u2011edge expertise is ensured, enabling the development of high\u2011value solutions. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\tOur activities include:\t\t\t\t\t\n\t\t\t\t\t\t\t<\/h3>\n\t\t<\/div>\n\t\t\n\t<\/div>\n<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\r\n Design, writing, and implementation of R&D projects in European programs (Horizon Europe, Digital Europe, Interreg, etc.) <\/h5>\r\n \r\n
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\r\n Development of prototypes (proof of concept) and pilot applications <\/h5>\r\n \r\n
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\r\n Research and development in fields such as Artificial Intelligence, Internet of Things, Big Data, and Cloud Technologies <\/h5>\r\n \r\n
\r\n <\/div>\r\n \r\n <\/div> \r\n <\/div>\r\n<\/div>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\r\n Exploration of new business models and digital services <\/h5>\r\n \r\n
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\r\n Transfer of know\u2011how from research to commercial exploitation <\/h5>\r\n \r\n
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\n\t\t\t\tPublications \u2013 Presentations \u2013 Case Studies\t\t\t\t\t\n\t\t\t\t\t\t\t<\/h3>\n\t\t<\/div>\n\t\t\n\t<\/div>\n<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\r\n \r\n <\/i> <\/span>\r\n Knowledge Graphs and Machine Learning in Fake News and Misinformation Detection

<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
    The rise of digital platforms has accelerated the spread of misinformation, creating significant social, political, and economic challenges. Knowledge Graphs (KGs) are emerging as effective tools for improving the accuracy, interpretability, and scalability of fake\u2011news detection systems, addressing limitations of traditional machine\u2011learning approaches that rely mainly on linguistic analysis.
    \n
    \nThis work includes a literature review synthesizing findings from recent studies on the application of Knowledge Graphs in misinformation detection. It examines how KGs enhance detection by capturing real\u2011world relationships, analyzing context, and improving model interpretability, while also discussing existing limitations related to scalability, data completeness, and adaptation to specific contexts.
    \n
    \nThe reviewed studies highlight the need for future research focused on developing scalable, real\u2011time, and cross\u2011lingual Knowledge Graph models to strengthen global misinformation\u2011detection capabilities.

    \n
    \nAdditionally, preliminary results from two use cases are presented, showcasing a methodology for constructing Knowledge Graphs that can serve as a valuable tool for addressing the spread of misinformation.
      <\/div>\r\n <\/div>\r\n
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      \r\n \r\n <\/i> <\/span>\r\n Dynamic Demand Forecasting with AI: Maximizing Value in the Supply Chain<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
        This work presents the development of a dynamic demand\u2011forecasting platform designed to accurately predict demand and quantify its added value in supply\u2011chain management, leveraging advanced machine\u2011learning algorithms and operational management techniques.

        \n
        \nThe platform collects and processes real\u2011time data from multiple sources, such as point\u2011of\u2011sale systems, e\u2011commerce transactions, competitor pricing policies, weather conditions, and consumer\u2011sentiment data. By integrating environmental and product\u2011related parameters, the platform optimizes inventory levels, delivery routing, and overall operational efficiency.
        \n
        \nThe solution achieves high forecasting accuracy by utilizing models such as XGBoost and Support Vector Regression (SVR), which consistently outperform traditional forecasting methods. At the same time, it is designed to be scalable, cost\u2011effective, and user\u2011friendly, making it particularly suitable for small and medium\u2011sized enterprises (SMEs), which often face technological and financial constraints when adopting advanced forecasting systems.
        \n
        \nThe implementation of the system significantly enhances decision\u2011making processes, leading to reduced operational costs and improved customer satisfaction.
          <\/div>\r\n <\/div>\r\n
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          \r\n \r\n <\/i> <\/span>\r\n Real\u2011World Case Study on Sales Forecasting Using Artificial Intelligence<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
            28th Panhellenic Conference on Informatics (PCI), 13\u201315 December 2024, Athens, Greece
            \n
            \nAccurate sales forecasting is a critical factor for optimizing operations and supporting strategic decision\u2011making in the e\u2011commerce sector. This work presents a comprehensive review of existing literature on sales\u2011forecasting algorithms, covering both traditional statistical approaches and advanced artificial intelligence (AI) techniques.

            \n
            \nUsing a dataset from one of the largest e\u2011commerce companies in Greece, multiple AI\u2011based models are applied to predict sales trends. The preliminary results highlight the effectiveness of AI algorithms in identifying complex patterns within the data, achieving higher forecasting accuracy compared to conventional methods\u2014particularly when semantic data from external sources, such as weather conditions and Google Trends, are incorporated.
            \n
            \nThese findings underscore the potential of integrating artificial intelligence into sales\u2011forecasting processes, contributing to enhanced competitiveness and operational efficiency for e\u2011commerce businesses.
              <\/div>\r\n <\/div>\r\n
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              \r\n \r\n <\/i> <\/span>\r\n White Paper: Cancer Survivorship and AI for Well\u2011Being \u2013 A Collaborative Approach of European Research Projects<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                A White Paper has been published presenting the results of the collaboration among 11 CORDIS projects, offering valuable recommendations and directions for future research in the fields of well\u2011being, cancer, and artificial intelligence in health.
                \n
                \nThis document is the outcome of synergies among multiple Horizon 2020 projects participating in the cluster \u201cCancer Survivorship and AI for Wellbeing (CS\u2011AIW)\u201d, aiming to promote innovative approaches that enhance the quality of life and care of cancer survivors.
                \n
                \nThe BD4QoL project made a substantial contribution, particularly in Chapter 4, titled \u201cLessons learned from our collaboration\u201d, which focuses on the insights and conclusions derived from the cooperation among the research projects.
                  <\/div>\r\n <\/div>\r\n
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                  \r\n \r\n <\/i> <\/span>\r\n Smartphone\u2011Based Strategy for Monitoring Quality of Life in Head and Neck Cancer Survivors
                  <\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                    Part of the book series Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST, Volume 488)
                    \n
                    \nSmartphone\u2011based IoT systems have the potential to effectively predict and monitor Quality\u2011of\u2011Life (QoL) indicators when designed with an appropriate methodology. This work aims to develop a comprehensive strategy for creating a specialized QoL\u2011monitoring application for head and neck cancer survivors.
                    \n
                    \nFirst, the results of a literature review on mHealth services for cancer patients are presented. Then, the clinical study protocol is described in detail, within which patients are encouraged to:
                    \n
                    \n
                  • apply self\u2011management practices through active symptom tracking,
                    maintain healthy lifestyle habits,
                    interact with embedded artificial intelligence that serves as an additional communication channel between patient and clinician,
                    \n
                  • complete standardized QoL questionnaires via a web platform from home.
                    \n
                    \nThe challenges encountered, the selected non\u2011invasive data\u2011collection procedures, and the qualitative data derived from physical, social, and behavioral indicators together form a valuable set of guidelines and requirements for future research efforts focused on post\u2011treatment cancer\u2011patient monitoring using portable IoT devices.
                      <\/div>\r\n <\/div>\r\n
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                      \r\n \r\n <\/i> <\/span>\r\n Multicenter Randomized Trial for Assessing Quality of Life Using Non\u2011Invasive Intelligent Tools During Post\u2011Curative Follow\u2011up of Head and Neck Cancer Patients<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                      • Head and Neck Medical Oncology Department, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Istituto Nazionale dei Tumori, Milan, Italy
                      • Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
                      • Oslo Center for Biostatistics and Epidemiology, University of Oslo, Oslo, Norway
                      • Oslo Center for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway
                      • Universidad Polit\u00e9cnica de Madrid-Life Supporting Technologies Research Group, ETSIT, Madrid, Spain
                      • Applied Research Division for Cognitive and Psychological Science, IEO, European Institute of Oncology IRCCS, Milan, Italy
                      • Department of Psychology, Educational Science and Human Movement (SPPEFF), University of Palermo, Palermo, Italy
                      • Information Technology Programme Management Office, DOTSOFT, Thessaloniki, Greece
                      • DeustoTech, Faculty of Engineering, Universidad de Deusto, Bilbao, Spain
                      • Institute of head and neck studies and Education, University of Birmingham, Birmingham, United Kingdom
                      • Division of Epidemiology and Health Care Research, JGU \u2013 Johannes Gutenberg University, Mainz, Germany
                      • Division of Oral and Maxillofacial Surgery \u2013 Bristol Dental Hospital, University of Bristol \u2013 Bristol Medical School, Bristol, United Kingdom
                      • Maxillo-Facial Surgery, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
                      • Maxillo-Facial Surgery, Interdisciplinary Department of Medicine, University of Bari \u201cAldo Moro\u201d, Bari, Italy
                      • MultiMed Engineers srls, Parma, Italy
                        \n
                        \nHead and neck cancer (HNC) survivors face significant physical, psychological, and socioeconomic burdens. Achieving cancer\u2011free survival while maintaining a high quality of life (QoL) is a central goal in the management of HNC patients, making lifelong follow\u2011up essential.
                        \n
                        \nA particularly ambitious objective is to implement this follow\u2011up through advanced analysis of environmental, emotional, and behavioral data discreetly collected via mobile devices.
                        \n
                        \nThis clinical study aims to reduce the proportion of HNC survivors\u2014who have completed treatment between 3 months and 10 years prior\u2014experiencing clinically significant QoL deterioration during follow\u2011up, by leveraging non\u2011invasive tools such as patients\u2019 mobile devices.
                        \n
                        \nThe Big Data for Quality of Life (BD4QoL) study is an international, multicenter, randomized (2:1), open\u2011label trial. Its primary endpoint is the evaluation of clinically significant QoL deterioration based on the EORTC QLQ\u2011C30 index over a 24\u2011month post\u2011treatment follow\u2011up period. The total study sample includes 420 patients.
                        \n
                        \nParticipants are randomly assigned either to the BD4QoL platform monitoring arm or to the standard clinical\u2011practice arm. The BD4QoL platform provides a comprehensive set of services for patient monitoring and empowerment through two core tools:

                        \n
                        \n
                      • a mobile application installed on participants\u2019 smartphones, featuring a chatbot for e\u2011coaching,
                        \n
                      • a Point\u2011of\u2011Care dashboard through which researchers manage patient data.
                        \n
                        \nIn both groups, participants complete QoL questionnaires at baseline and every six months, while also following the standard post\u2011treatment follow\u2011up schedule according to clinical practice.
                        \n
                        \nPatients in the intervention arm (n = 280) gain access to the BD4QoL platform, whereas those in the control arm (n = 140) do not. Key inclusion criteria include completion of treatment for non\u2011metastatic HNC and use of an Android smartphone. Exclusion criteria include active treatment or the presence of synchronous cancers. <\/div>\r\n <\/div>\r\n
                        \r\n
                        \r\n \r\n <\/i> <\/span>\r\n Digital Health for Supporting Head and Neck Cancer Survivors
                        <\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                          CONFERENCE: IEEE BHI-BSN 2021
                          \nIEEE-EMBS International Conference on Biomedical and Health Informatics (BHI\u201921), jointly organised with the 17th IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks (BSN\u201921)
                          \n
                          \n
                          This article presents the innovative capabilities that technological solutions can offer in supporting patients who have survived head and neck cancer.

                          The research was conducted within the framework of the BD4QoL project and focuses on leveraging digital\u2011health technologies to improve quality of life, monitoring, and overall support for patients during the post\u2011treatment period.
                            <\/div>\r\n <\/div>\r\n
                            \r\n
                            \r\n \r\n <\/i> <\/span>\r\n Smartphone\u2011Based Strategy for Monitoring Quality of Life in Head and Neck Cancer Survivors<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                              EAI PervasiveHealth 2022 \u2013 16th EAI International Conference on Pervasive Computing Technologies for Healthcare
                              \n12\u201314 December 2022
                              \nThessaloniki, Greece
                              \n
                              \nSmartphone\u2011based IoT systems have the potential to effectively predict and monitor Quality\u2011of\u2011Life (QoL) indicators when designed with the appropriate methodology. This work aims to develop a comprehensive strategy for creating a specialized QoL\u2011monitoring application for head and neck cancer survivors.
                              \n
                              \nFirst, the results of a literature review on mHealth services for cancer patients are presented. Then, the clinical study protocol is described in detail, within which patients are encouraged to:
                              \n
                              \n
                            • apply self\u2011management practices through active symptom tracking,
                              \n
                            • maintain healthy lifestyle habits,
                              \n
                            • interact with embedded artificial intelligence that serves as an additional communication channel between patient and clinician,
                              \n
                            • complete standardized QoL questionnaires via a web platform from home.
                              \n
                              \nThe challenges encountered, the selected non\u2011invasive data\u2011collection procedures, and the qualitative data derived from physical, social, and behavioral indicators together form a valuable set of guidelines and requirements for future research efforts focused on monitoring cancer survivors after treatment using portable IoT devices.
                                <\/div>\r\n <\/div>\r\n
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                                \r\n \r\n <\/i> <\/span>\r\n Using Classification Techniques for Traffic Prediction in Smart Cities<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                                  Conference paper \u2013 First Online: First Online: 29 May 2020 Part of the book series IFIP Advances in Information and Communication Technology (IFIPAICT, Volume 583)
                                  \n
                                  \nSmart Cities are emerging as highly complex and interconnected ecosystems, offering intelligent services and innovative solutions to improve citizens\u2019 daily lives. This work examines the use of classification techniques in Smart City projects, with a particular focus on traffic prediction.
                                  \n
                                  \nThrough a systematic literature review, the main thematic areas and methods used in smart\u2011city applications are analyzed, with special emphasis on data\u2011harvesting processes and data\u2011mining techniques.
                                  \n
                                  \nThe study investigates whether it is feasible to predict traffic load based on historical data and meteorological conditions. The results show that different predictive models can be developed using weather data, achieving varying levels of accuracy and effectiveness. These findings highlight the potential of applying AI and machine\u2011learning techniques to traffic\u2011management challenges in Smart City environments.
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                                    \r\n \r\n <\/i> <\/span>\r\n Smart Cities Data Classification for Predicting Electricity Consumption & Traffic<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                                      Smart Cities are continuously evolving into highly complex and interconnected ecosystems, offering intelligent services and innovative solutions. These ecosystems generate and utilize large volumes of data from multiple sources, creating new challenges as well as opportunities for developing efficient smart\u2011city services and applications.
                                      \nThis work examines the connection between Data Mining techniques and Smart City projects through a systematic literature review that highlights the main thematic areas and methods applied. The research places particular emphasis on data\u2011harvesting processes and city\u2011data analysis using data\u2011mining techniques.
                                      \nAt the same time, two key research questions are explored:
                                      \n
                                      \n
                                    • the extent to which it is feasible to predict electricity consumption and traffic load based on historical data and meteorological conditions,
                                      \n
                                    • which data characteristics are most suitable for prediction or for supporting decision\u2011making in matters of energy consumption.
                                      \n
                                      \nThe results show that in both cases, effective predictive models can be developed using weather data, highlighting the potential of applying AI and machine\u2011learning techniques in Smart City environments.
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                                        \r\n \r\n <\/i> <\/span>\r\n Classification Methodology for Traffic Prediction: Highlighting the Impact of COVID\u201119

                                        <\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                                          Journal: Integrated Computer-Aided Engineering, vol. 28, no. 4, pp. 417-435, 2021
                                          \n
                                          \nThis work presents an innovative classification methodology for day\u2011ahead traffic prediction. The research examines whether traffic conditions can be forecast based on meteorological factors, seasonality, time intervals, and mobility\u2011restriction measures related to the COVID\u201119 pandemic.

                                          \n
                                          \nReliable predictive models are proposed that utilize smaller and more targeted datasets. Beyond feature\u2011selection processes, the methodology incorporates new attributes associated with COVID\u201119 mobility restrictions, forming a new data model for traffic analysis.
                                          \n
                                          \nThe proposed approach investigates the optimal training subset for model development. The results showed that different models can be developed with varying levels of success, while the highest accuracy was achieved when all relevant features were combined and the proposed training subset was used.
                                          \n
                                          \nThe methodology demonstrated significant accuracy improvements compared to previously published approaches, highlighting the potential of applying AI and machine\u2011learning techniques to traffic prediction in Smart City environments.
                                            <\/div>\r\n <\/div>\r\n
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                                            \r\n \r\n <\/i> <\/span>\r\n Classification Methodology for Traffic Prediction: Highlighting the Impact of COVID\u201119
                                            <\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                                              Issue title: Selection of papers from the 21st EANN (Engineering Applications of Neural Networks) and 16th AIAI (Artificial Intelligence Applications and Innovations) Joint International Conference
                                              \n
                                              \nThis work presents an innovative classification methodology for day\u2011ahead traffic prediction. The research examines whether traffic conditions can be forecast based on meteorological factors, seasonality, time intervals, and mobility\u2011restriction measures related to the COVID\u201119 pandemic.

                                              \n
                                              \nReliable predictive models are proposed that utilize smaller and more targeted datasets. Beyond feature\u2011selection processes, the methodology incorporates new attributes associated with COVID\u201119 mobility restrictions, forming a new data model for traffic analysis.
                                              \n
                                              \nThe proposed approach investigates the optimal training subset for model development. The results showed that different models can be developed with varying levels of success, while the highest accuracy was achieved when all relevant features were combined and the proposed training subset was used.
                                              \n
                                              \nThe methodology demonstrated significant accuracy improvements compared to previously published approaches, highlighting the potential of applying AI and machine\u2011learning techniques to traffic prediction in Smart City environments.
                                                <\/div>\r\n <\/div>\r\n
                                                \r\n
                                                \r\n \r\n <\/i> <\/span>\r\n Game\u2011Based Smart System for Detecting Developmental Speech and Language Disorders in Early Childhood Communication: A Protocol Toward Digital Clinical Diagnostic Procedures<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                                                  Interactive Mobile Communication, Technologies and Learning Conference
                                                  \nIMCL 2021: New Realities, Mobile Systems and Applications, pp. 559\u2013568
                                                  \n
                                                  \nAlthough international literature reports high prevalence rates of developmental speech and language disorders in children (3\u201317%), many cases remain undiagnosed, depriving children of timely and effective intervention.
                                                  \n
                                                  \nThe use of digital and mobile technologies in health and education creates new opportunities for monitoring, decision\u2011making, classification, and assessment processes. This study presents and documents a design and development protocol for a digital approach that supports screening and early\u2011detection procedures for developmental speech and language difficulties in early childhood communication.
                                                  \n
                                                  \nThe proposed solution leverages smart computing models, sensors, and early\u2011diagnosis indicators of linguistic and communication difficulties, and is developed in successive phases. The system design includes:
                                                  \n
                                                  \n
                                                • an interactive game\u2011based digital application for the child,
                                                  \n
                                                • an online data\u2011collection environment for parents and clinical specialists,
                                                  \n
                                                • a complete functional specification of the game\u2011based activities and the overall system architecture.
                                                  \n
                                                  \nThe proposed smart system has the potential to enhance digital\u2011healthcare processes for children\u2019s communication skills, while contributing to positive social and economic impact in line with contemporary digital\u2011transformation trends in healthcare.
                                                    <\/div>\r\n <\/div>\r\n
                                                    \r\n
                                                    \r\n \r\n <\/i> <\/span>\r\n Co\u2011Designing User Experience in Location\u2011Based Games for a Museum Network: Involving Cultural\u2011Heritage Professionals and Local Communities<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                                                      Designing location\u2011based games (LBGs) for the cultural\u2011heritage sector requires the active participation of local communities and cultural\u2011heritage professionals to ensure authenticity, cultural relevance, and content validity.
                                                      \n
                                                      \nThis work presents a participatory and co\u2011design approach for developing LBGs that promote awareness and learning around intangible cultural heritage, specifically traditional crafts and artisanal techniques. The research was carried out within a long\u2011term project that covered the entire process\u2014from initial awareness\u2011raising to final implementation.
                                                      \n
                                                      \nFollowing a design\u2011thinking methodology, the study outlines the participatory methods used to engage cultural\u2011heritage professionals, local communities, and visitors of museums and cultural sites. These methods include:
                                                      \n
                                                      \n
                                                    • field visits,
                                                      \n
                                                    • design workshops,
                                                      \n
                                                    • field playtesting,
                                                      \n
                                                    • field studies.
                                                      \n
                                                      \nIn parallel, the paper analyzes participatory\u2011design issues that emerged during the project, such as:
                                                      \n
                                                      \n
                                                    • the centrality and representativeness of participants,
                                                      \n
                                                    • generating meaningful outcomes through collaborative sessions,
                                                      \n
                                                    • co\u2011creating content through playtesting,
                                                      \n
                                                    • the impact of the pandemic on participatory processes.
                                                      \n
                                                      \nThe work presents a comprehensive case of participatory and co\u2011design development of location\u2011based games for cultural heritage, emphasizing long\u2011term collaboration and continuous participant involvement in designing three different LBGs for a network of museums and cultural spaces.
                                                        <\/div>\r\n <\/div>\r\n
                                                        \r\n
                                                        \r\n \r\n <\/i> <\/span>\r\n Personalization Framework for Cultural Routes: Case Study of the TRACCE Project<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                                                          Recent developments in digital\u2011storytelling technologies within cultural tourism have strengthened new trends toward more comfortable, interactive, and personalized travel experiences. The emergence of recommendation systems and personalization techniques creates new opportunities for enhancing the experience of cultural\u2011heritage visitors.
                                                          \n
                                                          \nThis work presents an innovative narrative system for cultural routes, which combines users\u2019 multimedia\u2011content preferences with different typologies of cultural tourists.
                                                          \n
                                                          \nAs a research foundation, the McKercher typology is employed, categorizing cultural\u2011heritage visitors into five main groups. Using a specially designed questionnaire, an enriched typology of cultural tourists is developed, adding three additional categories based on users\u2019 preferences regarding multimedia content.
                                                          \n
                                                          \nThe proposed approach contributes to the creation of more personalized and interactive cultural experiences, enhancing visitor engagement and interaction within cultural routes and heritage environments.
                                                            <\/div>\r\n <\/div>\r\n
                                                            \r\n
                                                            \r\n \r\n <\/i> <\/span>\r\n Redefining Smart Tourism through Smart Gamified and Gaming Applications in Greece
                                                            <\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                                                              World Academy of Science, Engineering and Technology \u2013 International Journal of Social and Business Sciences
                                                              \nVol. 15, No. 01, 2021
                                                              \n
                                                              \nSmart technologies are increasingly used to enhance the travel experience and shape a destination\u2019s image through digital applications and social\u2011media platforms. This work presents the design and implementation of smart\u2011management applications that promote culture, sustainability, and accessibility in two different tourism destinations in Greece.

                                                              \n
                                                              \nThe first case concerns Corfu, a highly popular destination and UNESCO World Heritage Site, where increased visitor numbers create challenges in experience organization and infrastructure management. The second case focuses on Kilkis, a destination with low tourist traffic and high seasonality, where traditional approaches to promoting culture and local experiences have not produced the desired results.
                                                              \n
                                                              \nTo address these challenges, two different systems were developed:
                                                              \n
                                                              \n
                                                            • \u201cHologrammatic Corfu\u201d for the old town of Corfu,
                                                              \n
                                                            • \u201cBRENDA\u201d for the Kilkis region.
                                                              \n
                                                              \nAlthough the two systems were designed independently and respond to different needs, they are based on a shared gaming and gamification methodology.
                                                              \n
                                                              \nHologrammatic Corfu was designed to support comprehensive exploration of the city before, during, and after the trip, using transmedia content such as:
                                                              \n
                                                              \n
                                                            • photographs,
                                                              \n
                                                            • 360\u00b0 videos,
                                                              \n
                                                            • augmented reality,
                                                              \n
                                                            • hologrammatic videos.
                                                              \n
                                                              \nIn parallel, statistical analysis of point\u2011of\u2011interest visitation is used to dynamically redirect visitors, enhancing sustainability, accessibility, and balanced management of tourist flows.
                                                              \n
                                                              \nBRENDA was designed to promote gastronomic and historical tourism, using serious\u2011gaming and gamification mechanisms that connect local businesses with cultural points of interest. This approach encourages active participation from both local communities and visitors, fostering sustainable and interactive tourism experiences.
                                                              \n
                                                              \nFinally, the work highlights the potential for reusing gaming mechanisms and transmedia elements in new areas of interest, contributing to the transformation of destinations into modern smart destinations.
                                                              \n
                                                              \nConference Title: ICSTDM 2021 \u2013 International Conference on Smart Tourism and Destination Management
                                                              \nConference Location: Istanbul, Turkey Conference Dates: 28\u201329 January 2021
                                                                <\/div>\r\n <\/div>\r\n
                                                                \r\n
                                                                \r\n \r\n <\/i> <\/span>\r\n Participatory Urban Planning through an Online WebGIS Platform: Functions and Tools<\/span>\r\n <\/i><\/span>\r\n <\/h5>\r\n
                                                                  This work presents an online WebGIS platform for participatory urban planning, focusing on its objectives, functionalities, and tools within the context of the ppCITY research project.
                                                                  \n
                                                                  \nThe development of Information and Communication Technologies (ICT), and particularly WebGIS tools, has significantly strengthened public\u2011participation processes, expanding the ability of diverse stakeholder groups to engage in urban planning and decision\u2011making.
                                                                  \n
                                                                  \nTechnically, the platform is based on open\u2011source ppGIS solutions and integrates innovative online tools that support the core methodological stages of participatory planning, leveraging real spatial and urban challenges.
                                                                  \n
                                                                  \nThe system enables:
                                                                  \n
                                                                  \n
                                                                • the creation of projects and sub\u2011projects aligned with the stages of participatory urban planning,
                                                                  \n
                                                                • the use of libraries of proposed solutions,
                                                                  \n
                                                                • the combination of user profiling and opinion weighting,
                                                                  \n
                                                                • the management and analysis of geospatial data through WebGIS tools.
                                                                  \n
                                                                  \nThe primary goal of the platform is to highlight the essential characteristics of public space and to organize processes of meaningful and equitable citizen participation in urban planning.
                                                                  \n
                                                                  \nThis research approach also aims to create an open community of users, experts, planners, and developers around an open\u2011source ppWebGIS software environment, fostering collaboration and participatory innovation in the fields of Smart Cities and urban planning.
                                                                    <\/div>\r\n <\/div>\r\n <\/div>\r\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
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                                                                    \n\t\t\t\tMedia\t\t\t\t\t\n\t\t\t\t\t\t\t<\/h3>\n\t\t<\/div>\n\t\t\n\t<\/div>\n<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
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                                                                    MUSEUM PLACE<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
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                                                                    TTLS<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
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                                                                    DEVELOPMENT<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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                                                                    BD4Qol<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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                                                                    WEAR4SAFE<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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                                                                    SMART TESLA<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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                                                                    THE LEGEND OF BLANCO<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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                                                                    PPCITY<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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                                                                    INTEL ANN<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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                                                                    SUSANNA<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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                                                                    NOONIOT<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
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                                                                    KED PATRAS<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
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                                                                    \n\t\t\t\t\t\t\t\t\t

                                                                    ANNETE-SPIRIT<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
                                                                    \n\t\t\t\t
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                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
                                                                    \n\t\t\t\t\t\t\t\t\t

                                                                    ANNETE<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
                                                                    \n\t\t\t\t
                                                                    \n\t\t\t\t\t\t\t
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                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
                                                                    \n\n \n
                                                                    \n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
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                                                                    AI4DEBUNK<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
                                                                    \n\n \n
                                                                    \n
                                                                    \r\n
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                                                                    \n\t\t\t\t
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                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
                                                                    \r\n
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                                                                    \n\t\t\t\t
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                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
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                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
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                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
                                                                    \n\n \n
                                                                    \n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
                                                                    \n\t\t\t\t\t\t\t\t\t

                                                                    SMART SPEECH<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
                                                                    \n\n \n
                                                                    \n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
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                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
                                                                    \n\t\t\t\t\t\t\t
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                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
                                                                    \r\n
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                                                                    \n\t\t\t\t
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                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
                                                                    \n\n \n
                                                                    \n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
                                                                    \n\t\t\t\t\t\t\t\t\t

                                                                    TRACCE DOT<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
                                                                    \n\n \n
                                                                    \n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
                                                                    \n\t\t\t\t\t\t\t
                                                                    \n\t\t\t
                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
                                                                    \n\t\t\t\t\t\t\t
                                                                    \n\t\t\t
                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
                                                                    \n\n \n
                                                                    \n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
                                                                    \n\t\t\t\t\t\t\t\t\t

                                                                    AURORA MINDS<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t
                                                                    \n\n \n
                                                                    \n
                                                                    \r\n
                                                                    \r\n \r\n \t\t
                                                                    \n\t\t\t\t
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                                                                    <\/div>\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n <\/div>\r\n <\/div>\r\n
                                                                    \r\n
                                                                    \r\n \r\n <\/div>\r\n <\/div>\r\n \t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

                                                                    We innovate today for the solutions of tomorrow Dr. Despina Elisavet Filippidou Head of Innovation Start Hub Email Address innovation@dotsoft.gr Phone +30 2310 500 181 The Research and Innovation Department ensures that DOTSOFT remains at the forefront of technological developments, strengthening its long\u2011term competitiveness and laying the foundations for the company\u2019s sustainable growth. DOTSOFT\u2019s Research […]<\/p>\n","protected":false},"author":1,"featured_media":36825,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-39445","page","type-page","status-publish","has-post-thumbnail","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/dotsoft.gr\/en\/wp-json\/wp\/v2\/pages\/39445","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dotsoft.gr\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/dotsoft.gr\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/dotsoft.gr\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dotsoft.gr\/en\/wp-json\/wp\/v2\/comments?post=39445"}],"version-history":[{"count":0,"href":"https:\/\/dotsoft.gr\/en\/wp-json\/wp\/v2\/pages\/39445\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dotsoft.gr\/en\/wp-json\/wp\/v2\/media\/36825"}],"wp:attachment":[{"href":"https:\/\/dotsoft.gr\/en\/wp-json\/wp\/v2\/media?parent=39445"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}