There is a pressing need for residential solutions that ensure the health, safety, and privacy of older individuals while allowing them to live independently, as the global population ages. This project will create a cutting-edge smart home system that enhances the design and implementation of homes by incorporating non-invasive health surveillance, privacy-preserving data analytics, and Building Information Modeling (BIM). The system's impact on well-being, healthcare costs, and property tenure will be evaluated by stakeholders through the use of Virtual Reality (VR) to simulate smart residential environments. Additionally, VR will facilitate cognitive health and social interaction among geriatric residents by offering immersive experiences. In real time, Artificial Intelligence (AI) will personalize health surveillance, adapt to the routines of seniors, detect health abnormalities, and alert caregivers. Cognitive and social support will be provided by AI virtual assistants, which will increase independence. 

In this project, we are creating and deploying a Blockchain-based Healthcare Management System that securely integrates medical, pharmacy, wellness, and employee data into a single platform. By leveraging Blockchain's core features, distributed trust, data immutability, and automated smart contracts, alongside advanced healthcare analytics, the system aims to address key challenges in today's healthcare landscape, including data fragmentation, rising costs, and lack of transparency. As a result, our platform will generate real-time, actionable insights that enable employers to proactively engage employees who are at risk of developing costly health issues. We aim to improve health outcomes and reduce overall healthcare expenses through smart contracts that will automate essential processes like claims adjudication, benefit coordination, and incentive distribution. Additionally, we can enhance operational efficiency and reduce administrative burdens. We do believe that the solution will enable organizations to achieve significant cost savings, enhance data security and compliance, and improve overall workforce well-being. 

In this project, we would like to develop a Generative AI (GenAI)-driven platform that adeptly produces tailored content, automates creative processes, and improves user experiences across multiple areas. The platform will utilize advanced language models, vision models, and multimodal AI techniques to provide high-quality outputs, including personalized study materials, marketing content, product descriptions, and customer support responses. The system is engineered for adaptability and user orientation, incorporating rapid optimization, real-time content enhancement, and customizable templates specific to various sectors. The objective is to optimize workflows, enhance productivity, and democratize access to AI-generated innovation. By including ethical AI practices, transparency, and human-in-the-loop feedback mechanisms, the platform will guarantee the responsible and effective utilization of GenAI technology. 

As worldwide populations age, loneliness has emerged as an escalating public health issue among the elderly, with considerable ramifications for both mental and physical well-being. Studies indicate that 33–57% of persons aged 65 and above exhibit symptoms of loneliness and social isolation. These disorders are intricately associated with heightened risks of depression, anxiety, dementia, hypertension, myocardial infarctions, and cerebrovascular accidents. This initiative seeks to mitigate the loneliness pandemic among the elderly by creating an Artificial Intelligence Digital Service for Wellness (AIDSW). AIDSW utilizes artificial intelligence and user-centered design to provide continuous, tailored assistance, in contrast to traditional therapies that depend on sporadic human interaction, such as phone check-ins or group sessions. This intelligent assistant will oversee wellness in real-time, promote social engagement, and guarantee prompt connection with caregivers or family members when necessary. This effort aims to improve quality of life, mitigate health risks linked to loneliness, and create a scalable, proactive paradigm for elder care through the integration of accessible technology and AI-driven engagement. 

Unmanned Aerial Vehicles (UAVs) are increasingly used across logistics, surveillance, agriculture, and emergency response industries. A critical challenge in UAV operations is achieving high-accuracy autonomous landing, especially in constrained, dynamic, or GPS-denied environments. This project aims to develop a robust precision landing system for UAVs by integrating computer vision, sensor fusion, and advanced control algorithms. The system will leverage onboard cameras, AI/ML Algorithms, and inertial measurement units (IMUs) to detect landing targets, estimate position in real-time, and guide the UAV safely to the designated point with sub-meter accuracy. The outcomes of this project will enhance the reliability and autonomy of UAV operations, supporting mission-critical deployments where manual control or GPS reliance is not feasible.

GreenTwin is an innovative project at the intersection of agriculture, technology, and sustainability, designed to revolutionize how we manage and monitor farming environments. It leverages the power of digital twin technology to create a virtual replica of real-world agricultural systems, with a core focus on reducing greenhouse gas emissions from farming activities. By integrating real-time data from sensors, drones, and satellite sources, GreenTwin provides farmers with smart, data-driven insights, eliminating guesswork and enabling precision agriculture. 

The project is supported by NGI Sargasso and funded by the European Union to advance technologies that drive a more open, secure, and inclusive internet and digital future. 

In this project, we propose to develop a Generative Artificial Intelligence (GenAI)-enabled teaching ecosystem to enhance student engagement and learning outcomes through innovative pedagogical approaches in core courses taught in the college of IST, such as Basic Programming, Computational Thinking, and Technical Writing. Our study aims to address emerging challenges associated with GenAI in academic environments and introduce new teaching methods centered around its capabilities.