I am Arianna Fedeli

CHANGES (Cultural Heritage Active Innovation for Next-Gen Sustainable Society) is a national project funded by the Italian PNRR. It promotes innovation and sustainability in cultural heritage through collaboration among universities, research centers, and institutions. My work focuses on Digital Twin technologies that integrate IoT data, 3D digitization, and AI models to support the monitoring and preservation of artworks and monuments.

COBOL (COmmunity-Based Organized Littering) is a project by the Gran Sasso Science Institute and the University of Milan “Bicocca”, funded under the PRIN 2022 program. It combines computer science, AI, and civic education to address illegal waste dumping. Through gamification and crowdsourced data from students, the project applies machine learning and computer vision to classify waste and promote environmental awareness.

FloWare introduces a model-driven methodology that supports the reuse and customization of Internet of Things applications. It allows developers to compose, configure, and deploy IoT solutions efficiently by leveraging reusable building blocks and domain-specific models.

X-IoT aims to improve the portability of IoT applications across heterogeneous platforms. Through a model-driven approach, it enables developers to design applications independently of the underlying IoT infrastructure, automating code generation and deployment for multiple environments.

FloBP integrates IoT data and services into business processes using a model-driven paradigm. It extends BPMN models to represent IoT events and interactions, allowing organizations to design and execute IoT-enhanced processes with higher automation and traceability.