The CEAR 10/A contribution focuses on the transformation of spatial data into coherent, optimised, and communicatively effective digital models intended for integration into immersive and interactive environments. Particular attention is devoted to workflows starting from metric survey data and point clouds (in coordination with colleagues from Geomatics), analysing different approaches and applications for interpreting, simplifying, and structuring complex datasets in order to construct lightweight and semantically organised 3D models. The modelling process is not understood as a purely technical operation, but as an interpretative and design act in which Drawing plays a mediating role between metric accuracy, representational coherence, and computational requirements related to real-time visualisation.

At the end of the course, students will be able to: Knowledge • Understand the theoretical foundations of 3D modelling within the disciplinary field of Drawing. • Distinguish between survey data, point clouds, meshes, and parametric models. • Understand principles of geometric modelling, topological optimisation, and Level of Detail (LOD) management for real-time applications. Skills • Optimise geometries and topologies for the production of lightweight and interoperable models. • Prepare 3D assets for integration into immersive environments and graphics engines. • Collaborate effectively with colleagues from other disciplines in the development of the digital pipeline. Competences • Mediate between metric rigour and representational synthesis. • Critically evaluate modelling strategies and related software tools according to their subsequent application within immersive environments.

Recommended prior competence in 3D modelling software, along with basic knowledge of digital representation and three-dimensional modelling principles.

Drawing contribution develops the theme of three-dimensional modelling, with particular attention to the transformation of point clouds, survey data, and two-dimensional drawings into structured and optimised digital models. The main techniques of geometric abstraction, mesh cleaning and optimisation, Level of Detail (LOD) management, and format interoperability are analysed. The objective is to produce lightweight and coherent 3D models ready for integration into immersive environments and interdisciplinary pipelines.

The module includes theoretical lectures, guided exercises, and laboratory activities carried out in groups. Teaching is delivered in blended format (50% in person, 50% online, with a maximum of 30% asynchronous content). Students will develop optimised 3D models starting from survey datasets or provided materials, with technical review sessions and interdisciplinary discussions.

Specific bibliographic references will be provided during the course.

Nessuno;

Modalita di esame: Accertamento (esame senza voto);

Exam: Check;

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Gli studenti e le studentesse con disabilita o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unita Special Needs, al fine di permettere al/la docente la declinazione piu idonea in riferimento alla specifica tipologia di esame.