ICT knowledge and applications enable a better use of resources in buildings, hence allowing for optimising building indoor environmental quality while reducing energy needs during both building design and building intelligent operational phases, helping cities to reduce their carbon emissions. In the course Intelligent Building Optimization, we address this challenge, dealing with the integration of building systems, technology and energy systems within a smart control environment. This is done by describing building components and related technical systems, as well as digital architecture, climate-responsive building envelope, and kinetic façade. In this context, ICT is used for smart control of heating, ventilation, and air conditioning systems in order to provide thermal comfort and control air quality and illumination. White box models are adopted together with grey and black box ones to support the development of digital twins and optimise both building design envelope choices via surrogate modelling and building operational actions. The latter is performed by simulating an intelligent building management system (BMS) able to automatically set, by means of BMS control algorithms, building-related actuation parameters on the basis of measured real-time data, exploiting innovative approaches of the use of digital twins and advanced building modelling solutions.

Students will gain skills and acquire knowledge concerning the relationship between ICT systems and: - main aspects connected to the principal building technological elements for further system integration; - main principles related to smart building and smart cities design with special regard to intelligent building optimisation; - resource-saving measures to be used in technical building systems (heating, ventilation, cooling, lighting); - indoor climate control, including natural ventilation; - comforts and indoor environmental quality in buildings (thermal, visual, IAQ) - methods, tools and procedures for assessing environmental and energy building performance; - concepts and basics to support dynamic/hourly building energy simulation; - white box, grey box and black box modelling for building performance analyses and digital twin applications; - Building Management System (BMS) and middleware platform development.

Lectures and exercises regard the following topics: 1) smart building: concepts, scenarios and technological solutions 2) introduction to sustainable building: comfort domains (thermal, IAQ, visual) and energy performances 3) ICT optimisation techniques for building indoor environmental quality and energy savings 4) white box, grey box, and black box modelling for the built environment supporting digital twins 5) surrogate modelling production and applications 6) computing user comfort correlated KPIs, GUI, smart sensoring and actuating, data gathering and elaborations 7) Building Management System (BMS) and middleware platform development

The application of knowledge acquired by students from the courses lectures on the above mentioned topics will be carried out through both brief specific exercises and within the interdisciplinary project on a smart building design. From a methodological point-of-view, a two-faceted approach will be followed: on one hand, models and technological solutions to be applied to a building with the aim of reducing its environmental impacts will be presented, so that students can understand the working principles of the various technical building systems and design them accordingly. On the other hand, the existing (and future evolution) ICT systems needed to manage, coordinate, interact, program and integrate such building functionalities, will be discussed. Within the interdisciplinary project, students will develop in group a practical design exercise, by developing and simulating computational models of the control of technical building systems described in the course combining energy modelling and coding as well as simulating data collection and elaborations connected to ICT solutions for implementing new and "smart" functions.

Due to the innovative contents of this course no reference publications are given. Materials and documentation, such as slides, tables, graphs, software, printed handouts related to both lectures and exercises will be supplied during the course together with scientific papers. Nevetheless the following books may be considered: 1) Wang S (2010) Intelligent buildings and building automation, Spon Press. 2) Sinopoli J (2016) Advanced Technology for Smart Buildings, Artech House 3) Chiesa G (2020) Technological paradigms and digital eras, Springer 4) Sinopoli J (2009) Smart Buildings Systems for Architects, Owners and Builders, Butterworth-Heinemann 5) Pagani R, Chiesa G (eds) (2016) Urban data: Tools and methods towards the algorithmic city, FrancoAngeli 6) Hensen JLM, Lamberts R (eds) (2019) Building Performance Simulation for Design and Operation, 2nd edn, Routledge 7) Holzer P, Psomas T (eds) (2018) Ventilative Cooling Sourcebook, IEA EBC Annex 62, Aalborg Un. 8) Brackney L et al. (2018) Building Energy Modeling with OpenStudio, Springer

Slides; Esercizi; Strumenti di simulazione;

Modalita di esame: Prova scritta (in aula); Prova orale obbligatoria; Elaborato scritto prodotto in gruppo;

Exam: Written test; Compulsory oral exam; Group essay;

... Learning target achievements will be reached via lectures, seminars and learning exercises through individual activity and teamwork in building design case studies. Deliveries are consistent with scheduled activities and final exam dates. The final exam with relevant scoring will include: - a test to assess theoretical knowledge acquired during the course (weight: 40% of the final score; duration: 1 h) consultation of supporting tools and material is not allowed; - an evaluation by the teachers of the final results of the exercises carried out during the course and presented in a book and a code repository one week before the final exam (weight: 40%); - a slide presentation of the results of the exercises carried out during the course and a discussion about them to check students comprehension of the learning process (weight: 20%; duration: 20 minutes per student team). The exercises are developed in teams supporting white box building energy and comfort modelling, surrogate modelling definition to optimise building design choices, and developing a simulated building control logic to support smart building operational management in semi-real-time. The laude will be assigned only if the answers to the different parts of the exam are not only correct from a numerical and content point of view but also exceptionally clear and complete in the exposition

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.