Description du projet :
Contexte
Chaque année, plusieurs milliards sont investis dans la mise en conformité et dans l’amélioration des performances énergétiques et structurelles du bâti existant ; avec la forte augmentation du prix de l’énergie et de possibles restrictions quant à son utilisation, ce montant va clairement augmenter à l’avenir.
Lorsqu’un bâtiment doit être assaini, les spécialistes identifient les meilleures stratégies de rénovation, basées sur des études relativement poussées et généralement coûteuses. Pour permettre un assainissement de qualité, durable et efficace à l’échelle du territoire, chaque bâtiment doit être caractérisé au mieux pour pouvoir identifier ses performances globales, i.e. énergétiques, thermiques, structurelles, de confort (par exemple l’isolation phonique ou encore l’accès aux personnes à mobilité réduite) et de sécurité (incendie, par exemple) pour l’usager/habitant.
Sur la base de ce constat, nous proposons une solution basée sur un système-expert et l’IA avec implication de l’humain, afin d’offrir la possibilité d’évaluer l’état global de bâtiments à petite ou large échelle et, à terme, de pouvoir établir des stratégies d’assainissement (également à petite ou large échelle) pertinentes, globales et adaptées de bâtiments existants.
Objectif principal et méthodologie de travail
Nous proposons de développer une plateforme numérique permettant l’obtention d’informations pertinentes afin de caractériser un ou plusieurs bâtiments et d’en évaluer les performances globales. Les solutions digitales visées mixent systèmes experts, intelligence artificielle (IA) et incluent ponctuellement l’intervention de l’humain (figure ci-dessous).
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Assainissement 4.2 : méthodologie de travail
Les objectifs spécifiques sont:
- Développement d’un système-expert d’identification de typologies constructives ;
- Création d’une interface utilisateur servant à renseigner le système-expert développé sous (1);
- Réalisation d’une campagne de relevé de détails typologiques d’éléments de façades ;
- Développement d’un algorithme IA pour la reconnaissance d’éléments de façades pertinents liés au système-expert développé en (1) et d’identification typologique ;
Établissement d’un rapport de caractérisation à destination de l’utilisateur.
Equipe de recherche au sein de la HES-SO:
Devaux Mylène
Partenaires académiques: Hennebert Jean, HEIA; Niederhäuser Lavinia, HEIA; Schwab Stefanie, HEIA
Durée du projet:
01.09.2023 - 31.12.2024
Montant global du projet: 170'100 CHF
Statut: En cours
SWITCH edu-ID
Administration
