The information and communication technologies (ICTs) utilization ratio in the construction industry is relatively low. This industry is characterized by low productivity, time and cost overruns in projectsdue to inefficient management processes, poor communication and low process automation. To improve construction performance, a BIM-based (BIM - (Building Information Modelling) and augmented reality (AR) application (referred to as the AR4C: Augmented Reality for Construction) is proposed, which integrates a location-based management system (LBMS). The application provides context-specific information on construction projects and tasks, as well as key performance indicators on the progress and performance of construction tasks. The construction projects are superimposed onto the real world, while a site manager is walking through the construction site. This paper describes the most important methods and technologies, which are needed to develop the AR4C application. In particular, the data exchange between BIM software and the Unity environment is discussed, as well as the integration of LBMS into BIM software and the AR4C application. Finally, the implemented and planned functionalities are argued. The AR4C application prototype was tested in a laboratory environment and produced positive feedback. Since the application addresses construction sites, a validation in semi-real scenarios with end users is recommended.

Architects face the challenge of exploring various design solutions in the early design stage, often with conflicting optimization goals. To tackle this complexity, they need to rely on tools and methodologies during the conceptual phase to assess and optimize designs, considering multiple aspects of building performance. Parametric Design, Generative Design, and automation in Building Information Modelling (BIM) offer architects new opportunities to work on complex buildings. These advancements empower designers to enhance their designs, increase project efficiency, improve performance, and reduce project time and costs. Multi-Objective Optimization algorithms are employed to address conflicting objectives in the design process. The GENIUS project introduces an Algorithm-Aided Design workflow that optimizes the building shape and Window-to-Wall Ratio of an office building, considering energy and daylight performance. The integration of BIM software, visual programming tools, and Artificial Intelligence techniques (Genetic Algorithms and RBFOpt model-based optimization) allows architects to identify optimal solutions aligning with design objectives. The workflow was validated through a case study of a large office building, focusing on maximizing daylight performance using the Spatial Daylight Autonomy metric and minimizing energy consumption using the Energy Use Intensity metric. The GENIUS project equips architects with a methodology and toolset to improve their designs and identify optimal solutions for complex design challenges.

This paper describes the Ri.Fa.Re. timber-based solution, an innovative timber-based prefabricated panel for the energy refurbishment of the existing Italian buildingś façades. Although similar technologies have already been tested in several European countries, they are not feasible to be used in the Italian context characterized by specific geometric features of the building stock and by seismic constraints which are not relevant for most of European countries. Moreover, this research does not aim only at developing a product but also at adopting a new process, based on parametric design and lean construction principles. The main outcome of this project is a concrete kit for energy refurbishment suitable for the Italian context, including: a) a technological prefabricated but customizable product and b) a more efficient process to decrease time and cost wastes during the whole process

Advancements in Parametric Design, Generative Design, and automation in Building Information Modelling (BIM) have opened new opportunities for architects and engineers working on complex buildings, such as offices. These developments allow designers to enhance their designs, increase project efficiency, improve performance, and reduce project time and costs. To address conflicting objectives that arise during the design process, genetic algorithms with multi-objective optimization (MOO) have been employed in architectural design. The GENIUS project aims to optimize building shape, apertures, and shading systems in the concept and design stages, with a focus on energy and daylight performance. The project integrates BIM and visual programming tools with Artificial Intelligence techniques like Genetic Algorithms and RBFOpt model-based optimization. Optimization algorithms are used to identify the best solutions that meet all design objectives, helping architects optimize their designs and achieve desired outcomes. The workflow was tested on a case study of a large office building, with MOO focused on maximizing daylight performance using Spatial Daylight Autonomy metric and minimizing energy consumption using Energy Use Intensity metric. The project provides architects with a method to improve their designs using Algorithm Aided Design tools, which help identify the best solutions for complex design problems.