The Master Programme in Robotics and Advanced Construction is an innovative educational format that offers interdisciplinary skills and understanding through a series of class seminars that are put into practice through hands-on workshops. IAAC gives students the opportunity to create individual studio agendas and develop Pilot Thesis Projects based on the knowledge acquired during the seminars and workshops split into 3 Modules. In this way, IAAC puts together an experimental learning environment for the training of professionals with both theoretical and practical responses to the increasing complexity of the construction sector.
Aim: To predict the number of seating spaces based on various types of seating layout, number of corridors and dimensions of generative enclosed rectangular spaces such as an auditorium. Objectives: Dataset Design: To create Dataset for the required problem, a synthetic dataset is designed with the help of various bylaws supporting the problem. Data Analysis: … Read more
The project’s objective was to create a machine-learning model capable of classifying repurposed timber components within an assembly process as either structural or non-structural, using factors such as defect quantity, age, and exposure to weather conditions as input. Dataset Generation and Analysis The dataset was produced using Roboflow by utilizing scans of the timber elements … Read more
Our aim is to develop a machine learning model that accurately predicts the color outcome of ceramic underglazes based on their ingredient compositions and firing conditions. In the world of ceramic art, the process of underglazing involves applying colors to pottery which are then sealed under a transparent glaze before firing. However, predicting the final … Read more
