The Chair of Intelligent Technical Design is concerned with the application of modern information and communication technology (ICT) during the design, the construction and the operation of civil infrastructure, such as buildings, bridges, tunnels, road and pipe networks. In this regard, we use methods of Building Information Modelling (BIM), Computer Vision and Machine Learning as well as Virtual and Augmented Reality to efficiently and sustainably inform decision makers.
"Intelligent Technical Design refers to a design approach that utilizes advanced technologies, such as artificial intelligence and machine learning, to optimize the design process and improve the performance, efficiency, and sustainability of building and infrastructure systems. It integrates data-driven insights, real-time performance monitoring, and machine learning algorithms into the design process to make informed decisions, automate manual processes, and reduce the risk of human error. The goal of Intelligent Technical Design is to create high-performing, sustainable, and efficient building and infrastructure systems." [ChatGPT, 2023]
Digital ITD Twin: Room Climate
We have created a digital twin of our professorship. In the second step, we have visualized room climate data and allow the user to adjust the radiator thermostat from the virtual world.
A digital twin represents a connection between a real object and the digital world. The twin consists of a digital model that is automatically updated with data from the real world and also automatically transfers changes from the digital world to the real world. We have created such a twin. In the second step, we focus on automated data exchange. Sensors for temperature and humidity record data from the real world; this data is stored and visualized in the VR environment. In addition, radiator thermostats in the virtual world can be used to set the desired room temperature. This information is transmitted to the thermostats in the real world.
The result may be found here: https://vimeo.com/896488121?share=copy
Thanks to the following students of Digital Engineering: Juan González Cavero, Justin James, Anil Chandra Kavi and Srividya Raju for their help.
