Dev Conference by Neo4j
Session Track: Data Science
Session Time:
Session description
This session will present an innovative cloud infrastructure for an IoT-based monitoring platform tailored for a district in Hamburg, Germany. It will demonstrate how integrating GPT language models via LangChain and utilizing Building Information Modeling (BIM) and Neo4j for data management enhances data analysis and decision-making. Attendees will learn how this platform significantly improves operational efficiency and resource optimization. By attending, you will gain insights into cutting-edge technologies for smart building management, and discover how to implement these advancements to optimize data management and improve decision-making processes in smart districts.
Research Associate, RWTH Aachen University
He studied Electrical Engineering and Information Technology at RWTH Aachen University in Germany. Since May 2021, he has been working as a Research Associate at the Institute for Energy Efficient Buildings and Indoor Climate at RWTH Aachen University. His main research fields include innovative monitoring concepts for buildings, cloud-based energy optimization, and artificial intelligence.
Energy Engineering Student, RWTH Aachen University
Energy Engineering Student
