Angelina Aziz

M. Eng.
Wissenschaftliche Mitarbeiterin
Raum: IC 6/75.77
Tel.: 0234 32 - 23047
ORC-ID: 0000-0001-7853-1395

Optimizing Fire Safety in Building Maintenance with Machine Learning

Visual inspection of building elements, especially those related to fire safety, is a critical aspect of building maintenance and safety. But, traditional inspection methods have their limitations, including being time-consuming, labor-intensive, and subject to human error. Therefore, by using machine learning algorithms, inspection procedures can be streamlined, and human errors can be minimized. Additionally, machine learning models can identify patterns and deviations that may not be noticeable to the human eye, leading to earlier detection of faults and the ability to take corrective measures before a fire outbreak occurs due to bad fire safety management.

Optimizing Fire Safety in Building Maintenance with Machine Learning


  • Sönmez, Gamze (2022): Vorgehensweise zur systematischen Formalisierung von Prüfregeln für BIM-Modelle zum Zeitpunkt der Ausführungsplanung (HOAI LPH5)
  • Lobitz, Timo (2023): Automatische Erkennung von Sicherheits- und Gesundheitsschutzkennzeichnung mithilfe eines maschinellen Lernverfahrens
  • Zazai, Milad (2023): Automatic MEP Component Detection with Deep Learning
  • Heinbach, Jan Hendrick (2023): Visual partial inspection of re safety equipment using machine learning
  • Soultana, Ayman (2023): Building an Active Learning Application for Object Detection on a Technical Building Equipment Dataset


  • Joshi, Keyur (2023): Analyzing the Potential of Uncertainty Estimation for a Deep Learning Video-based Fire Detection Algorithm
  • Trost, Lukas (2023): Autonomous recognition of fire extinguisher types and fire classes in images