Marcus Dombois, M.Sc.
Institute of Numerical Methods and Informatics in Civil Engineering
Critical Infrastructures and Emergency Information Management
Data Mining and Machine Learning
- Extraction and processing of information and knowledge from structured and unstructured data
- Automated collection of sensor data
Indoor Tracking and Navigation
- Usage of mobile devices
- Integration of digital building models
- Use of various sensors such as Wi-Fi, Bluetooth LE or inertial sensors
- Sensor fusion
Building Information Modeling (BIM)
Multiscale Information System for Emergency Management and Mission Planning
In an emergency situation information and knowledge are critical for effective mission planning and response actions. Even though large amounts of information are collected in the operational control center, there are two big problems that can be identified. Firstly, because of data complexity and the amount of unstructured information, emergency dispatchers tend to be overwhelmed due to a lacking information management and therefore cannot take advantage of the information. Secondly, a lot of information such as weather, social media, ad hoc information from emergency responders and so on, despite potentially being available, are not considered for the use in emergency response.
Within this thesis processes and information in the area of emergency response will be analyzed and a general data model for the representation of emergency-related information will be developed. Based on the data model data mining and information retrieval techniques as well as machine learning methods will be applied for automatically processing available data and information sources to help optimize the information management process. The research is focused on the integration and processing of so far unused information, especially ad hoc information and data from critical infrastructures such as telecommunication. Furthermore the effects and the perception of “knowing” and “not knowing” and how it can affect the decision making process are analyzed.
Number of items: 11.
Engels, Jens Ivo ; Monstadt, Jochen ; Dombois, Marcus ; Frank, Sybille ; Stahlhut, Chris ; Enders, Tina
Bittner, Timo ; Eller, Christian ; Dombois, Marcus ; Rüppel, Uwe (2018):
Bittner, Timo ; Eller, Christian ; Dombois, Marcus ; Rüppel, Uwe
Crespo, Arturo ; Dombois, Marcus ; Henning, Jan (2018):
Engels, Jens Ivo ; Lukitsch, Kristof ; Müller, Marcel ; Stahlhut, Chris ; Eifert, Stephanie ; Knauf, Alice ; Thiessen, Nadja ; Elsner, Ivonne ; Huck, Andreas ; Marathe, Manas ; Crespo, Arturo ; Dombois, Marcus ; Henning, Jan (2018):
Eller, Christian ; Bittner, Timo ; Dombois, Marcus ; Rüppel, Uwe (2018):
Dombois, Marcus ; Bittner, Timo ; Rüppel, Uwe
Dombois, Marcus ; Döweling, S. (2016):
Dombois, Marcus (2016):
Dombois, Marcus (2013):