Jörg Blankenbach

Prof. Dr.-Ing.

RWTH Aachen University

Germany

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Prof. Dr.-Ing. Jörg Blankenbach is a faculty member at RWTH Aachen University in Germany. His research areas encompass structural monitoring, indoor localization, energy modeling, and the application of geostatistics in real-time geodata streams. He has contributed to various publications focusing on innovative methods for infrastructure analysis and the integration of digital twins in built environments.

Articles (15)

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2025

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2025

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2025

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2021

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2021

Collaborators (4)

Christian Heipke

Leibniz University Hannover

GERMANY

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Helmut Mayer

Professor

Bundeswehr University Munich

GERMANY

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Franz Rottensteiner

Associate Professor

Leibniz University Hannover

GERMANY

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Liqiu Meng

Technical University of Munich

GERMANY

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Jörg Blankenbach

Research Interests

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Articles (15)

Structural Monitoring Without a Budget—Laboratory Results and Field Report on the Use of Low-Cost Acceleration Sensors

Synergizing natural visual features and 3D building models for robust indoor localization in mixed reality environments

Geodata-based number of floor estimation for urban residential buildings as an input parameter for energy modelling

Hypermedia-driven RESTful API for digital twins of the built environment

Hierarchical SVM for Semantic Segmentation of 3D Point Clouds for Infrastructure Scenes

Geostatistics on Real-Time Geodata Streams—High-Frequent Dynamic Autocorrelation with an Extended Spatiotemporal Moran’s I Index

Thermal reality capturing with the Microsoft HoloLens 2 for energy system analysis

Geostatistics on Real-Time Geodata Streams—An Extended Spatiotemporal Moran’s I Index with Distributed Stream Processing Technologies

Geospatial Information Research: State of the Art, Case Studies and Future Perspectives

DeepLocBIM: Learning Indoor Area Localization Guided by Digital Building Models

Quality Assessment of a Novel Camera-Based Measurement System for Roughness Determination of Concrete Surfaces—Accuracy Evaluation and Validation

Multi-Task Neural Network for Position Estimation in Large-Scale Indoor Environments

DeepLocBox: Reliable Fingerprinting-Based Indoor Area Localization

Evolutionary Optimization Strategy for Indoor Position Estimation Using Smartphones

Three-dimensional CityGML building models in mobile augmented reality: a smartphone-based pose tracking system

Collaborators (4)

Christian Heipke

Helmut Mayer

Franz Rottensteiner

Liqiu Meng

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