TY  - CHAP
A1  - Altherr, Lena
A1  - Conzen, Max
A1  - Elsen, Ingo
A1  - Frauenrath, Tobias
A1  - Lyrmann, Andreas
ED  - Reiff-Stephan, Jörg
ED  - Jäkel, Jens
ED  - Schwarz, André
T1  - Sensor retrofitting of existing buildings in an interdisciplinary teaching project at university level
T2  - Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel
N2  - Existing residential buildings have an average lifetime of 100 years. Many of these buildings will exist for at least another 50 years. To increase the efficiency of these buildings while keeping costs at reasonable rates, they can be retrofitted with sensors that deliver information to central control units for heating, ventilation and electricity. This retrofitting process should happen with minimal intervention into existing infrastructure and requires new approaches for sensor design and data transmission. At FH Aachen University of Applied Sciences, students of different disciplines work together to learn how to design, build, deploy and operate such sensors. The presented teaching project already created a low power design for a combined CO2, temperature and humidity measurement device that can be easily integrated into most home automation systems
KW  - Building Automation
KW  - Smart Building
KW  - CO2
KW  - Carbon Dioxide
KW  - Education
Y1  - 2023
SN  - 978-3-910103-01-6
U6  - http://dx.doi.org/10.33968/2023.04
N1  - 19. AALE-Konferenz. Luxemburg, 08.03.-10.03.2023.
BTS Connected Buildings & Cities Luxemburg
(Tagungsband unter https://doi.org/10.33968/2023.01)
SP  - 31
EP  - 40
PB  - le-tex publishing services GmbH
CY  - Leipzig
ER  - 
TY  - CHAP
A1  - Arndt, Tobias
A1  - Conzen, Max
A1  - Elsen, Ingo
A1  - Ferrein, Alexander
A1  - Galla, Oskar
A1  - Köse, Hakan
A1  - Schiffer, Stefan
A1  - Tschesche, Matteo
T1  - Anomaly detection in the metal-textile industry for the reduction of the cognitive load of quality control workers
T2  - PETRA '23: Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments
N2  - This paper presents an approach for reducing the cognitive load for humans working in quality control (QC) for production processes that adhere to the 6σ -methodology. While 100% QC requires every part to be inspected, this task can be reduced when a human-in-the-loop QC process gets supported by an anomaly detection system that only presents those parts for manual inspection that have a significant likelihood of being defective. This approach shows good results when applied to image-based QC for metal textile products.
KW  - Datasets
KW  - Neural networks
KW  - Anomaly detection
KW  - Quality control
KW  - Process optimization
Y1  - 2023
SN  - 9798400700699
U6  - http://dx.doi.org/10.1145/3594806.3596558
N1  - PETRA '23: Proceedings of the 16th International Conference on Pervasive Technologies Related to Assistive Environments, Corfu Greece, July 5 - 7, 2023.
SP  - 535
EP  - 542
PB  - ACM
ER  - 
TY  - CHAP
A1  - Thoma, Andreas
A1  - Stiemer, Luc
A1  - Braun, Carsten
A1  - Fisher, Alex
A1  - Gardi, Alessandro G.
T1  - Potential of hybrid neural network local path planner for small UAV in urban environments
T2  - AIAA SCITECH 2023 Forum
N2  - This work proposes a hybrid algorithm combining an Artificial Neural Network (ANN) with a conventional local path planner to navigate UAVs efficiently in various unknown urban environments. The proposed method of a Hybrid Artificial Neural Network Avoidance System is called HANNAS. The ANN analyses a video stream and classifies the current environment. This information about the current Environment is used to set several control parameters of a conventional local path planner, the 3DVFH*. The local path planner then plans the path toward a specific goal point based on distance data from a depth camera. We trained and tested a state-of-the-art image segmentation algorithm, PP-LiteSeg. The proposed HANNAS method reaches a failure probability of 17%, which is less than half the failure probability of the baseline and around half the failure probability of an improved, bio-inspired version of the 3DVFH*. The proposed HANNAS method does not show any disadvantages regarding flight time or flight distance.
Y1  - 2023
U6  - http://dx.doi.org/10.2514/6.2023-2359
N1  - AIAA SCITECH 2023 Forum, 23-27 January 2023, National Harbor, MD & Online
PB  - AIAA
ER  -