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Prof. Dr. Florian Wahl

  • Data Analytics
  • Machine Learning
  • Pattern Recognition
  • Embedded Systems
  • Ubiquitous Computing

Professor


consulting time

by appointment via Mrs. Verena Windorfer-Bogner.


Sortierung:
Beitrag in Sammelwerk/Tagungsband

  • Domenic Sommer
  • Sebastian Wilhelm
  • Diane Ahrens
  • Florian Wahl

Implementing an Intersectoral Telemedicine Network in Rural Areas: Evaluation from the Point of View of Telemedicine Users

pg. 15-27.

  • (2023)

DOI: 10.5220/0011755500003476

  • TC Grafenau
  • DIGITAL
  • GESUND
Zeitschriftenartikel

  • Roman-David Kulko
  • Alexander Pletl
  • H. Mempel
  • Florian Wahl
  • Benedikt Elser

OpenVNT: An Open Platform for VIS-NIR Technology

In: Sensors vol. 23 pg. 3151.

  • (2023)

    ISSN: 1424-8220

DOI: 10.3390/s23063151

Spectrometers measure diffuse reflectance and create a “molecular fingerprint” of the material under investigation. Ruggedized, small scale devices for “in-field” use cases exist. Such devices might for example be used by companies in the food supply chain for inward inspection of goods. However, their application for the industrial Internet of Things workflows or scientific research is limited due to their proprietary nature. We propose an open platform for visible and near-infrared technology (OpenVNT), an open platform for capturing, transmitting, and analysing spectral measurements. It is built for use in the field, as it is battery-powered and transmits data wireless. To achieve high accuracy, the OpenVNT instrument contains two spectrometers covering a wavelength range of 400–1700 nm. We conducted a study on white grapes to compare the performance of the OpenVNT instrument against the Felix Instruments F750, an established commercial instrument. Using a refractometer as ground truth, we built and validated models to estimate the Brix value. As a quality measure, we used coefficient of determination of the cross-validation (R2CV) between the instrument estimation and ground truth. With 0.94 for the OpenVNT and 0.97 for the F750, a comparable R2CV was achieved for both instruments. OpenVNT matches the performance of commercially available instruments at one tenth of the price. We provide an open bill of materials, building instructions, firmware, and analysis software to enable research and industrial IOT solutions without the limitations of walled garden platforms.
  • TC Grafenau
  • DIGITAL
Beitrag in Sammelwerk/Tagungsband

  • Domenic Sommer
  • Tobias Greiler
  • Stefan Fischer
  • Sebastian Wilhelm
  • Lisa-Marie Hanninger
  • Florian Wahl

Investigating Use Requirements. A Participant Observation Study to Define the Information Needs at a Hospital Reception . (Short Paper)

pg. 1-10.

Springer Nature Switzerland AG

  • (2023)

DOI: 10.1007/978-3-031-35992-7_23

  • TC Grafenau
  • DIGITAL
  • GESUND
Vortrag

  • Florian Wahl

Das Unterstützungspotential von künstlicher Intelligenz in der Pflege

CARE REGIO Kempten

  • 24.03.2023 (2023)
  • Angewandte Informatik
  • DIGITAL
  • GESUND
Vortrag

  • Domenic Sommer
  • Miloslav Kovacevic
  • Florian Wahl

Caregivers Workplace Expectations and Job Satisfaction. Online Survey of Caregivers In Bavaria . Abstract und Poster

Hochschule Kempten Kempten

  • 23.-24.03.2023 (2023)
  • TC Grafenau
  • DIGITAL
  • GESUND
Vortrag

  • Florian Wahl

Unlocking the Potential of Artificial Intelligence in Care

Institut Nationale des Sciences Appliqués (INSA) Lyon Lyon, France

  • 10.05.2023 (2023)
  • Angewandte Informatik
  • DIGITAL
  • GESUND
Zeitschriftenartikel

  • Florian Wahl
  • Matthias Breslein
  • Benedikt Elser

On-demand forklift hailing system for Intralogistics 4.0

In: Procedia Computer Science vol. 200 pg. 878-886.

  • (2022)

    ISSN: 18770509

DOI: 10.1016/j.procs.2022.01.285

The shift to I4.0 is happening. While large companies have a range of solutions to implement that change, small and medium-sized enterprises (SME) fall short on solutions tailored for their specific needs. To support SMEs in their transformation toward I4.0, we propose a lightweight system to hail forklifts in a production facility of a medium-sized enterprise. Existing shop floor workflows are implemented within the system and allow machine operators to hail forklift drivers using an embedded or a web-based client. Forklift drivers receive driving instructions on their smartphones. Shift managers can monitor intralogistic activities on a dashboard. Management can extract relevant production and forklift KPIs from the system. In a two-week evaluation phase, we installed our system in a production facility for injection moulded plastic parts. We equipped 12 machines and two forklifts and registered a total of 690 jobs. We found half of the jobs were picked up in 4:05 min and 80% of all jobs were completed in less than 40:02 min.
  • TC Grafenau
  • DIGITAL
Vortrag

  • Florian Wahl

Das Unterstützungspotential von KI in der Pflege

Universität Passau Passau

  • 26.06.2022 (2022)
  • Angewandte Informatik
  • DIGITAL
  • GESUND
Vortrag

  • Florian Wahl

Wieviel Personal brauche ich morgen? Nachfrageprognose in der Stückgutlogistik . Posterpräsentation

Technische Hochschule Deggendorf Deggendorf

  • 10.04.2019 (2019)
  • TC Grafenau
  • Angewandte Informatik
  • Angewandte Wirtschaftswissenschaften
  • NACHHALTIG
  • DIGITAL
Vortrag

  • Florian Wahl

Produktion 4.0 in KMUs - Datenerhebung und Datenanalyse

XING Nutzergruppe FRG Schönberg

  • 06.06.2019 (2019)
  • TC Grafenau
  • Angewandte Informatik
  • DIGITAL
Vortrag

  • Florian Wahl

Produktion 4.0 in KMUs - Datenerhebung und Datenanalyse

Technische Hochschule Deggendorf Deggendorf

  • 05.06.2019 (2019)
  • TC Grafenau
  • Angewandte Informatik
  • DIGITAL
Vortrag

  • Florian Wahl

Building Industry 4.0 logistics applications with MicroPython and ESP32 MCUs

Basel, Schweiz

  • 11.07.2019 (2019)
  • TC Grafenau
  • Angewandte Informatik
  • DIGITAL
Vortrag

  • Florian Wahl

Data Science with Python

Passau

  • 17.10.2019 (2019)
  • TC Grafenau
  • Angewandte Informatik
  • DIGITAL
Vortrag

  • Florian Wahl

Data Science with Python

Hochschulgruppe Deggendorf der Gesellschaft für Informatik Deggendorf

  • 27.06.2019 (2019)
  • TC Grafenau
  • Angewandte Informatik
  • DIGITAL
Vortrag

  • Michael Fernandes
  • Florian Wahl

Tomatenkrimi - Der Foodscanner als Ermittler . Keynote

Grafenau

  • 12.07.2019 (2019)
  • TC Grafenau
  • Angewandte Informatik
  • NACHHALTIG
Vortrag

  • Florian Wahl

Wieviel Personal brauche ich morgen? . Best Presentation Award

Technische Hochschule Deggendorf Deggendorf

  • 10.04.2019 (2019)
  • TC Grafenau
  • Angewandte Informatik
  • Angewandte Wirtschaftswissenschaften
  • NACHHALTIG
  • DIGITAL
Zeitschriftenartikel

  • Florian Wahl
  • O. Amft

Data and Expert Models for Sleep Timing and Chronotype Estimation from Smartphone Context Data and Simulations

In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (Association for Computing Machinery, NY, USA) vol. 2

  • (2018)

DOI: 10.1145/3264949

We present a sleep timing estimation approach that combines data-driven estimators with an expert model and uses smartphone context data. Our data-driven methodology comprises a classifier trained on features from smartphone sensors. Another classifier uses time as input. Expert knowledge is incorporated via the human circadian and homeostatic two process model. We investigate the two process model as output filter on classifier results and as fusion method to combine sensor and time classifiers. We analyse sleep timing estimation performance, in data from a two-week free-living study of 13 participants and sensor data simulations of arbitrary sleep schedules, amounting to 98280 nights. Five intuitive sleep parameters were derived to control the simulation. Moreover, we investigate model personalisation, by retraining classifiers based on participant feedback. The joint data and expert model yields an average relative estimation error of -2±62 min for sleep onset and -5±70 min for wake (absolute errors 40±48 min and 42±57 min, mean median absolute deviation 22 min and 15 min), which significantly outperforms data-driven methods. Moreover, the data and expert models combination remains robust under varying sleep schedules. Personalising data models with user feedback from the last two days showed the largest performance gain of 57% for sleep onset and 59% for wake up. Our power-efficient smartphone app makes convenient everyday sleep monitoring finally realistic.
  • TC Grafenau
  • Angewandte Informatik
  • DIGITAL