"This site requires JavaScript to work correctly"
minimize Header

Sebastian Wilhelm, M.Sc.

Applied Research in Engineering Sciences (Applied Computer Science)

Centre for Applied Research

Technology Campus Grafenau

Academic Staff

Grafenau

08552/975620-25

Sortierung:
Contribution
  • Sebastian Wilhelm
  • Dietmar Jakob

Digital support for managing Organized Neighborhood Assistance.

In: Applied Research Conference (ARC) 2019. pg. 531-535

  • Eds.:
  • M. Reichenberger
  • J. Mottok

  • (2019)

show abstract

In the context of demographic change and an aging society, neighborhood help is playing an increasingly important role in our society. Within this work a framework for developing a digital platform to manage an Organized Neighborhood Assistance is developed. A special focus lies on analyzing the functional, technical and legal requirements.
Contribution
  • Sebastian Wilhelm
  • A. Gerl

Policy-based Authentication and Authorization based on the Layered Privacy Language.

In: Workshopband zur 18. Fachtagung "Datenbanksysteme für Business, Technologie und Web". pg. 245-255

  • Eds.:
  • D. Nicklas
  • A. Thor
  • N. Ritter
  • M. Klettke
  • A. Heuer
  • H. Meyer

  • (2019)

DOI: 10.18420/btw2019-ws-25

show abstract

In 2018 the General Data Protection Regulation (GDPR) has been enforced providing a new legal framework with rules and regulations for processing personal data. The requirement for distinguishing between purposes has been introduced, leading to the necessity of adapting existing authentication and authorization processes. We introduce a detailed authentication and authorization extension, which is able to verify requests on personal data based on the Layered Privacy Language (LPL). This extension is evaluated in the form of a benchmark, utilizing the Policy-based De-identification, to demonstrating its efficiency and suitability for data-warehouses.
Contribution
  • Sebastian Wilhelm
  • Dietmar Jakob
  • Melanie Dietmeier

Development of a senior-friendly training concept for imparting media literacy.

In: INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik - Informatik für Gesellschaft. 49. GI-Jahrestagung INFORMATIK 2019 (Lecture Notes in Informatics (LIN)) pg. 699-710

  • Eds.:
  • K. David
  • M. Lange
  • G. Stumme
  • K. Geihs

Bonn

  • (2019)

DOI: 10.18420/inf2019_83

show abstract

The use of digital solutions to support rural areas, and in particular elderly people, is the goal of the ‘Digitales Dorf’ and ‘BLADL’ research projects. This work assessed seniors’ media literacy in two model communities; with the result that fear of fraudster and lack of knowledge are the most common causes that prevent elderly people from using digital technologies. Based on these evaluation results, a combined training offer of tutorial and digital consultation hour was developed and evaluated.
Contribution
  • Sebastian Wilhelm
  • Dietmar Jakob
  • Diane Ahrens

Human Presence Detection by monitoring the indoor CO2 concentration.

In: Tagungsband zur Konferenz Mensch und Computer 2020 (06.-09.09.2020; Magdeburg). pg. 199-203

  • (2020)

DOI: 10.1145/3404983.3409991

show abstract

Presence detection systems are becoming more and more important and are used in smart home environments in the Ambient Assisted Living (AAL) domain or in surveillance technology. Common systems focus on using motion sensors or cameras which have only a limited viewing angle and therefore monitoring gaps can easily occur within a room. Humans produce carbon dioxide (CO2) through their respiration which is distributed in rooms. As a result if one (or more) persons are in a room a significant increase in CO2 concentration in the room can be noted. With this work we investigate an approach to detect the presence or absence of people indoors by monitoring the CO2 concentration in the ambient air.
Contribution
  • Dietmar Jakob
  • Sebastian Wilhelm
  • A. Gerl

Data Privacy Management (DPM) - A Private Household Smart Metering Use Case.

In: Workshopband 6. Usable Security und Privacy Workshop im Rahmen der Konferenz Mensch und Computer 2020 (06.-09.09.2020; Magdeburg).

  • Eds.:
  • B. Preim
  • A. Nürnberger
  • C. Hansen

  • (2020)

DOI: 10.18420/muc2020-ws119-003

show abstract

The automated collection of real life data in private households places special requirements on a Data Privacy Management (DPM) concept. The development and implementation of a DPM concept for use in a scientific environment is demonstrated according to a successful use case – the project BLADL. The intention of this paper is to provide a guideline for ethical and privacy-preserving data collection and management in research projects in the EU. 
Contribution
  • Dietmar Jakob
  • Sebastian Wilhelm

Amazon Echo: A Benchmarking Model Review.

In: Proceedings of the 14th International Conference on Interfaces and Human Computer Interaction (23-25 July 2020; Zagreb, Croatia).

  • (2020)

show abstract

Smart speakers are becoming increasingly popular. The market leader for smart speakers are the products of the Echo family from Amazon. There are currently 9 different models with different technical specifications available in Germany. With this paper, the models was benchmarked against each other in terms of (i) speech recognition reliability, (ii) output sound pressure and (iii) power consumption in a laboratory experiment. Previous works in this area has only considered individual models of the product family. Significant differences in speech recognition accuracy, output sound pressure and power consumption were identified between the models. In general it was observed, that the Echo Show 8 model was the most efficient in terms of the above criterias.
Contribution
  • Sebastian Wilhelm
  • Dietmar Jakob
  • Jakob Kasbauer
  • Melanie Dietmeier
  • A. Gerl
  • Benedikt Elser
  • Diane Ahrens

Organizational, Technical, Ethical and Legal Requirements of Capturing Household Electricity Data for Use as an AAL System.

In: Proceedings of the Fifth International Congress on Information and Communication Technology (ICPCCI 2019) [20-21 February 2020; London, UK]. (Advances in Intelligent Systems and Computing)

Springer International Publishing Singapore

  • (2020)

DOI: 10.1007/978-981-15-5856-6_38

show abstract

Due to demographic change elderly care is one of the major challenges for society in near future fostering new services to support and enhance the life quality of the elderly generation. A particular aspect is the desire to live in one’s homes instead of hospitals and retirement homes as long as possible. Therefore it is essential to monitor the health status i.e. the activity of the individual. In our data-driven society data is collected at an increasing rate enabling personalized services for our daily life using machine-learning and data mining technologies. However the lack of labeled datasets from a realistic environment hampers research for training and evaluating algorithms. In the project BLADL we use data mining technologies to gauge the health status of elderly people. Within this work we discuss the challenges and caveats both from a technical and ethical perspectives to create such a dataset.
Book
  • S. Sczogiel
  • A. Busch
  • A. Göller
  • A. Gabber
  • B. Williger
  • S. Schmitt-Rüth
  • Diane Ahrens
  • Dietmar Jakob
  • Sebastian Wilhelm

Digital fit im Alter. Handlungsempfehlung für Gemeinden zu Bildungsangeboten für Senioren (Hg.: Fraunhofer-Institut für Integrierte Schaltungen [IIS]; Technische Hochschule Deggendorf [THD]).

  • (2020)

DOI: 10.13140/RG.2.2.23245.05609

show abstract

Ziel der Broschüre ist es, Gemeinden insbesondere im ländlichen Raum, über die Konzeption von Bildungsangeboten für ältere Menschen zu informieren und sie dazu zu befähigen, ähnliche Initiativen in ihren Gemeinden zu starten.
Lecture
  • Sebastian Wilhelm

Activity Monitoring reusing Home Infrastructure Data.

In: Digital French-German Summer School with Industry 2020

  • 04.06.2020 (2020)
Lecture
  • Dietmar Jakob
  • Sebastian Wilhelm

Prozessablauf von automatisierten Datenerhebungen in privaten Haushalten – Erfahrungsbericht.

In: Data2Day 2020 - Konferenz für Big Data, Data Science und Machine Learning

Print Media Academy Heidelberg (online)

  • 20.10.2020 (2020)

show abstract

Smarte Technologien erzeugen Datenströme, die unter anderem für personalisierte Mehrwertdienste genutzt werden können. Zur Entwicklung entsprechender Dienste und intelligenter Algorithmen ist es häufig notwendig, gelabelte Rohdaten zu sammeln.  Dabei sind neben den technischen Herausforderungen auch Datenschutzbestimmungen und ethische Fragestellungen zu berücksichtigen.  In unserem Vortrag präsentieren wir einen Erfahrungsbericht über die Erhebung von Stromverbrauchsdaten in 20 privaten Haushalten, beginnend bei der Auswahl der Testhaushalte, der Sicherstellung einer informierten Zustimmung, die Installation der technischen Komponenten bis zur Anonymisierung und Veröffentlichung der Daten.
Lecture
  • Sebastian Wilhelm

Activity Monitoring reusing Home Infrastructure Data.

In: IRIXYS - Young Scientists’ Workshop

Online

  • 18.11.2020 (2020)
Contribution
  • Sebastian Wilhelm

Activity-monitoring in Private Households for Emergency Detection: A Survey of Common Methods and Existing Disaggregable Data Sources.

In: Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies. pg. 263-272

SCITEPRESS - Science and Technology Publications

  • (2021)

DOI: 10.5220/0010180002630272

Contribution
  • Dietmar Jakob
  • Sebastian Wilhelm
  • A. Gerl
  • Diane Ahrens

A Quantitative Study on Awareness, Usage and Reservations of Voice Control Interfaces by Elderly People.

In: Proceedings of the 23rd International Conference on Human-Computer Interaction (HCII 2021) [July 24–29, 2021; online]. (Lecture Notes in Computer Science (LNCS))

  • (2021)

show abstract

One third of Germans talk to ’Alexa’, ’Siri’ and other voice-controlled devices. These devices become omnipresent and change the way how humans interact with digital technologies. We hypothesize, this Human-Computer-Interface can minimize barriers for elderly people in their usage of digital services. But, do elderly people even know about voice-controlled technologies? Are the systems used by elderly and what reservations do they have? Based on a quantitative study in three municipalities in a rural area (n = 747), we found that 59% of people aged 55+ years know voice-controlled devices, 37% used them at least once and even 26% use them regularly. But, more than two thirds of respondents (69%) are concerned that their data are not safe. In contrast, only 35% express concerns to be unable to use the devices. The study concludes that there is a gap between the perceived usefulness and trust in the devices for the surveyed demographic.
Contribution
  • Sebastian Wilhelm

Exploiting Home Infrastructure Data for the Good: Emergency Detection by Reusing Existing Data Sources.

In: Human Interaction, Emerging Technologies and Future Applications IV. (Advances in Intelligent Systems and Computing) vol. 1378 pg. 51-58

  • Eds.:
  • T. Ahram
  • R. Taiar
  • F. Groff

Springer International Publishing Cham

  • (2021)

DOI: 10.1007/978-3-030-74009-2_7

Journal article
  • Sebastian Wilhelm
  • Jakob Kasbauer

Exploiting Smart Meter Power Consumption Measurements for Human Activity Recognition (HAR) with a Motif-Detection-Based Non-Intrusive Load Monitoring (NILM) Approach.

In: Sensors vol. 21 pg. 8036

  • (2021)

DOI: 10.3390/s21238036

show abstract

Numerous approaches exist for disaggregating power consumption data, referred to as non-intrusive load monitoring (NILM). Whereas NILM is primarily used for energy monitoring, we intend to disaggregate a household’s power consumption to detect human activity in the residence. Therefore, this paper presents a novel approach for NILM, which uses pattern recognition on the raw power waveform of the smart meter measurements to recognize individual household appliance actions. The presented NILM approach is capable of (near) real-time appliance action detection in a streaming setting, using edge computing. It is unique in our approach that we quantify the disaggregating uncertainty using continuous pattern correlation instead of binary device activity states. Further, we outline using the disaggregated appliance activity data for human activity recognition (HAR). To evaluate our approach, we use a dataset collected from actual households. We show that the developed NILM approach works, and the disaggregation quality depends on the pattern selection and the appliance type. In summary, we demonstrate that it is possible to detect human activity within the residence using a motif-detection-based NILM approach applied to smart meter measurements.
Contribution
  • Sebastian Wilhelm
  • Dietmar Jakob
  • Jakob Kasbauer
  • Diane Ahrens

GeLaP: German Labeled Dataset for Power Consumption.

In: Proceedings of Sixth International Congress on Information and Communication Technology. (Lecture Notes in Networks and Systems) vol. 235 pg. 21-33

  • Eds.:
  • Nilanjan Dey
  • Amit Joshi
  • Simon Sherratt
  • Xin-She Yang

Springer Singapore Singapore

  • (2022)

DOI: 10.1007/978-981-16-2377-6_5

show abstract

Due to the increasing spread of smart meters, numerous researchers are currently working on disaggregating the power consumption data. This procedure is commonly known as Non-Intrusive Load Monitoring (NILM). However, most approaches to energy disaggregation first require a labeled dataset to train these algorithms. In this paper, we present a new labeled power consumption dataset that was collected in 20 private households in Germany between September 2019 and July 2020. For this purpose, the total power consumption of each household was measured with a commercial available smart meter and the individual consumption data of 10 selected household appliances were collected.
Contribution
  • Dietmar Jakob
  • Sebastian Wilhelm

Voice Controlled Devices: Awareness, Usage and Reservations of Young Adults.

In: Proceedings of the 7th International Conference on Human Interaction & Emerging Technologies: Artificial Intelligence & Future Applications. (Advances in Intelligent Systems and Computing (AISC))

  • (2022)

show abstract

Voice Controlled Devices (VCDs) are becoming increasingly popular, both as integrated voice control functionality in mobile and stationary devices and in the form of devices that can be controlled primarily by voice, such as smart speakers. Young adults have already grown up with digital technologies that can be operated via peripherals or touchscreens. It is particularly interesting whether this younger generation, familiar with conventional human-computer interfaces, will accept the voice control function. In this context, however, there is a lack of studies that address awareness, usage, and reservations of voice-controlled interfaces among young adults. This paper presents a quantitative study (n=246) that shows that while 96% of young adults are aware of VCDs, only 18% regularly use the voice control feature. However, 77% expressed concerns that their data would not be safe by using VCDs.
Contribution
  • Sebastian Wilhelm
  • Dietmar Jakob

Evaluating the Efficiency and Sustainability of a Training Concept for Imparting Media Literacy to the Elderly.

In: Proceedings of the 7th International Conference on Human Interaction & Emerging Technologies: Artificial Intelligence & Future Applications. (Advances in Intelligent Systems and Computing (AISC))

  • (2022)

show abstract

Elderly people often feel overstrained by the increasingly fast progress of digitization. Due to the strongly informal learning behavior of the elderly, particular concepts for improving their media literacy are needed to reduce existing barriers. Numerous concepts for this have already been developed, but their success has not yet been comprehensively evaluated. This study examines the suitability of an existing, two-part training concept consisting of seminars and supportive consultation hours for the sustainable teaching of media literacy in dealing with smartphones, tablets, or PCs. For this purpose, a quantitative study is conducted among participants of a corresponding offer (N=100). This work confirms that seminars in small groups combined with supportive consultation hours are very well suited to impart the media literacy of elderly people in the long term. 82% of respondents stated that their media literacy had improved after taking part in a seminar (n=74), and 86% now claim to use at least one digital device more often (n=74).
Contribution
  • Sebastian Wilhelm
  • Dietmar Jakob
  • A. Gerl
  • S. Schiegg

Die Vision eines Personal Information Management-System (PIMS) durch automatisierte Datenschutzselbstauskunft.

In: Daten-Fairness in einer globalisierten Welt. pg. 373-398

  • Eds.:
  • G. Hornung
  • R. Neuburger
  • M. Friedewald
  • F. Bieker
  • A. Roßnagel

Nomos Verlagsgesellschaft mbH & Co. KG

  • (2023)

DOI: 10.5771/9783748938743-373

Contribution
  • 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.

In: Proceedings of the 9th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE). pg. 15-27

  • (2023)

DOI: 10.5220/0011755500003476

Contribution
  • 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).

In: HCI International 2023 Posters. 25th International Conference on Human-Computer Interaction, HCII 2023, Copenhagen, Denmark, July 23–28, 2023, Proceedings, Part II (Communications in Computer and Information Science) pg. 1-10

  • Eds.:
  • G. Salvendy
  • C. Stephanidis
  • S. Ntoa
  • M. Antona

Springer Nature Switzerland AG

  • (2023)

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

Contribution
  • Sebastian Wilhelm
  • Jakob Folz
  • Florian Wahl

Open Personal Data: Anonymisierung im Spannungsfeld zwischen Informationsgehalt und Robustheit.

In: Data Sharing: Datenkapitalismus by Default?. Posterproceedings - Forum Privatheit 2023 pg. 36

  • Eds.:
  • M. Friedewald
  • M. Karaboga

Fraunhofer-Institut für System- und Innovationsforschung ISI

  • (2023)
Journal article
  • Sebastian Wilhelm
  • Jakob Kasbauer
  • Dietmar Jakob
  • Benedikt Elser
  • Diane Ahrens

Exploiting Smart Meter Water Consumption Measurements for Human Activity Event Recognition.

In: Journal of Sensor and Actuator Networks (Special Issue Smart Cities and Homes: Current Status and Future Possibilities) vol. 12

  • (2023)

DOI: 10.3390/jsan12030046

show abstract

Human activity event recognition (HAER) within a residence is a topic of significant interest in the field of ambient assisted living (AAL). Commonly, various sensors are installed within a residence to enable the monitoring of people. This work presents a new approach for HAER within a residence by (re-)using measurements from commercial smart water meters. Our approach is based on the assumption that changes in water flow within a residence, specifically the transition from no flow to flow above a certain threshold, indicate human activity. Using a separate, labeled evaluation data set from three households that was collected under controlled/laboratory-like conditions, we assess the performance of our HAER method. Our results showed that the approach has a high precision (0.86) and recall (1.00). Within this work, we further recorded a new open data set of water consumption data in 17 German households with a median sample rate of 0.083̲ Hz to demonstrate that water flow data are sufficient to detect activity events within a regular daily routine. Overall, this article demonstrates that smart water meter data can be effectively used for HAER within a residence.
Contribution
  • Dietmar Jakob
  • Sebastian Wilhelm
  • Armin Gerl
  • Florian Wahl
  • Diane Ahrens

Voice Controlled Devices: A Comparative Study of Awareness, Ownership, Usage, and Reservations Between Young and Older Adults.

In: Human Aspects of IT for the Aged Population. Proceedings (Part I) of the 9th International Conference ITAP 2023 - Human Aspects of IT for the Aged Population - Held as Part of the 25th HCI International Conference (HCII) 2023 (Copenhagen, Denmark; July 23–28, 2023) (Lecture Notes in Computer Science) vol. 14042 pg. 348-365

  • Eds.:
  • J. Zhou
  • Q. Gao

Springer Nature Switzerland Cham

  • (2023)

DOI: 10.1007/978-3-031-34866-2_25

Lecture
  • Norbert Lichtenauer
  • Sebastian Wilhelm
  • Florian Wahl

EAsyAnon – Empfehlungs- und Auditsystem zur Anonymisierung.

In: Forschungsfrühstück der Technischen Hochschule Deggendorf am Gesundheitscampus Bad Kötzting

Bad Kötzting

  • 16.06.2023 (2023)
Lecture
  • Norbert Lichtenauer
  • Sebastian Wilhelm

Anonymization of personal health Data is open data: A systematic analysis of enabling factors and barriers in the EAsyAnon Project.

In: DigiHealthDay 2023 – International Scientific Symposium at DIT-ECRI

Pfarrkirchen

  • 09.-11.11.2023 (2023)
UnpublishedWork
  • Jakob Folz
  • Robert Aufschläger
  • Manjitha Vidanalage
  • E. März
  • J. Guggumos
  • Md Moin Uddin
  • Sebastian Wilhelm

Software Requirements Specification: EAsyAnon Audit System.

Zenodo Deggendorf Institute of Technology via Zenodo

  • 2024 (2024)

DOI: 10.5281/zenodo.13734418

Contribution
  • Florian Wahl
  • Sebastian Wilhelm

Sensorik und künstliche Intelligenz in der Pflege.

In: Digitale Innovationen in der Pflege. pg. 307-324

  • Eds.:
  • W. Swoboda
  • N. Seifert

Springer Berlin Heidelberg Berlin, Heidelberg

  • (2024)

DOI: 10.1007/978-3-662-67914-2_12

show abstract

Pflegesysteme befinden sich im Dilemma zwischen einer steigenden Anzahl Pflegebedürftiger einerseits und dem Fachkräftemangel auf Seiten der Pflegekräfte andererseits. Bis 2030 erwartet die Bertelsmannstiftung eine Lücke von 260 bis 490 Tausend Pflegekräften. Der Einsatz von Technologien wie Sensorik und KI bietet hier vielversprechende Lösungen, um Pflegekräfte zu entlasten, die Effizienz in der Pflege zu steigern und gleichzeitig die Lebensqualität von Pflegebedürftigen zu erhöhen. Die Entwicklungen in den Bereichen KI und Sensorik erlauben uns künftig diese Technologien intesiver in der Pflege einzusetzen. In diesem Kapitel geben wir eine kurze Übersicht über die Grundlagen der (KI) und typische Sensormodalitäten. Anschließend stellen wir die typischen Analyseebenen vor, welche für KI-Anwendungen im Pflegebereich interessan sind. Bevor wir ein Fazit ziehen, beschreiben wir zwei Beispielanwendungen: Die Aktivitätserkennung mittels Sensorbrille sowie die Notfallerkennung auf Basis von Smart-Meter Daten. Wir sind der Überzeugung, dass KI in der Zukunft einen signifikanten Beitrag zur Effizienzsteigerung und Verbesserung der Pflege beitragen kann und wird.
Journal article
  • Norbert Lichtenauer
  • Lukas Schmidbauer
  • Sebastian Wilhelm
  • Florian Wahl

A Scoping Review on Analysis of the Barriers and Support Factors of Open Data.

In: Information vol. 15 pg. 5

  • 20 December 2023 (2024)

DOI: 10.3390/info15010005

show abstract

ackground: Using personal data as Open Data is a pervasive topic globally, spanning various sectors and disciplines. Recent technological advancements, particularly in artificial intelligence and algorithm-driven analysis, have significantly expanded the capacity for the automated analysis of vast datasets. There’s an expectation that Open Data analysis can drive innovation, enhance services, and streamline administrative processes. However, this necessitates a legally and ethically sound framework alongside intelligent technical tools to comprehensively analyze data for societal benefit. Methodology: A systematic review across seven databases (MEDLINE, CINAHL, BASE, LIVIVO, Web of Science, IEEExplore, and ACM) was conducted to assess the current research on barriers, support factors, and options for the anonymized processing of personal data as Open Data. Additionally, a supplementary search was performed in Google Scholar. A total of 𝑛=1192 studies were identified, and 𝑛=55 met the inclusion criteria through a multi-stage selection process for further analysis. Results: Fourteen potential supporting factors (𝑛=14) and thirteen barriers (𝑛=13) to the provision and anonymization of personal data were identified. These encompassed technical prerequisites as well as institutional, personnel, ethical, and legal considerations. These findings offer insights into existing obstacles and supportive structures within Open Data processes for effective implementation.
UnpublishedWork
  • Jakob Folz
  • Manjitha Vidanalage
  • J. Guggumos
  • Sebastian Wilhelm

Software Requirements Specification: EAsyAnon Trust Service.

Zenodo Deggendorf Institute of Technology via Zenodo

  • 2024 (2024)

DOI: 10.5281/zenodo.13740256

Journal article
  • Sebastian Wilhelm
  • Florian Wahl

Emergency Detection in Smart Homes Using Inactivity Score for Handling Uncertain Sensor Data.

In: Sensors vol. 24

  • 12.10.2024 (2024)

DOI: 10.3390/s24206583

show abstract

In an aging society, the need for efficient emergency detection systems in smart homes is becoming increasingly important. For elderly people living alone, technical solutions for detecting emergencies are essential to receiving help quickly when needed. Numerous solutions already exist based on wearable or ambient sensors. However, existing methods for emergency detection typically assume that sensor data are error-free and contain no false positives, which cannot always be guaranteed in practice. Therefore, we present a novel method for detecting emergencies in private households that detects unusually long inactivity periods and can process erroneous or uncertain activity information. We introduce the Inactivity Score, which provides a probabilistic weighting of inactivity periods based on the reliability of sensor measurements. By analyzing historical Inactivity Scores, anomalies that potentially represent an emergency can be identified. The proposed method is compared with four related approaches on seven different datasets. Our method surpasses existing approaches when considering the number of false positives and the mean time to detect emergencies. It achieves an average detection time of approximately 05:23:28 h with only 0.09 false alarms per day under noise-free conditions. Moreover, unlike related approaches, the proposed method remains effective with noisy data.
Journal article
  • E. März
  • J. Guggumos
  • Sebastian Wilhelm

Wie viel Open Data kann es geben?.

In: Datenschutz und Datensicherheit - DuD vol. 48 pg. 378-382

  • (2024)

DOI: 10.1007/s11623-024-1925-y

show abstract

In Zeiten wachsender Datenmengen und eines zunehmenden Interesses an Open Data steht die Frage im Raum: “Wie viel Offenheit ist möglich?” Zentrale Zielsetzung jeder Veröffentlichung von Daten als Open Data ist deren Anonymität. Nur dann liegen die Daten außerhalb des Geltungsbereichs der Datenschutz-Grundverordnung. Die steigende Verfügbarkeit von personenbezogenen Zusatzinformationen aus öffentlichen Quellen wie sozialen Medien erschweren allerdings die Anonymisierung, weil mit zunehmender Datenmenge auch die Möglichkeiten einer Verknüpfung von Daten (Data Linkage) zunehmen und damit auch das Risiko einer möglichen Re-Identifizierung steigt. Die Veröffentlichung von anonymisierten Daten erfordert daher aufgrund des unumkehrbaren Charakters eine umfassende Analyse der Re-Identifizierungsrisiken.
UnpublishedWork
  • Jakob Folz
  • Robert Aufschläger
  • Manjitha Vidanalage
  • E. März
  • J. Guggumos
  • Md Moin Uddin
  • Sebastian Wilhelm

Software Requirements Specification: EAsyAnon Recommender System.

Zenodo Deggendorf Institute of Technology via Zenodo

  • 2024 (2024)

DOI: 10.5281/zenodo.13318624

Journal article
  • Domenic Sommer
  • Sebastian Wilhelm
  • Florian Wahl

Nurses’ Workplace Perceptions in Southern Germany—Job Satisfaction and Self-Intended Retention towards Nursing.

In: Healthcare vol. 12 pg. 172

  • (2024)

DOI: 10.3390/healthcare12020172

show abstract

Our cross-sectional study, conducted from October 2022 to January 2023, aims to assess post-COVID job satisfaction, crucial work dimensions, and self-reported factors influencing nursing retention. Using an online survey, we surveyed 2572 nurses in different working fields in Bavaria, Germany. We employed a quantitative analysis, including a multivariable regression, to assess key influence factors on nursing retention. In addition, we evaluated open-ended questions via a template analysis to use in a joint display. In the status quo, 43.2% of nurses were not committed to staying in the profession over the next 12 months. A total of 66.7% of our surveyed nurses were found to be dissatisfied with the (i) time for direct patient care. Sources of dissatisfaction above 50% include (ii) service organization, (iii) documentation, (iv) codetermination, and (v) payment. The qualitative data underline necessary improvements in these areas. Regarding retention factors, we identified that nurses with (i) older age, (ii) living alone, (iii) not working in elder care, (iv) satisfactory working hours, (v) satisfactory career choice, (vi) career opportunities, (vii) satisfactory payment, and (viii) adequate working and rest times are more likely to remain in the profession. Conversely, dissatisfaction in (ix) supporting people makes nurses more likely to leave their profession and show emotional constraints. We uncovered a dichotomy where nurses have strong empathy for their profession but yearn for improvements due to unmet expectations. Policy implications should include measures for younger nurses and those in elderly care. Nevertheless, there is a need for further research, because our research is limited by potential bias from convenience sampling, and digitalization will soon show up as a potential solution to improve, e.g., documentation and enhanced time for direct patient time.
Lecture
  • Norbert Lichtenauer
  • Sebastian Wilhelm
  • Lukas Schmidbauer
  • Florian Wahl

EAsyAnon - Empfehlungs- und Auditsystem zur Anonymisierung. Poster: "Analysis of barriers and support factors of open data" [unveröffentlicht].

In: Anonymisierung für eine sichere Datennutzung (AnoSiDat)

Lübeck

  • 16.-17.04.2024 (2024)
Lecture
  • Sebastian Wilhelm

Anonymizing Data for Open Data Repositories. Expert training (VIII).

In: Workshop on Open Science and Open Science Infrastructure Development (ERASMUS+-Projekt "Towards Open Science Communitites development in Sub-Saharan Africa Region" [OSCAR 2.0])

Technische Hochschule Deggendorf Deggendorf

  • 05.11.2024 (2024)