DigitalTC GrafenauBeitrag (Sammelband oder Tagungsband)
Sebastian Wilhelm
Exploiting Home Infrastructure Data for the good: Emergency Detection by reusing existing Data Sources
[Accepted for publication]
Advances in Intelligent Systems and Computing
2021
Abstract anzeigen
Monitoring people within their residence can enable elderly to live a self-determined life in their own home environment for a longer period of time. Therefore commonly activity profiles of the residents are created using various sensors in the house. Deviations from the typical activity profile may indicate an emergency situation. An alternative approach for monitoring people within their residence we investigates within our research is reusing existing data sources instead of installing additional sensors. In private households there are already numerous data sources such as smart meters weather station routers or voice assistants available. Intelligent algorithms can be used to evaluate this data and conclude on personal activities. This in turn allows the creation of activity profiles of the residents without using external sensor technology.This work outlines the research gap in reusing existing data sources for Human Activity Recognition (HAR) and emergency detection which we intend to fill with our further work.
DigitalTC GrafenauBeitrag (Sammelband oder Tagungsband)
Dietmar Jakob
Acceptance and Practically of Voice Assistance Systems in the everyday life of seniors: A study design
[Accepted for publication]
Advances in Intelligent Systems and Computing
2021
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Voice assistance systems (VAs) are becoming more popular. For Digital Natives these systems are almost part of everyday life. Does this technology also have the potential to facilitate access to digital services for persons aged 55+? Using the example of Amazon's "Echo" devices our research intends to provide a survey of the extent to which VAs are known to the target group how many elderly people own these systems and whether there are any reservations. In addition test persons will be investigated which form of interaction seems easiest for the solution of the tasks and how the operation of VAs differs from the operation of mobile devices to be learned and applied. The evaluation will include statements on socio-demographic and ethnographic aspects. Various Amazon Echo devices are installed in 20 senior households (and additionally in their family households) in order to test user acceptance and its benefits under real-world conditions.
DigitalTC GrafenauBeitrag (Sammelband oder Tagungsband)
Sebastian Wilhelm
Activity-Monitoring in Private Households for Emergency Detection: A Survey of Common Methods and Existing Disaggregable Data Sources
[Accepted for publication]
Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies
2021
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Ambient-Assisted Living (AAL) technologies can enable the elderly people to live a self-determined life in their own home environment instead of hospitals and retirement homes for a longer period of time. Hence AAL systems are not only used for everyday support but also for the detection of potential emergency situ- ations and for triggering notification chains. For this purpose the people are usually continuously monitored within their residents by ambient or wearable sensors to detect deviations in their daily behavior.This work surveys common used technologies for Human Activity Recognition (HAR) / Human Presence De- tection (HPD) which is the basis for emergency detection. Furthermore by examining various home automa- tion software existing data sources from the residential infrastructure are identified that would be suitable for detecting personal activities.
DigitalTC GrafenauBeitrag (Sammelband oder Tagungsband)
Sebastian Wilhelm, Dietmar Jakob, Jakob Kasbauer, Diane Ahrens
GeLaP: German Labeled Dataset for Power Consumption
[Accepted for publication]
Proceedings of the 6th International Congress on Information and Communication Technology
2021
Abstract anzeigen
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.
DigitalTC GrafenauBuch (Monographie)
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
Abstract anzeigen
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.
DigitalNachhaltigTC GrafenauZeitschriftenartikel
S. Goisser, S. Wittmann, Michael Fernandes, H. Mempel, C. Ulrichs
Comparison of colorimeter and different portable food-scanners for non-destructive prediction of lycopene content in tomato fruit
Postharvest Biology and Technology, vol. 167, no. September
2020
DOI: 10.1016/j.postharvbio.2020.111232
Abstract anzeigen
Lycopene, the red colored carotenoid in tomatoes, has various health benefits for humans due to its capability of scavenging free radicals. Traditionally, the quantification of lycopene requires an elaborate extraction process combined with HPLC analysis within the laboratory. Recent studies focused simpler methods for determining lycopene and utilized spectroscopic measurement methods. The aim of this study was to compare non-destructive methods for the prediction of lycopene by using color values from colorimeter measurements and Vis/NIR spectra recorded with three commercially available and portable Vis/NIR spectrometers, so called food-scanners. Tomatoes of five different ripening stages (green to red) as well as tomatoes stored up to 22 days after harvest were used for modeling. After measurement of color values and collection of Vis/NIR spectra the corresponding lycopene content was analyzed spectrophotometrically. Applying exponential regression models yielded very good prediction of lycopene for color values L*, a*, a*/b* and the tomato color index of 0.94, 0.90, 0.90 and 0.91, respectively. Color value b* was not a suitable predictor for lycopene content, whereas the (a*/b*)² value had the best linear fit of 0.87. In comparison to color measurements, the cross-validated prediction models developed for all three food-scanners had coefficients of determination (r²CV) ranging from 0.92 to 0.96. Food-scanners also can be used for additional measurements of internal fruit quality, and therefore have great potential for fruit quality assessment by measuring a multitude of important fruit traits in one single scan.
DigitalAngewandte WirtschaftswissenschaftenTC GrafenauBeitrag (Sammelband oder Tagungsband)
Sebastian Wilhelm, Dietmar Jakob, Diane Ahrens
Human Presence Detection by monitoring the indoor CO2 concentration
Tagungsband zur Konferenz Mensch und Computer 2020 (06.-09.09.2020; Magdeburg)
2020
DOI: 10.1145/3404983.3409991
Abstract anzeigen
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.
DigitalAngewandte WirtschaftswissenschaftenTC GrafenauBeitrag (Sammelband oder Tagungsband)
Sebastian Wilhelm, Dietmar Jakob, Jakob Kasbauer, M. Dietmeier
Organizational, Technical, Ethical and Legal Requirements of Capturing Household Electricity Data for Use as an AAL System
Proceedings of the Fifth International Congress on Information and Communication Technology (ICPCCI 2019) [20-21 February 2020; London, UK]
2020
DOI: 10.1007/978-981-15-5856-6_38
Abstract anzeigen
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.
DigitalAngewandte WirtschaftswissenschaftenTC GrafenauBeitrag (Sammelband oder Tagungsband)
Dietmar Jakob, Sebastian Wilhelm
Amazon Echo: A Benchmarking Model Review
Proceedings of the 14th International Conference on Interfaces and Human Computer Interaction (23-25 July 2020; Zagreb, Croatia)
2020
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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.
DigitalAngewandte WirtschaftswissenschaftenTC GrafenauBeitrag (Sammelband oder Tagungsband)
Dietmar Jakob, Sebastian Wilhelm, A. Gerl
Data Privacy Management (DPM) - A Private Household Smart Metering Use Case
Workshopband 6. Usable Security und Privacy Workshop im Rahmen der Konferenz Mensch und Computer 2020 (06.-09.09.2020; Magdeburg)
2020
DOI: 10.18420/muc2020-ws119-003
Abstract anzeigen
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.
DigitalAngewandte WirtschaftswissenschaftenTC GrafenauVortrag
Diane Ahrens
Räumliche Unabhängigkeit Dank Digitalisierung
Sommerkolloquium 2020 der Bayerischen Akademie Ländlicher Raum und Akademie für Politik und Zeitgeschehen der Hanns-Seidel-Stiftung „Corona und die große Transformation: Perspektiven für die ländlichen Räume?“, München
2020
DigitalAngewandte InformatikTC GrafenauZeitschriftenartikel
Ali Fallah Tehrani, M. Strickert, Diane Ahrens
Class of Monotone Kernelized Classifiers on the basis of the Choquet Integral
Expert Systems, vol. 37, no. First published: 21 January 2020, pp. 1-15
2020
DOI: 10.1111/exsy.12506
Abstract anzeigen
The key property of monotone classifiers is that increasing (decreasing) input values lead to increasing (decreasing) the output value. Preserving monotonicity for a classifier typically requires many constraints to be respected by modeling approaches such as artificial intelligence techniques. The type of constraints strongly depends on the modeling assumptions. Of course, for sophisticated models such conditions might be very complex. In this study we present a new family of kernels that we call it Choquet kernels. Henceforth it allows for employing popular kernel‐based methods such as support vector machines. Instead of a naïve approach with exponential computational complexity we propose an equivalent formulation with quadratic time in the number of attributes. Furthermore, since coefficients derived from kernel solutions are not necessarily monotone in the dual form, different approaches are proposed to monotonize coefficients. Finally experiments illustrate beneficial properties of the Choquet kernels.
DigitalAngewandte InformatikTC GrafenauBeitrag (Sammelband oder Tagungsband)
Monica I. Ciolacu, Leon Binder, Heribert Popp
Enabling IoT in Education 4.0 with Biosensors from Wearables and Artificial Intelligence
Proceedings of the 2019 IEEE 25th International Symposium for Design and Technology in Electronic Packaging (SIITME) [Oct 23-26, 2019; Cluj-Napoca, Romania], New York, NY, USA
2020
DOI: 10.1109/SIITME47687.2019.8990763
Abstract anzeigen
A major challenge for Education 4.0 is to make use of wearable devices for helping students in monitoring their learning behavior and their activities (steps, heart rate variability, and heart rate) in real-time. The first aim of this paper is to present our implementation of adaptivity and Artificial Intelligence (AI) methods within the Education 4.0 process. In this work, we investigate embedded biosensors (noninvasive, low-cost, and distraction-free) used in smartphones and smartwatches. The next objective is to enable IoT for Higher Education, i.e. a novel system assisted by AI that takes embedded biosensor data and environmental data into account in order to estimate students’ wellbeing and health. In this regard, we propose a framework that uses wearable devices to collect data with biofeedback methods to support students’ academic success.
DigitalNachhaltigAngewandte WirtschaftswissenschaftenTC GrafenauBeitrag (Sammelband oder Tagungsband)
S. Goisser, J. Krause, Michael Fernandes, H. Mempel
Determination of tomato quality attributes using portable NIR-sensors
Proceedings of OCM 2019: 4th International Conference on Optical Characterization of Materials (13-14 March, 2019; Karlsruhe), Karlsruhe
2019
ISBN: 978-3-7315-0864-9
DOI: 10.5445/KSP/1000087509
Abstract anzeigen
As part of a research project a multidisciplinary approach of different research institutes is followed to investigate the possibility of using a commercially available miniaturized NIR-sensor for the determination of tomato fruit quality parameters in postharvest. Correlation of spectra and tomato reference values of firmness, dry matter and total soluble solids showed good prediction accuracy. Additionally the decline of firmness over storage time with respect to storage temperature of tomatoes could be modelled. Therefore, the decline of firmness as an indicator for shelf-life can be predicted using this portable NIR-Sensor.
DigitalTC GrafenauZeitschriftenartikel
Michael Scholz, C. Brenner, O. Hinz
AKEGIS: automatic keyword generation for sponsored search advertising in online retailing
Decision Support Systems, vol. 119, no. April, pp. 96-106
2019
DOI: 10.1016/j.dss.2019.02.001
Abstract anzeigen
Sponsored search advertisers face several complex decisions when planning and implementing a new sponsored search advertising campaign. These decisions include the selection of keywords, the definition of landing pages, and the formulation of bidding strategies. Relatively low attention has been paid on supporting the selection of keywords in recent research and most studies on sponsored search advertising focus on the formulation of bidding strategies and strategies for budget planning. We present a novel approach for automatically generating sponsored search keywords that relies on the theory of consumer search behavior. Our approach uses an online store's internal search log to extract keywords used by consumers within their search process, because recent research has shown that especially consumers with a high conversion probability that exhibit goal-directed instead of exploratory search patterns use an online store's internal search engine. We empirically test our approach based on a store's internal search engine and identify the effects of this approach by comparing it to a state-of-the-art approach. Our analysis reveals that our approach substantially increased the number of profitable keywords, improved the store's conversion rate by approximately 41%, and decreased the average cost per click by more than 70%.
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