A5020500388- Sensor Technology and Measurement Systems
- Scientific Measurement and Uncertainty Evaluation
- Energy Efficient Wireless Sensor Networks
- Animal Vocal Communication and Behavior
- Fault Detection and Control Systems
- Speech and Audio Processing
- Research Data Management Practices
- Data Quality and Management
- Marine animal studies overview
- Advanced Chemical Sensor Technologies
- Distributed Sensor Networks and Detection Algorithms
- Semantic Web and Ontologies
- Amphibian and Reptile Biology
- Advanced MEMS and NEMS Technologies
- Experimental Learning in Engineering
- Acoustic Wave Phenomena Research
- Time Series Analysis and Forecasting
- Hearing Loss and Rehabilitation
- Advanced Sensor Technologies Research
- Scientific Computing and Data Management
- Image Processing and 3D Reconstruction
- Digital Transformation in Industry
- Building Energy and Comfort Optimization
- Structural Health Monitoring Techniques
- Advanced Measurement and Metrology Techniques
Physikalisch-Technische Bundesanstalt
2021-2025
Blockheizkraftwerks- Träger- und Betreibergesellschaft (Germany)
2022
Technical University of Munich
2016-2019
Heinz Maier-Leibnitz Zentrum
2019
Bernstein Center for Computational Neuroscience Munich
2016
Sensor networks have appeared on the 'radar' of metrology only recently and a rigorous treatment metrological assessment not yet been established. However, sensor as measuring systems underpin many developments in digital transformation, with applications ranging from regulated utility to low-cost Internet Things (IoT). The necessitates fundamental revision calibration, uncertainty propagation performance new approaches for information data handling regarding individual sensors their...
In internally coupled ears, displacement of one eardrum creates pressure waves that propagate through air-filled passages in the skull and cause opposing eardrum, conversely. By modeling membrane, passages, propagating waves, we show ears generate unique amplitude temporal cues for sound localization. The magnitudes both these are directionally dependent. tympanic fundamental frequency segregates a low-frequency regime with constant time-difference magnification from high-frequency domain...
The Internet of Things (IoT) is characterized by a large number interconnected devices or assets. Measurement instruments in the IoT are typically digital sense that their indications available only as output. Moreover, growing sensors contain built-in pre-processing system, e.g., for compensating unwanted effects. This paper considers application metrological principles to such so-called “smart sensors” IoT. It addresses calibration sensors, mathematical and semantic approaches,...
Sensor networks, which are increasingly being used in a broad range of applications, constitute measurement paradigm involving ensembles sensors measuring possibly different quantities at discrete sample spatial locations and temporal points outside the laboratory. If sensor networks to be considered as true metrology systems results derived from them for decision-making, such regulatory context, it is important that accompanied by reliable statements uncertainty. This paper gives preview...
Abstract Accurate measurements in dimensional metrology necessitate strict controls on spatial and temporal variations the measurement room temperature. Due to limitations number of sensors that can be placed a given room, interpolation methods leverage information from multiple are necessary assess conditions at unsampled locations. In this contribution, Kriging is used spatially interpolate temperatures limited with different uncertainties temperature controlled housing two coordinate...
The annotation of sensor data with semantic metadata is essential to the goals automation and interoperability in context Industry 4.0. In this contribution, we outline a description quality networks terms indicators, metrics interpretations. concepts thus defined are consolidated into an ontology that describes metainformation heterogeneous methods for determination corresponding dimensions outlined. By incorporating support calibration models measurement uncertainty via previously derived...
In recent years, data science and engineering have faced many challenges concerning the increasing amount of data. order to ensure findability, accessibility, interoperability, reusability (FAIRness) digital resources, objects as a synthesis metadata with persistent unique identifiers should be used. this context, FAIR principles formulate requirements that research and, ideally, also industrial fulfill make full use them, particularly when Machine Learning or other data-driven methods are...
Animals that are small compared to sound wavelengths face the challenge of localizing a source since main cues direction—interaural time differences (ITD) and interaural level (ILD)—both depend on size. Remarkably, majority terrestrial vertebrates possess internally coupled ears (ICE) with an air-filled cavity connecting two eardrums producing inherently directional middle-ear system. Underwater, longer faster sound-speed reduce both ITD ILD cues. Nonetheless, many animals communicate...
Sensors are a key element of recent Industry 4.0 developments and currently further sophisticated functionality is embedded into them, leading to smart sensors. In typical "Factory the Future" (FoF) scenario, several sensors different data acquisition units (DAQs) will be used monitor same process, e.g. wear critical component, in this paper an electromechanical cylinder (EMC). If use machine learning (ML) applications interest, all DAQs need brought together consistent way. To enable...
Abstract The development and integration of metrological processes to address complex, large-scale systems interconnected measuring instruments, i.e., sensor networks, has been a topic increasing importance in the last decade. Initial developments network metrology include, e.g., treatment sensors with digital-only output, measurement uncertainty evaluation for time series data, digital representation information such sensors. In principle, modern technologies allow fully automated operation...
Earlier studies have reported that numerous vertebrate taxa skeletal muscle(s) attaching directly, or indirectly, onto the tympanic membrane. The present study links these prior by quantitatively modeling influence of muscle contraction on tension, dampening, and, ultimately, fundamental frequency. In this way, efficacy muscles to dynamically alter sensory response ear is quantified. Changing tension modifies eardrum's frequency, a key notion in understanding hearing through internally...
The enrichment of raw sensor data with contextual information is essential to enabling interoperability and the automation analysis in Industry 4.0 applications. In this paper an ontology describe dynamic transfer behavior calibrated sensors a metrologically consistent manner presented. By merging extending commonly used ontologies, new constructed that describes mathematical details models machine-interpretable manner. Incorporating measurement uncertainty as integral part ontology,...
Sensor networks underpin many developments in digital transformation, with applications ranging from regulated utility to low-cost Internet of Things (IoT).The metrological assessment sensor necessitates a fundamental revision calibration, uncertainty propagation and performance new approaches for information data handling regarding the individual sensors their interactions network allow systems metrology approach be established.This contribution summarizes initial findings three research...
Information leveraged from multiple sensors is generally more versatile than that a single sensor.For instance, the value of physical quantity at an unsampled location can be estimated by interpolating measurements spatially separated sensors.In this contribution, kriging used to interpolate room temperatures limited number with different measurement uncertainties and propagation sensor interpolated values using Monte Carlo simulation demonstrated.A potential application assess quality also...
In recent years, data science and engineering have faced many challenges concerning the increasing amount of data.In order to ensure findability, accessability, interoperability reusability (FAIRness) digital resources, objects as a synthesis metadata with persistent unique identifiers should be used.In this context, FAIR principles formulate requirements that research and, ideally, also industrial fulfill make full use them, particularly when Machine Learning or other data-driven methods...