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Digital inspection twin (DIT) acting as a mirror between the physical and virtual measuring world. In this paper the measurement system with the CMMs ZEISS UMM 500 and DEA-IOTA-2203 was used as a physical twin, and a virtual machine, generated after modelling and configuring in PTC Creo software. Virtual measurement system is developed for inspection of the standard types of tolerances (concentricity, perpendicularity i.e.) and basic inspection features (IF) (plane, cylinder, truncated cone i.e.). The result of this paper is a new approach of the conceptual development of the digital inspection twin, based on CMMs - towards off-line DIT based on CMM by virtue of the control data list (CDL) and .ncl (DMIS) file.

The paper presents an application for virtual didactic laboratory dedicated for instrumentation classes using blockchain technology for saving students measurements data in order to ensure their uniqueness. The application is developed in Labview and it does both, the lab simulation and the data saving using blockchain technology in a local private wallet. The laboratory part is dedicated to a multimeter verification using an adjustable voltage source. The adjustable voltage source is based on a Feussner compensator and on a Weston standard. The blockchain part is connecting to the teacher private wallet and saves the data as a blockchain transaction every time when the student press the button. The application is delivered to the student as an executable program, so he does not know where and how the data is sent. Further, the lab part of the present application can be modified to use remote controlled instruments, except the comparator that can be replaced with a modern adjustable voltage source. The paper presents at the beginning the used blockchain technology, how the transaction are performed, how the traceability can be verified, how the data is organized within a transaction. Further, the lab part of the application is described. Each simulated instrument respects the construction error limits provided in their datasheets, while each individual run of the instrument will generate a uniquely random value within this interval. In the end some demo acquired data and discussions are provided.

Form error is the departure of a manufactured part from its design or ideal shape, and is a key characteristic to be assessed in quality engineering in manufacturing. In practice, form errors are usually estimated from coordinate measurements involving only a finite number of measured points and the form error for the complete workpiece surface has to be inferred on the basis of these measurements. This paper is about determining whether a product meets its specifications based on its form error using a probabilistic model. Based on form error data and a product specification, the relationship between conformance testing and making decisions is established. In this paper, we define a form error model using a uniform distribution with unknown bounds, and then utilize a Bayesian approach to assign a distribution to the form error parameter and use this distribution in a conformity and risk assessment methodology to quantify the risk of incorrect decisions. The risk assessment is carried out using derived expressions of specific risks associated with product conformity. A slightly more extensive posterior model, taking into consideration the probable random effects of form errors, is discussed for the reader's interest. Numerical experiments illustrate the effectiveness of this approach by providing a decision framework to control the risks associated with making a wrong decision.

Continuous gait measurement can bring relevant indicators for healthcare professionals. Several techniques were developed for this cause. However, the beneficiaries, especially senior adults, find it hard to accept a monitoring device as it takes away their privacy. In this paper, we present a non-intrusive, low-cost and easy to implement model for gait measurement at home. It consists of implementing 4 passive infrared (PIR) sensors facing each other by pair. Our approach is based on a Deep Learning (DL) model that takes as input the signals generated by the PIR sensors, as they are representative of the distance and the speed of the moving object. A temporary Depth camera is used for training the model on the gait parameters. To evaluate our approach, we conducted multiple series of experiments on real sensor data. The results are promising and show that our approach is efficient for continuous gait measurement.

Manual therapy and evaluations are performed by therapists. The rehabilitation efficiency must be improved to reduce the physical and time load of the therapists by using automated therapy and quantitative evaluation. So, we suggested the upper limb rehabilitation system using a small movable robot, and we are developing the system. In this research, we measure motor characteristics of healthy people and patients using the system, to realize the quantitative evaluation of a patient's paralysis. In this paper, a description of the detailed upper limb rehabilitation system and evaluation degree of recovery by measuring motor characteristics using the system. As the result, it was found that the degree of recovery of patients can be quantitatively evaluated using the upper limb rehabilitation support system.

This paper describes Food-MetNet, a coordinated preparatory initiative to establish the European Metrology Network on Food Safety (EMN-FS). Food-MetNet aims to establish a long-term ongoing dialogue between the metrology community and relevant stakeholders, in particular, European Union Reference Laboratories (EURLs), National Reference Laboratories (NRLs) and the Joint Research Centre (JRC). This dialogue is meant to support the collection of needs from stakeholders, the take-up of metrological research output and the development of the roadmaps needed to navigate future research.

We have been developing a measurement system for microstructures using a small-diameter optical fiber probe. The contact detection method using a threshold value may cause a large error due to the time lag between the real contact time and the time detected by the measurement system. In this paper, we investigated a method for detecting the starting point of contact using an AR model and LSTM, a type of deep learning when the stylus tip contacts the measured surface. The results of measurement experiments using an inclined surface showed that the detection accuracy using AR model decreased as the inclination angle increased, but the LSTM was able to detect the contact point with high accuracy even when the inclination angle increased. It was also confirmed that the method using LSTM can detect contact with high accuracy without being affected by drift over time and various noises (other than random noise).

In future manufacturing and metrology, there is increasing demand to organize relevant metadata and knowledge to present information in semantically meaningful, reusable, easily accessible, and interoperable form. Up-to-date information on measurement uncertainty is key to interpretation of measurement results and to assessment of the quality of the measurement process. Although various technologies from knowledge engineering have been proposed to fulfil this requirement, previous work has not fully addressed the uncertainty during the measurement process. This paper presents the method to develop an ontology of the measurement process and the uncertainty of results on the example of coordinate measurements. The resulting ontology model based on a set of competency questions, including key concepts and relationships between them, is presented and discussed. The consistency of the ontology model is verified by inferencing rules and answering competency questions in Protege software. The presented ontology will find wide applications in metrology and Industry 4.0.

The second quantum revolution is underway and the deployment of Quantum Technologies (QT) keeps pace with it. This technological paradigm-switch creates opportunities and challenges for industry, innovation and society. Several large companies, as well as start-ups, have started to develop and engineer quantum devices or begun to integrate them into their products: the commercial success of QT, together with progress in research and development, relies on certification and reliability built upon internationally agreed standards and metrological traceability. A group of European National Metrology Institutes (NMIs) and Delegated Institutes (DIs) have recently created a European Metrology Network for Quantum Technologies (EMN-Q) under the auspices of EURAMET. The objective of the EMN-Q is to co-ordinate the activities of the European NMIs and Dis to ensure their efficient support for European competitiveness in quantum technologies. A special focus of the EMN-Q will be to develop new measurement capabilities and dedicated services to serve the rapidly-growing needs of industry and research institutions in this field. Industry, governmental agencies, academic sectors or any other type of stakeholder are welcome to contact the EMN-Q and discuss their metrology needs. These can relate not only to quantum characteristics of quantum devices, but also to metrology of key enabling technologies, metrology that can improve the supply chain of industrial quantum devices or other industrial needs connected with quantum technologies. EMN-Q aims to become is to become the central contact point to stakeholders interested in metrology for quantum technologies by: • contributing to standardisation & certification of quantum technologies; • promoting the take-up of metrology in the development of these technologies; • supporting industrial needs in synergy with the technological objectives of the EC Quantum Flagship and national quantum technology programs; and • promoting the use of quantum measurement techniques where advantageous for “classical” technical areas. We are in process of structuring and developing the communication services of the EMN-Q. One of the key aspect in this EMN-Q development is the establishment the EMN-Q Strategic Research Agenda (SRA). The SRA will contain the technological roadmaps that are created by the EMN-Q members in consultation with the EMN-Q Stakeholder Community. In this paper, we will provide a short overview of the EMN-Q organization, and of the SRA and the relative Technological Roadmaps.

Precise Point Positioning (PPP) based Global Positioning System (GPS) frequency and time transfer methods have proved to achieve good accuracy over past years. Several factors can make significant influence in the realization of an accurate time transfer, where multipath error is one of the most important. The multipath can be caused by various man-made and natural structures. Also, the longer the propagation distance, the more serious is the effect. This error can be studied with respect to the satellite elevation angles to the ground station. In this paper, the GPS-PPP processed time transfer results are analysed for a varying range of elevation angles. Acceptable accuracy is obtained for an elevation angle of 20° for which 7–8 GPS satellites are visible on average. With the advancement in other Global Navigation System Satellites (GNSS), the number of visible satellites increases, which gives flexibility to filter satellites based on the signal strength quality as well.

The present paper describes the activity carried out at Istituto Nazionale di Ricerca Metrologica (INRIM) within the EMPIR Joint Research Project 16ENV06 “Metrology for Stable Isotope Reference Standards - SIRS”, for the realisation of a dilution device for generating dynamic mixtures of CO2 at ambient mole fractions. The aim of the activity was to realise a system able to generate mixtures with isotopic composition and target uncertainties as the static gravimetric reference materials realised in the SIRS project. These dynamic reference materials can be used to validate the static reference materials and for stability and fractionation studies. The dilution system was realised and a preliminary validation was carried out, focusing on the performances of the mixing chamber, which represents the core of the system. The system was tested in terms of amount fraction, by using a Non-Dispersive Infrared analyser.

This paper presents the updates implemented by the Vibration Laboratory of INMETRO on the electrical calibration of charge conditioning amplifiers. We can now carry out both standard classical calibrations with fixed in-series capacitors and including an adjustable parallel capacitance to match the total capacitance of a given pair of accelerometer plus cable. The calibration system and some analysis of measurement results are presented.

Calibration certificate is an important reference point for metrological measurement traceability. In connection with the approval of the latest revision of SI and the dissemination of a new reference base based on quantum standards, the issue of digitalization of calibration certificates becomes especially urgent. The possibilities of electronic and even more digital calibration certificates (hereinafter DCC) significantly improve the traceability of measurements in comparison with the traditional paper certificate. The form and content of DCC, however, are still not clearly determined and require deep study. Our work is aimed at presenting and summarizing the available results in this field, and formulating the critical questions on the creation of DCC that arise during the work on its implementation. Based on the analysis performed and our own experience in the implementation of the electronic calibration certificate (ECC) we presented a preliminary scheme for the implementation of DCC in our organization. We also touch upon related issues, namely digital signature and e-infrastructure of National Scientific Centre “Institute of Metrology” (NSC IM).

The design of distributed real-time systems including In- ternet of Things (IoT) systems is complex due to open-ended architectures requirements. An emergent solution to deal with this complexity and to manage system constraints is the integration of adaptation strategies in distributed devices behavior. The developement of such systems denotes a signifi-cant challenge on providing autonomous and intelligent ability to verify distributed devices behaviors and constraints such as battery storage of sensors. Existing AI-based approaches for dynamic IoT systems proposed solutions relative to the target system for resolving specific problems without consid-ering interoperability and reusability. Using MDE approach and UML/MARTE profile for high-level abstraction becomes a promising solution to ease the design of intelligent IoT systems. This paper recalls and classifies the existing AI and MDE-based works for the design of dynamic distributed systems especialy IoT applications. We concentrate on a set of criteria to highlight the shortages of existing approaches on the design of distributed devices interaction, adaptation and system constraints. Finally, we introduce our future directions to cope with the limits of existing solutions while taking into account the observed criteria.

An optical setup for measurement of the pitch deviation of a diffraction grating has been designed and developed. Multiple autocollimation units are employed in the setup so that the angles of diffraction of diffracted beams can be detected simultaneously. This enables the optical sensor head to evaluate the scale pitch deviation while separating the contributions from the scale local slope and the scale angular error motion that cannot be achieved by the conventional laser diffraction methods. In this paper, firstly, the resolution needed for the angle sensor is estimated using a theoretical analysis. After that, the design of an optical head for the angle sensor is carried out. A built prototype optical head is also used to conduct some feasibility tests, and the measurement of the pitch deviation of a scale grating brought from a commercial optical linear encoder is demonstrated.

This paper introduced the working principle of multi-user electric energy meters and analyzed the mechanism of the error in the electric energy measurement introduced by interaction among users in the meter. The key technology of the multi-user electric energy meter verification was defined and the detection method was studied. A detector for the verification of multi-user electric energy meters was invented which could give large current output to applied to each user simultaneously. The detector provided a reliable detection scheme and a technical guarantee for the development of multi-user electric energy meter technology.

The information that humans get when they look at an object is qualitative, not quantitative. There are several measurement methods to recognize objects quantitatively. However, few of them can be performed in the natural field of view, and the scale of the measurement object is limited by the performance of the sensor. Therefore, in this study, we developed a system to measure large structures in the natural field of view. In this paper, we report the configuration of the system and the experimental results.

In this paper, we described a metrological AFM in order to calibrate step height standards used as transfer artefacts for commercial AFMs. With X, Y and Z axes laser displacement interferometers installed, related calibrated results are directly traceable to the SI of metre definition. The step height measurement accuracy was verified using several step heights up to 2000 nm. Corresponding measurement uncertainty in step height standard calibration was estimated in line with the Guide to the Expression of Uncertainty in Measurement (GUM). The expanded measurement uncertainty (k = 2) was better than 2.5 nm over a full range of up to 2000 nm. This suggests that the developed metrology system is capable of conducting nano-scale metrological standard calibration which is applicable to disseminating accuracy and traceability to commercial AFMs and optical microscopes in application of surface topography measurement.

Chromatic aberrations are mostly supressed in typical industrial lenses to ensure a well-defined colour image. Beside the main wavelengths which are recognizable for the human eye, multispectral cameras can sample with a more detailed chromatic (spectral) resolution. This leads to a partial wavelength depended unsharpness in the images. If the imaging system can be well defined out of these imperfections, a depth information can be calculated. In this paper the theoretical model as well as a method for the 3D-reconstruction out of different colour (spectral) channels will be discussed.

The measurement data quality of CO2 sensors plays a critical role in the implementation of the demand control ventilation (DCV) using a network of CO2 sensors. In this paper, the airflow field and spatial distribution of CO2 in an indoor space such as a seminar room was investigated utilizing computational fluid dynamics (CFD) analysis. The locations in the seminar room for proper placement of the CO2 sensors are identified, for assuring the measurement data quality and effective DCV to achieve high energy efficiency.

Nowadays, non-intrusive load monitoring (NILM) systems represent an effective alternative to monitoring individual appliances' consumption, avoiding the costs and spatial constraints imposed by the installation of additional sensors. Modern artificial intelligence algorithms, such as machine learning algorithms, make it possible to split the aggregate power absorption profile of a user into the individual power absorption profiles of the main household appliances. However, there is still no full awareness of how these systems can be used effectively and in what situations they can provide consistent support. This paper illustrates the most promising management, diagnostics, and automation activities that can be carried out with the help of an efficient NILM system, referring to the most significant works in literature. A discussion of challenges and future research directions is also provided.

METROFOOD-RI ( www.metrofood.eu ) is an ESFRI research infrastructure, funded upon the EU H2020 METROFOOD-PP project for its Preparatory Phase, aiming to establish a new distributed European Research Infrastructure (RI) to promote scientific excellence and increase efficiency in food quality and food safety. It strives to provide and coordinate high-level metrological services on a European scale for researchers, laboratories, food inspection agencies and policymakers. As part of the preparatory phase towards the legal statute of ERIC (European Research Infrastructure Consortium), a service portfolio is being set up along with its provision diagram. As a test for this model of service provision, three use cases have been defined that are representative of the different types of access that will be provided by METROFOOD-RI: 1. physical access to a food pilot plant for demonstrating technical solutions and adaptations of food processing technology to minimize acrylamide in bakery products at the National Research & Development Institute for Food Bio-resources (IBA, Romania). 2. remote access to the transmission electron microscope facility for physicochemical characterization of nanoparticles in food (Sciensano, Belgium). 3. virtual access to two e-services for open data use, mainly addressed to researchers, laboratories, food inspection agencies and policy makers: • a search engine and database for agrifood reference materials and official methods • an application programming interface (API) for a risk evaluation tool The use cases will help to evaluate the usability of the single access point of the research infrastructure and to fine-tune the access procedures and interfaces with users. This will support the elaboration of the final service chart of METROFOOD-RI including all the potential physical, electronical and integrated services that the infrastructure aims to provide to its users. The paper will give an overview and first evaluation of the use case service provision and provide an overview of the potential METROFOOD-RI service portfolio.

This paper presents a tracking system to find the position and yaw rotation of a handheld device based on the imaging of an adhesive marker attached to a person's body. Our goal is to provide accurate data that can be combined with data from a giant magnetoresistance sensor to be able to locate a foreign body inside a human body for surgical removal. We tested the system with a series of computer simulations and analyzed the results obtained. Our best setup provided a Root Mean Square Error of less than 1.6 mm for the x coordinate, less than 1 mm for the y coordinate, less than 1.2 cm for the z coordinate and less than 1.1° for the yaw rotation value in a test with wide variations of all values. The results obtained are promising and open the way for the combination of data with the portable magnetic sensor.

The convolutional neural network is a subfield of artificial neural networks and has made great achievements in various domains over the past decade. The technique has been widely applied including computer vision, natural language processing, image analysis, etc. The field of measurement also achieves exciting progress with convolutional neural networks. This paper gives a survey of convolutional neural networks from software algorithms to hardware architectures perspective and the applications in measurement. The survey hopes to give contributions to the cross-research of artificial intelligent and measurement.

Short-term exposures to indoor air contaminants can cause adverse health impacts and warrant a need for real-time measurements. The most common indoor pollutants are carbon dioxide (CO2), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), total volatile organic compounds (TVOCs), and particulate matter with a diameter of less than 2.5 μm (PM2.5). Several low-cost monitors for indoor air quality are commercially available; however, few of them are accurately tested. A stable, easy to use, and reproducible platform was developed in this paper. In these laboratory conditions, the comparison between the low-cost sensors and calculated concentration was shown to be linear (R2 of 0.980, 0.972, 0.990, 0.958, 0.987, and 0.816 and rs of 0.982, 0.985, 0.900, 0.924, 0.982, and 0.571 for PM2.5, CO2, CO, NO2, TVOC (ethylene), and O3 respectively). Laboratory conditions were used to test possible cross-interferences to the TVOC sensor; an increase of CO2, CO, and NO2 of 2500 ppm, 100 ppb, and 100 ppb respectively generated a change in the curve fit from linear to quadratic. A complete validation of a low-cost sensor was achieved by its application in a real indoor place. Good correlation between the reference methods and uHoo measurements of PM2.5, CO2, and O3 was achieved (rs = 0.765 to 0.894, 0.721 to 0.863, and 0.523 to 0.622 respectively).

A square cored PCF (SC-PCF) sensor is proposed in this paper for the purpose of detecting detrimental chemical analytes (DEHP, BPA, and BPS) that are generally found in different plastic products. This SC-PCF sensor is capable of operating in the 1–2 THz regimes. Within this operable range, we found a relatively higher sensitivity of 96.5% along with 95.73% core power fraction, 0.225 numerical aperture, and a lower Aeff of 1.48 × 105 μm2 at 1.9 THz frequency. A tiny confinement loss of 2.68 × 10−13 cm−1 and effective material loss of 0.008 cm−1 are also evaluated. Besides the present fabrication techniques ensures the feasibility of fabrication for this proposed SC-PCF sensor. These estimated results evinced that our proposed sensor can efficiently be used in terms of the noxious chemical compounds, gas, and bio-sensing applications.

Parkinson's disease (PD) is the most common neurodegenerative disease affecting significantly motor functions of elderly persons. The diagnosis and monitoring of PD is costly and inconvenient process even today, in under developing parts of the world. The observable symptoms of PD at early stage include disorders in handwriting and repetitive tasks of spiral drawing. With advancement of IT it is easier to collect spiral drawing samples using digitized tablet. We proposed detailed analysis of Static and dynamic spirals drawn by PD patients. For this, in-air and on-surface kinematic variables are taken out from data files generated for 25 patients and 15 healthy controls, using mathematical models. Results demonstrated nearly 91% classification accuracy to separate PD patients from healthy controls by applying feature engineering and four machine learning (ML) classifiers Logistic Regression, C-Support Vector Classification (SVC), K- nearest neighbor(KNN) classifier and ensemble model Random Forest Classifier(RFC). This paper confirms that digitized spiral drawings have major impact on classification of PD patients and healthy controls and hence can support future differential diagnosis of PD.

This paper provides values of the electrical elements of equivalent models for several textile-based electrodes. In ECG recording the skin-electrode-amplifier interface is modelled as an equivalent electrical circuit having one or two parallel C-R networks and series resistance. The electrical properties have been established using a switched dc current source, modulated with a sinusoidal source. For the single C-R electrode model values of resistance ranged from 10 ​kΩ to 28 ​MΩ and of capacitance from 0.03 ​nF to 15 ​μF. In the double C-R model values of resistance ranged from 1 ​kΩ to 25 ​MΩ and of capacitance from 9 ​pF to 872 ​μF. Recording of the ECG using textile-based electrodes has recently been explored in the context of wearable technology for telemedicine and remote monitoring. Knowledge of the electrical properties of such electrodes is essential for the design of amplifiers in ECG monitors to meet the IEC 60601 requirements.