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Mads Johansen, Anupam Prasad Vedurmudi, Martha Arbayani Zaidan, Milos Davidovic, Gertjan Kok, Maitane Iturrate-Garcia, Shahin Tabandeh
Data Quality Characteristics for Improved Metrology in Sensor Networks

Sensor networks are becoming increasingly practical to deploy in largely varying settings, which combined with the growing availability of low-cost sensors and the increasing scale of sensor networks, makes it highly challenging to ensure the trustworthiness and reliability of measurements and data. Factors such as physical inaccessibility and cost constraints make it infeasible to use established methods for calibration, further increasing the difficulty of assessing measurement uncertainty and ensuring traceability in sensor networks. In addition, the large volume of data generated makes the assessment of data quality in sensor networks infeasible without automated, efficient, and reliable methods. This paper explores how well-known data quality characteristics can be applied in a metrologically sound manner, enabling quality assessments even when reference data or traditional calibration data are unavailable.

Nikita D Zviagin
The Regional Metrology Organisations Coordination Working Group of the CIPM FORUM on Metrology and Digitalization. Helping Emerging NMIs on Their Path to Digital Transformation

On the first Meeting of the CIPM Forum on Metrology and Digitalization (FORUM MD) in March 2024 several task and working groups were established. Amongst them is the Working Group on RMO Coordination (FORUM MD WG RMO) which includes the chairpersons of working or task groups responsible for the digitalization projects inside 6 RMOs (AFRIMETS, APMP, COOMET, EURAMET, GULFMET and SIM). One of the main tasks of the group is to provide a link through RMOs between the Forum and every NMI (and their stakeholders), including NMIs that are not participating in the work of the Forum and are not yet the Signatories of the CIPM MRA and/or the Metre Convention, thus providing emerging NMIs with the possibility to get recent information on the topic and observe best practices in the field that have been already implemented by developed NMIs. The paper gives information about the FORUM MD WG RMO, its structure and participants, the work already done, current activities and future plans.

Deepak Sharma, Divya Singh Yadav, Preeti Kandpal, Bharath Vattikonda, Ashish Agarwal
A Timing Accuracy Assessment System Prototype for Multiple NTP Servers

Time synchronization is a critical aspect of modern IT systems. The Network Time Protocol (NTP) plays a crucial role in maintaining consistent and accurate time across digital infrastructure worldwide. NTP is aligned with digital metrology vision, enabling precise timekeeping through the remote correction of clocks. National Metrology Institutes (NMIs) around the world, the custodians of national time standards, play a pivotal role in disseminating accurate time information through NTP services. Multiple NTP servers are generally considered for redundancy and load distribution. To maintain this ecosystem, it is crucial to ensure the timing accuracy and reliability of all the NTP servers. This work presents a system prototype for ensuring timing accuracy of multiple NTP severs. The prototype has been developed considering self-developed Python program for collecting and processing NTP data along with a Grafana based visualization dashboard for timing accuracy assessment. The system may be useful in detecting and isolating faulty NTP servers. The system may be enhanced with Machine Learning based early anomaly detection and alerting mechanisms. The work may be useful for developing application specific customized dashboards for different metrological systems.

Fahad A. AlMuhlaki, Saad A. Bin Qoud, Rayan A. AlYousefi, I. AlFaleh, N. Qahtani, Khaled AlEnizi, AbdulRahman AlMrhom, A. El-Matarawey
SASO Proficiency Test Machine - Advanced Pythonic AI Algorithms for Automating and Validating ISO 13528 & ISO 5725-2 at Saudi Standards, Metrology, and Quality Organization - SASO-KSA

In the field of laboratory proficiency testing and method validation, linking to international standards such as ISO 13528, ISO 17043 and ISO 5725-2 is essential for ensuring data accuracy, consistency, and inter-laboratory comparability. However, simple implementation these standards can be led to insufficient error-handling and difficult to scale across large datasets. This study introduces a novel Python-based AI framework automating ISO 13528 and ISO 5725-2 compliance, enhancing data integrity and decision-making confidence. We introduce a robust software framework built on modern Python libraries and machine learning techniques that streamline key statistical computations required by these standards—including outlier detection, repeatability and reproducibility assessment, and performance scoring. The system not only automates routine calculations but also introduces intelligent validation checks that flag anomalies, inconsistencies, or deviations from expected patterns, thereby enhancing data integrity and decision-making confidence. By integrating AI-enhanced analytics with standardized evaluation protocols, this work bridges the gap between traditional statistical methods and modern computational capabilities.

Sunantiya Parana, Nititorn Kenyota, Narueson Nanna, Praiya Thongluang, Narin Chanthawong, Jariya Buajarern
Digitalization of Calibration Workflow at National Institute of Metrology Thailand (NIMT)

This paper presents the strategic digital transformation of workflows at the National Institute of Metrology Thailand (NIMT). The implementation of digital technologies has significantly reduced human errors, enhanced accuracy, and increased transparency in data handling. NIMT has proactively developed and deployed digital platforms across the organization to support this transformation. A key outcome of this initiative is the Equipment Management and Tracking System (EMTs), developed in alignment with ISO/IEC 17025, which enables efficient electronic management of measurement instruments. The integration of technologies such as Optical Character Recognition (OCR) and Digital Calibration Certificates (DCC) has further improved data accuracy and reduced processing time. In support of quality assurance, NIMT is also planning to develop a digital system to enhance its audit processes and ensure continued compliance with quality standards. This digital shift not only strengthens NIMT’s operational capabilities but also aligns Thailand’s measurement infrastructure with international metrological practices.

Hiroshi Watanabe, Yoshitaka Shimizu, Katsuhiro Shirono, Toshiyuki Fujimoto
Digitalized Third-Party Validation for Calibration Service: a System Design Example

We present a new case study of digitalized third-party validation for a calibration service of purity. The third-party validation is an add on to the calibration service, conducted by a third party independent from laboratory and customers, aiming at assuring quality of results. The case features frequent validations, and information leakage-free by checking data within the laboratory rather than externally, that have not been addressed in the previous cases. We describe the design and implementation of the system.

Tatyana Sheveleva, Gisa Foyer
Measurement Data and Information of Non-Automatic Weighing Instruments as Structured Data

The successful digitization of documents in conformity assessment, e.g. for calibration and test, requires both the compliance with different requirements and the use of a unified machine-readable data structure. A well-known example is the data structure for the Digital Calibration Certificate (DCC). Its use is proposed by the German Calibration Service (DKD) in its Report DKD-E 7-3 for the digitization of calibration certificates for non-automatic weighing instruments (NAWIs). An analysis has been carried out to check whether the proposal can be applied to OIML R 76 test reports. By comparing the measurement data and information in both types of documents, similarities and differences in the content description were identified. The following publication gives an overview of this analysis and its results and provides suggestions for the description of the test reports using the DCC.

Jeremy Latsko, Michael Brockway, Salvatore Capra, Evan Elliott
Digital Transformation for the United States Air Force Metrology and Calibration Program

The United States Air Force (USAF) Metrology and Calibration program's mission is to ensure USAF readiness through the accuracy, reliability, and traceability (A-R-T) of 700k units of Measurement & Test Equipment (M&TE). While our operations are extensive—500k annual calibrations across 65 global labs—current limitations in data capture, infrastructure, and analytical capabilities prevent us from fully leveraging our data for a modern, data-driven, proactive Quality Infrastructure (QI). Consequently, this paper explains capability gaps between our current and desired end state QIs, the resultant Digital Transformation (DT) strategy, and its technical implementation. This DT strategy will revolutionize our metrology operations, fundamentally improving the quality of A-R-T, and therefore further ensuring USAF readiness.

Robson S. da Silva, Roberto A. Filho, Marcos Oliveira Junior, Eduardo Mario Dias, Maria Lídia Rebello Pinho Dias
Knowledge Management foundations in the Design of the São Paulo State Institute of Weights and Measures (IPEM-SP) Quality Infrastructure Portal: Strategies and Challenges

This paper presents the conceptual, methodological, and technological foundations for a Knowledge Management (KM) model aimed at the digital transformation of the Quality Infrastructure (QI) ecosystem. As a case study, it examines the Quality Infrastructure Services Portal (PSIQ), currently under development by the Sao Paulo State Institute of Weights and Measures (IPEM-SP), at Technology Readiness Level 2 (TRL2). Using a qualitative, exploratory, and applied approach, the study supports the transition of the portal to TRL3. Classical KM models (SECI, DIKW, APO, and Cynefin) are employed to structure knowledge flows, while enabling technologies—such as Intelligent Virtual Assistants, Semantic Search, Big Data & Analytics, and Robotic Process Automation—are mapped to sustain operationalization. The results indicate that PSIQ can function as a cognitive digital platform for regulatory knowledge, institutional memory, interoperability, and strategic learning. The paper concludes with recommendations to consolidate KM as a strategic function in the digital transformation of QI in Brazil.

Volker Zeuner, Gulian Couvreur
Metrological AI Reliability Verification

Applications based on Artificial Intelligence (AI) are becoming useful tools in Metrology. The ability of, e.g., managing big amounts of devices or analysing Big Data using AI Applications (in the sense of Software) raises speditivity and accuracy of gaining metrological results as well as facilitates metrological analyses on a new scale. When AI is involved in measurement, decision making, classification, etc., it must be assured that the results are transparent, reproducible, comparable, and traceable, corresponding to the established metrological measurement requirements. Hence, the operation of AI Applications in Metrology should be subject to prior and periodic verification, regarding a classification of the AI types and their use scenarios (e.g., in Legal Metrology), their usage, and the expected results thereof.

Page 2 of 955 Results 11 - 20 of 9546