IMEKO Event Proceedings Search

   

Page 23 of 977 Results 221 - 230 of 9762

Paramita Guha, Arun Ram Prasath R T, Manish Kumar Tamrakar, Shrikrishan, Priyanka Jain
Development of Frontend Interface for Digital Calibration Certificate for AC High Current Source Parameters

CSIR-National Physical Laboratory, India an apex level body which provides calibration services to various secondary, tertiary calibration and testing labs and industries across the country. In general, calibration reports are commonly created in paper or word format to produce PDFs, which are time-consuming, tedious, and susceptible to human errors. Due to this several issues, BIPM- France is taking suitable goals to overcome this issue through the development of DCC. As globally leading NMIs like PTB, Germany, etc were working towards DCC developments, CSIR-NPL (NMI of India) takes part in DCC working group which are in-line with the leading NMIs. The main aim of this work is to create and implement a web application based on react.js to create digital calibration certificates. By deploying this solution, there will be substantial gains in data traceability, security, reliability, and accessibility. The project encompasses the creation of a Digital Calibration Certificate (DCC) platform that substitutes the conventional manual procedures with an automated, scalable system with the ability to produce structured and verifiable digital certificates. To further verify the authenticity and ease of validation, a model based on QR codes has been implemented that produces a unique, scannable code corresponding to a cloud-hosted copy of the certificate, permitting secure and instantaneous access. Also, advanced cryptographic algorithms like cryptographic hashing and PDF encryption are applied to secure the digital certificates and to ensure that the certificates remain tamper-proof and intact over their lifecycle. This end-to-end digital solution not only updates the laboratory's calibration report process but also establishes a new standard for secure, transparent, and effective calibration services.

Ahdrian Camilo C. Gernale, Nathaniel Ken A. Aquino, Roj Gian D. Gorospe, Mark Joseph C. Nicasio
National Metrology Laboratory of the Philippines Digital Calibration Certificate: DigiCert

This paper presents the design and implementation of a system application named DigiCert, a Digital Calibration Certificate (DCC) application developed by the National Metrology Laboratory of the Philippines (NMLPhil) of the Industrial Technology Development Institute to modernize calibration workflows and enhance certificate management through standardized, machine-readable documentation. DigiCert improves the process of changing old formats like scanned images and PDF files into organized XML using the Physikalisch-Technische Bundesanstalt (PTB) DCC XML schema. It also allows for manual data entry with a real-time XML preview and can convert back and forth between XML and an easy-to-read PDF. The system employs advanced techniques to enhance images, detect text arranged in a grid pattern, and recognize characters in order to extract both tabular and free-form data from those images. For PDF, it uses Python libraries like pdfplumber and regex parsing to ensure high accuracy. A user-friendly graphical user interface guides the operator through import, edit, and export functions across five dedicated windows, enforcing DCC schema compliance and reducing administrative overhead. DigiCert’s flexible design and compliance with ISO/IEC 17025:2018 standards guarantee that the application can work well with other systems, keep track of changes, and maintain security through cryptographic signatures, making it a suitable choice for modern digital measurement and certified calibration labs.

Jens Niederhausen
Towards an inclusive and agile implementation roadmap for a digital quality infrastructure

How do we best transition from an outdated QI with many manual processes and analogue quality documents to an efficient and interconnected QI that fully leverages digital and automatized processes and granular quality data? This paper aims to identify digital transition strategies that can account for the realistic boundary conditions that exist in today’s diverse QI landscape, particularly the different digital maturity levels across institutions and nations as well as elaborate regulatory frameworks. Informed by related initiatives, the paper presents promising approaches to map out transition roadmaps for individual starting conditions and transition velocities.

Anna-Maria Elert, Lena Meyer, Nanine Brunner, Michael Melzer, Claudia Koch
Advancing Digital Quality Infrastructure: Transforming Laboratory Processes for Enhanced Efficiency and Reliability

The digital Quality Infrastructure (QI) holds significant potential for ensuring and enhancing the accuracy, reliability, and efficiency of laboratory processes. Establishing digital QI tools and processes and the integration into the larger digital QI ecosystem however comes with many technical and organizational challenges at the laboratory but also larger system level. This paper presents solutions of a digital QI tool set that are being developed within the German initiative QI-Digital, our own experiences in the implementation of Digital Calibration Certificates (DCCs) as eAttestation in our laboratory, as well as the structured process we have been establishing to engage with the laboratory community to support adoption of the digital QI.

Peter Blattner, Oscar De Feo, Fabiano Assi
Swiss Quality Infrastructure in Transition

In response to the accelerating digitalization of society, the Swiss Quality Infrastructure (QI) is undergoing a strategic transformation. To support this, METAS organized a two-part workshop series in 2024 and 2025. The first workshop mapped the complex stakeholder landscape and explored key QI concepts like competence and trust, highlighting both formal and informal relationships. The second workshop moved from analysis to action, identifying pain points and generating digital solution ideas, including AI, and machine-readable standards. Participants identified possible initiatives such as a QI Data Space, Digital Calibration Certificate, and quality-IoT systems, while also addressing internal readiness challenges. Key outcomes included the need for shared infrastructure, international alignment, and seed funding to support implementation. The workshops provided a starting point for shaping a resilient, digitally enabled QI system tailored to Switzerland’s strengths and future needs.

Ihtisham Ul Haq, Luigi D’Alfonso, Giuseppe Fedele, Francesco Lamonaca
A Modular Windows-Based Intelligent API for Traceable Drone Positioning Using UWB-OptiTrack Fusion and AI-Based Residual Learning

Accurate and traceable drone positioning is crucial for autonomous aerial navigation, especially in GNSS-denied environments. Traditional approaches using Ultra-Wideband (UWB) sensors or Kalman Filters (KF) struggle with multipath interference, non-line-of-sight, and environmental uncertainties, and are often limited to Linux-based Application Programming Interfaces (APIs). This work presents an innovative framework based on: a novel modular Windows-based API for real-time drone positioning, the integration of Kalman filter for optimal multi-sensor data fusion and trajectory smoothing, AI-driven residual learning to correct systematic estimation errors, and metrology-compliant uncertainty modeling. The system enables real-time swarm deployment and pose-aware feedback using an auxiliary vision based positioning system (OptiTrack) and UWB data. A feedforward neural network compensates for residual errors in Kalman-filtered trajectories, while Monte Carlo simulations establish traceable 95% confidence intervals. Experimental tests show that the proposed framework reduces RMSE by over 40% across axes, with strong regression accuracy greater than 94%.

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.

Page 23 of 977 Results 221 - 230 of 9762