Topic: Metrology for sensor networks
Sensor networks occur in industrial 4.0 environments as well as in autonomous systems that make decisions based on measurement data. The research work in this topic area focuses on linking the research work of the individual disciplines in order to address metrological questions for such sensor networks.
EPM 22DIT02 "Fundamental principles of sensor network metrology" (FunSNM)
Sensor networks are used in a large number of fields but are struggling with data quality of varying degrees, with unknown measurement uncertainty and lack of traceability to the SI limiting their applicability. To overcome these issues, this project will address the metrological aspects of sensor networks, covering the uncertainty propagation, data quality metrics and SI-traceability in generic sensor networks, as well as the assessment, infrastructure, and risk analysis of distributed sensor networks alongside software frameworks and semantics via automated application of developed methods. The applicability of the methods, tools, and concepts will be demonstrated in typical real-world sensor networks.
Project duration: 09/2023 - 08/2026
Contact: 
Anupam Vedurmudi
BMBF FAMOUS "AAS-based modeling for the analysis of changing cyber-physical systems"
For traditional industrial measurement and calibration methods, the metrological quality infrastructure is based on accredited calibration equipment and standardized evaluation methods in order to assign measured values a quantitative statement about their reliability. In the course of the digital transformation, the underlying methods must be fundamentally revised in order to be able to automatically determine the quality of measurement data in changing systems in the context of industry 4.0, since the quality and reliability of sensors can vary greatly due to different measurement capabilities and environmental influences.
In the project, individual sensors are linked to a digital twin that is able to communicate information about the measurement uncertainty. Sub-networks of sensors are combined in flexible mathematical models in order to enable machine-oriented data evaluation. With the help of organic computing methods, flexible and partially autonomous sub-networks are formed. Furthermore, a methodology is being developed to identify unsafe measuring points from aggregated measured values or characteristic values.
Contact person at PTB: Maximilian Gruber
Website of the project: 
https://famous-project.eu
EMPIR-Project "Metrology for the Factory of the Future"
The "Factory of the Future" (Industry 4.0) focuses on networking and an autonomous flow of information and data in order to automate or intelligently support decisions. The aim is to increase efficiency and competitiveness. Transparency, comparability and sustainable quality assurance require reliable measurement data, data processing and confidence in the results obtained. The project "Metrology for the Factory of the Future" aims at establishing a metrological framework for the complete life cycle of measurement data in industrial IoT: from the calibration of digital sensors to the determination of measurement uncertainty in communication to methods of machine learning for data aggregation. With the implementation in realistic test fields, the practical applicability of the methods is demonstrated and templates are created for further areas of application.The project 17IND12 Met4FoF will work closely together with 17IND02 SmartCom. Both projects had their joint kick-off on June 18-19, 2018 in Braunschweig. Further information can be found on the project website.
Documents
short description of the project (Publishable Summary)- description of the cooperation with SmartCom