Measurement uncertainty is a complex technical and social phenomenon and is of great importance for the usefulness of any measurement, instrument, or node in the measurement network. Therefore, various methods of assessing and reducing uncertainty are used, referring to one or more sources of uncertainty, such as internal uncertainties of a measuring device, uncertainties characteristic of methods of measuring uncertainty caused by external conditions, and personal errors.
Measurement uncertainty is of particular importance in the Internet of Things networks due to the variety of devices and measurement methods. For this reason, uncertainty analysis becomes an important aspect of the assessment of the usefulness of these networks for measurements, the process of data enrichment, their initial processing and use for diagnosing and forecasting phenomena.
Therefore, when preparing this Special Issue proposal, the potential shareholders of this project are anticipated to be both those who conduct the measurements and those who process data from these measurements. Hence, it is proposed that this edition should contain the results of the work of teams dealing with the measurement of internal and external air pollutants and teams conducting research in CA17136 - Indoor Air Pollution Network, as well as those who will use this data working in CA16215 - European network for the promotion of portable, affordable and simple analytical platforms. Then this Special Issue will contain interesting results of uncertainty studies covering both the measurements themselves and their analysis and implementation processes.
This Special Issue expands the knowledge in the following areas of sensors:
Remote sensors
Sensor networks
Smart / Intelligent sensors
Sensor devices
Sensor technology and application
Sensing principles
Internet of Things
Signal processing, data fusion, and deep learning in sensor systems
