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Occupational health is an important topic, especially in industry, where workers are exposed to airborne by-products (e.g., dust particles and gases). Therefore, continuous monitoring of the air quality in industrial environments is crucial to meet safety standards. For practical and economic reasons, high-quality, costly measurements are currently only carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only.
The project “Robot-assisted Environmental Monitoring for Air Quality Assessment in Industrial Scenarios” (RASEM) addresses this issue by bringing together the benefits of both – low- and high-cost – measuring technologies enabling cost-efficient long-term air quality monitoring in realtime: A stationary network of low-cost sensors that is augmented by mobile units carrying high-quality sensors. By mapping the distribution of gases and particles in industrial environments with the proposed RASEM system, measures can be identified to improve on-site working conditions much faster than using traditional methods.
In this presentation, we detail the technical aspects of RASEM and introduce the mobile platforms used.
Setting up sensors for the purpose of environmental monitoring should be a matter of days, but often drags over weeks or even months, preventing scientists from doing real research. Additionally, the newly developed hardware and software solutions are often reinventing existing wheels. In this short paper, we revisit the design of our environmental sensing node that has been monitoring industrial areas over a span of two years. We share our findings and lessons learned. Based on this, we outline how a new generation of sensing node(s) can look like.
Digital twin for hydrogen refueling stations: An analytical study for safe and efficient operations
(2023)
This analytical overview is the initial study in developing the digital sensors twin for the hydrogen refueling station. The research includes a comprehensive analysis of the current literature, refueling protocol, standards, mathematical model, simulation model, and trends in digital twins and H2 technologies. Furthermore, this study has explored the various HRS attributes, such as leakage, temperature, pressure, and hydrogen flow, and identified different use cases of the hydrogen fuel station to build a digital sensor twin. Various real gas equations, such as the Van der Waals and Able-Noble equation of state (EOS), are applied to analyze the key factors and parameters affecting hydrogen and the MATLAB simulation model to validate the key elements and parameters. This study also focuses on identifying and addressing research gaps in hydrogen technology, contributing to advancing hydrogen infrastructure, and supporting the global transition to cleaner energy solutions.