Use of Multiple Low Cost Carbon Dioxide Sensors to Measure Exhaled Breath Distribution with Face Mask Type and Wearing Behaviour

Multi-Sensors for Human Activity Recognition

Human activity recognition (HAR) has made significant progress in recent years, with growing applications in various domains, and the emergence of wearable and ambient sensors has provided new opportunities in the field [...].

Quantitatively Visualizing Airborne Disease Transmission Risks of Different Exhalation Activities through CO2 Imaging

Aerosol transmission has played a leading role in COVID-19 pandemic. However, there is still a poor understanding about how it is transmitted. This work was designed to study the exhaled breath flow dynamics and transmission risks under different exhaling modes. Using an infrared photography device, exhaled flow characteristics of different breathing activities, such as deep breathing, dry coughing, and laughing, together with the roles of mouth and nose were characterized by imaging CO2 flow morphologies. Both mouth and nose played an important role in the disease transmission though in the downward direction for the nose. In contrast to the trajectory commonly modeled, the exhaled airflows appeared with turbulent entrainments and obvious irregular movements, particularly the exhalations involving mouth were directed horizontal and had a higher propagation capacity and transmission risk. While the cumulative risk was high for deep breathing, those transient ones from dry coughing, yawning, and laughing were also shown to be significant. Various protective measures including masks, canteen table shields, and wearable devices were visually demonstrated to be effective for altering the exhaled flow directions. This work is useful to understanding the risk of aerosol infection and guiding the formulation of its prevention and control strategies. Experimental data also provide important information for refining model boundary conditions.

Electrochemical Biosensor Based on Laser-Induced Graphene for COVID-19 Diagnosing: Rapid and Low-Cost Detection of SARS-CoV-2 Biomarker Antibodies

The severe acute respiratory syndrome originated by the new coronavirus (SARS-CoV-2) that emerged in late 2019, known to be a highly transmissible and pathogenic disease, has caused the COVID-19 global pandemic outbreak. Thus, diagnostic devices that help epidemiological public safety measures to reduce undetected cases and isolation of infected patients, in addition to significantly help to control the population’s immune response to vaccine, are required. To address the negative issues of clinical research, we developed a Diagnostic on a Chip platform based on a disposable electrochemical biosensor containing laser-induced graphene and a protein (SARS-CoV-2 specific antigen) for the detection of SARS-CoV-2 antibodies. The biosensors were produced via direct laser writing using a CO2 infrared laser cutting machine on commercial polyimide sheets. The presence of specific antibodies reacting with the protein and the K3[Fe(CN)6] redox indicator produced characteristic and concentration-dependent electrochemical signals, with mean current values of 9.6757 and 8.1812 µA for reactive and non-reactive samples, respectively, proving the effectiveness of testing in clinical samples of serum from patients. Thus, the platform is being expanded to be measured in a portable microcontrolled potentiostat to be applied as a fast and reliable monitoring and mapping tool, aiming to assess the vaccinal immune response of the population.

A Robust Miniaturized Gas Sensor for H2 and CO2 Detection Based on the 3ω Method

Gas concentration monitoring is essential in industrial or life science areas in order to address safety-relevant or process-related questions. Many of the sensors used in this context are based on the principle of thermal conductivity. The 3ω-method is a very accurate method to determine the thermal properties of materials. It has its origin in the thermal characterization of thin solid films. To date, there have been very few scientific investigations using this method to determine the thermal properties of gases and to apply it to gas measurement technology. In this article, we use two exemplary gases (H2 and CO2) for a systematical investigation of this method in the context of gas analysis. To perform our experiments, we use a robust, reliable sensing element that is already well established in vacuum measurement technology. This helix-shaped thin wire of tungsten exhibits high robustness against chemical and mechanical influences. Our setup features a compact measurement environment, where sensor operation and data acquisition are integrated into a single device. The experimental results show a good agreement with a simplified analytical model and FEM simulations. The sensor exhibits a lower detection limit of 0.62% in the case of CO2, and only 0.062% in case the of H2 at an excitation frequency of 1Hz. This is one of the lowest values reported in literature for thermal conductivity H2 sensors.

Smart Tree: An Architectural, Greening and ICT Multidisciplinary Approach to Smart Campus Environments

At present, climate change, pollution, and uncontrolled urbanism threaten not only natural ecosystems, but also the urban environment. Approaches to mitigate these challenges and able to provide an alternative for the use of the space are deemed to be multidisciplinary, combining architecture, vegetation integration, circular economy and information and communications technologies (ICT). University campuses are a key scenario to evaluate such solutions as their student and research community is intrinsically willing to support these experiences and provide a wide knowledge on the fields necessary for their design and implementation. However, the creation of areas combining usability and sustainability is commonly lacking a multidisciplinary approach combining all these different perspectives. Hence, the present work aims to overcome this limitation by the development of a novel integrated approach for campus spaces for co-working and leisure, namely a “Smart Tree”, where novel architecture, furniture design, flora integration, environmental sensoring and communications join together. To this end, a survey of the literature is provided, covering related approaches as well as general principles behind them. From this, the general requirements and constraints for the development of the Smart Tree area are identified, establishing the main interactions between the architecture, greening and ICT perspectives. Such requirements guide the proposed system design and implementation, whose impact on the environment is analyzed. Finally, the research challenges and lessons learned for their development are identified in order to support future works.