RESUMO
In this paper, the design and research of a sensor-based personal air-quality monitoring device are presented, which is retrofitted into different personal protective face masks. Due to its small size and low power consumption, the device can be integrated into and applied in practical urban usage. We present our research and the development of the sensor node based on a BME680-type environmental sensor cluster with a wireless IoT (Internet of Things)-capable central unit and overall low power consumption. The integration of the sensor node was investigated with traditional medical masks and a professional FFP2-type mask. The filtering efficiency after embedding was validated with a head model and a particle counter. We found that the professional mask withstood the embedding without losing the protective filtering aspect. We compared the inner and outer sensor data and investigated the temperature, pressure, humidity, and AQI (Air Quality Index) relations with possible sensor data-fusion options. The novelty is increased with the dual-sensor layout (inward and outward). It was found that efficient respiration monitoring is achievable with the device. With the analysis of the recorded data, characteristic signals were identified in an urban environment, enabling urban altimetry and urban zone detection. The results promote smart city concepts and help in endeavors related to SDGs (Sustainable Development Goals) 3 and 11.
RESUMO
In this paper, we investigated the applicability of ChatGPT AI in electronics research and development via a case study of applied sensors in embedded electronic systems, a topic that is rarely mentioned in the recent literature, thus providing new insight for professionals and academics. The initial electronics-development tasks of a smart home project were prompted to the ChatGPT system to find out its capabilities and limitations. We wanted to obtain detailed information on the central processing controller units and the actual sensors usable for the specific project, their specifications and recommendations on the hardware and software design flow additionally. Furthermore, an extensive literature survey was requested to see if the bot could offer scientific papers covering the given topic. It was found that the ChatGPT responded with proper recommendations on controllers. However, the suggested sensor units, the hardware and software design were only partially acceptable, with occasional errors in specifications and generated code. The results of the literature survey showed that non-acceptable, fabricated citations (fake authors list, title, journal details and DOI-Digital Object identifier) were presented by the bot. The paper provides a detailed qualitative analysis, a performance analysis and critical discussion of the aforementioned aspects while providing the query set, the generated answers and codes as supplied data with the goal to give added value to electronics researchers and developers if trying to reach out for the tools in their profession.
RESUMO
The COVID-19 outbreak increased demand for personal protective respirator masks. Textile masks based on cloth materials appeared to be a sustainable, comfortable, and cost-effective alternative available in global communities. In this study, we used laser-based particle counting for mask material qualification to determine the concentration filtering efficiency in general, everyday community use. The efficiencies of eleven different commercially available textile materials were measured in single-, double-, and triple-layer configurations according to their grammage, mesh (XY), and inter-yarn gap. It was found that in the single-layer configurations, most materials were well below the acceptable standards, with a wide variation in filtering efficiency, which ranged from 5% to ~50%. However, when testing the fabrics in two or three layers, the efficiency increased significantly, exceeding or approaching the standard for medical masks. Three layers of natural silk was able to produce a level of filtration efficiency of 84.68%. Two-layered natural silk achieved 70.98%, cotton twill achieved 75.6%, and satin-weave viscose achieved 69.77%. Further options can also be considered in cases where lower filtration is acceptable It was statistically shown that applying a second layer was more significant in terms of overall filtering than increasing the layer count to three. However, layer stacking limited the breathability. The paper presents measurement-based qualitative and quantitative recommendations for future textile applications in face mask manufacturing.
RESUMO
Flux contained in solder paste significantly affects the process of solder joint creation during reflow soldering, including the creation of an intermetallic layer (IML). This work investigates the dependence of intermetallic layer thickness on ROL0/ROL1 flux classification, glossy or matt solder mask, and OSP/HASL/ENIG soldering pad surface finish. Two original SAC305 solder pastes differing only in the used flux were chosen for the experiment. The influence of multiple reflows was also observed. The intermetallic layer thicknesses were obtained by the image analysis of micro-section images. The flux type proved to have a significant impact on the intermetallic layer thickness. The solder paste with ROL1 caused an increase in IML thickness by up to 40% in comparison to an identical paste with ROL0 flux. Furthermore, doubling the roughness of the solder mask has increased the resulting IML thickness by 37% at HASL surface finish and by an average of 22%.
