scholarly journals Evaluation and Application of a Novel Low-Cost Wearable Sensing Device in Assessing Real-Time PM2.5 Exposure in Major Asian Transportation Modes

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 270
Author(s):  
Wen-Cheng Vincent Wang ◽  
Shih-Chun Candice Lung ◽  
Chun-Hu Liu ◽  
Tzu-Yao Julia Wen ◽  
Shu-Chuan Hu ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Real Time ◽  
Mean Absolute Error ◽  
Low Cost ◽  
Absolute Error ◽  
Laboratory Evaluation ◽  
Sensing System ◽  
Transportation Modes ◽  
Pm2.5 Exposure ◽  
Device Location

Small low-cost sensing (LCS) devices enable assessment of close-to-reality PM2.5 exposures, though their data quality remains a challenge. This work evaluates the precision, accuracy, wearability and stability of a wearable particle LCS device, Location-Aware Sensing System (LASS, with Plantower PMS3003), which is 104 × 66 × 46 mm3 in size and less than 162 g in weight. Real-time particulate matter (PM) exposures in six major Asian transportation modes were assessed. Side-by-side laboratory evaluation of PM2.5 between a GRIMM aerosol spectrometer and sensors yielded a correlation of 0.98 and a mean absolute error of 0.85 µg/m3. LASS readings collected in the summer of 2016 in Taiwan were converted to GRIMM-comparable values. Mean PM2.5 concentrations obtained from GRIMM and converted LASS values of the six different transportation microenvironments were 16.9 ± 11.7 (n = 1774) and 17.0 ± 9.5 (n = 3399) µg/m3, respectively, showing a correlation of 0.93. The average one-hour PM2.5 exposure increments (concentration increase above ambient levels) from converted LASS values for Mass Rapid Transit (MRT), bus, car, scooter, bike and walk were 15.6, 6.7, −19.2, 8.1, 6.1 and 7.1 µg/m3, respectively, very close to those obtained from GRIMM. This work is one of the earliest studies applying wearable particulate matter (PM) LCS devices in exposure assessment in different transportation modes.

scholarly journals A study on the development of a light scattering particulate matter sensor and monitoring system

2020 ◽  
Vol 17 (3) ◽  
pp. 867-890
Author(s):  
Jun-Hee Choi ◽  
Hyun-Sug Cho
Keyword(s):  
Big Data ◽  
Particulate Matter ◽  
Light Scattering ◽  
Real Time ◽  
Monitoring System ◽  
Low Cost ◽  
Gravimetric Method ◽  
Correction Method ◽  
Measurement Methods ◽  
Linear Correction

The gravimetric method, which is mainly used among particulate matter (PM) measurement methods, includes the disadvantages that it cannot measure PM in real time and it requires expensive equipment. To overcome these disadvantages, we have developed a light scattering type PM sensor that can be manufactured at low cost and can measure PM in real time. We have built a big data system that can systematically store and analyze the data collected through the developed sensor, as well as an environment where PM states can be monitored mobile in real time using such data. In addition, additional studies were conducted to analyze and correct the collected big data to overcome the problem of low accuracy, which is a disadvantage of the light scattering type PM sensor. We used a linear correction method and proceeded to adopt the most suitable value based on error and accuracy.

scholarly journals Arduino based platform for process control learning

2020 ◽  
Vol 6 (5) ◽  
pp. 0585-0593
Author(s):  
Bruna Couto Molinar Henrique ◽  
Leonardo Couto Molinar Henrique ◽  
Humberto Molinar Henrique
Keyword(s):  
Open Source ◽  
Real Time ◽  
Low Cost ◽  
Control Unit ◽  
Absolute Error ◽  
Internal Model Control ◽  
Pid Controllers ◽  
Experimental Unit ◽  
Source Codes ◽  
Model Control

This work deals with implementation of an experimental flowrate control unit using free and low-cost hardware and software. The open-source software Processing was used to develop the source codes and user graphical interface and the open-source electronic prototyping platform Arduino was used to acquire data from an experimental unit. Work presents descriptions of the experimental setup, the real-time PID controllers used and theoretical/conceptual issues of Arduino. PID controllers based on internal model control, minimization of the integral of time-weighted absolute error, Ziegler-Nichols, and others were tuned for setpoint and load changes and real-time runs were carried out in order to make real-time use of  control theory learned in academy. Results showed the developed platform proved to be suitable for use in experimental setups allowing users compare their ideas and expectations with the experimental evidence in a real and low-cost fashion. In addition, the instrumentation is simple to configure with acceptable level noise and particularly useful for control/automation learning with educational purposes.

scholarly journals Laboratory evaluation of a low-cost, real-time, aerosol multi-sensor

2018 ◽  
Vol 15 (7) ◽  
pp. 559-567 ◽  
Author(s):  
Robert J. Vercellino ◽  
Darrah K. Sleeth ◽  
Rodney G. Handy ◽  
Kyeong T. Min ◽  
Scott C. Collingwood
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Laboratory Evaluation

scholarly journals Long-Term Performance Assessment of Low-Cost Atmospheric Sensors in the Arctic Environment

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1919 ◽  
Author(s):  
Federico Carotenuto ◽  
Lorenzo Brilli ◽  
Beniamino Gioli ◽  
Giovanni Gualtieri ◽  
Carolina Vagnoli ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Relative Humidity ◽  
Air Temperature ◽  
Meteorological Parameters ◽  
Low Cost ◽  
Absolute Error ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Svalbard Archipelago ◽  
Arctic Environment

The Arctic is an important natural laboratory that is extremely sensitive to climatic changes and its monitoring is, therefore, of great importance. Due to the environmental extremes it is often hard to deploy sensors and observations are limited to a few sparse observation points limiting the spatial and temporal coverage of the Arctic measurement. Given these constraints the possibility of deploying a rugged network of low-cost sensors remains an interesting and convenient option. The present work validates for the first time a low-cost sensor array (AIRQino) for monitoring basic meteorological parameters and atmospheric composition in the Arctic (air temperature, relative humidity, particulate matter, and CO2). AIRQino was deployed for one year in the Svalbard archipelago and its outputs compared with reference sensors. Results show good agreement with the reference meteorological parameters (air temperature (T) and relative humidity (RH)) with correlation coefficients above 0.8 and small absolute errors (≈1 °C for temperature and ≈6% for RH). Particulate matter (PM) low-cost sensors show a good linearity (r2 ≈ 0.8) and small absolute errors for both PM2.5 and PM10 (≈1 µg m−3 for PM2.5 and ≈3 µg m−3 for PM10), while overall accuracy is impacted both by the unknown composition of the local aerosol, and by high humidity conditions likely generating hygroscopic effects. CO2 exhibits a satisfying agreement with r2 around 0.70 and an absolute error of ≈23 mg m−3. Overall these results, coupled with an excellent data coverage and scarce need of maintenance make the AIRQino or similar devices integrations an interesting tool for future extended sensor networks also in the Arctic environment.

scholarly journals A Novel Method for Estimating Throwing Speed in Handball using a Wearable Device

2020 ◽  
Author(s):  
Sebastian D Skejø ◽  
Jesper Bencke ◽  
Merete Møller ◽  
Henrik Sørensen
Keyword(s):  
Cross Validation ◽  
Prediction Models ◽  
Mean Absolute Error ◽  
Low Cost ◽  
Absolute Error ◽  
Shoulder Injuries ◽  
Specific Load ◽  
Cheap Method ◽  
Novel Method ◽  
3D Motion Capture

Understanding the shoulder-specific load in handball is important for both prevention and rehabilitation of shoulder injuries. The shoulder-specific load is largely a result of the number and speed of throws. However, it is difficult to quantify number and speed of throws in handball due to limitations in the current technology. Therefore, the purpose of this study was to develop a novel method to estimate throwing speed in handball using a low-cost accelerometer-based device. Nineteen experienced handball players each performed 25 throws of varying types while we measured the acceleration of the wrist using the accelerometer and the throwing speed using 3D motion capture. Using cross-validation, we developed four prediction models using combinations of the logarithm of the peak total acceleration, sex and throwing type as the predictor and the throwing speed as the outcome. We found that all models were well-calibrated (mean calibration of all models: 0.0 m/s, calibration slope range: 0.99-1.00) and precise (R2 = 0.71-0.85, mean absolute error = 1.32-1.82 m/s). We conclude that the developed method appear to provide practitioners and researchers with a feasible and cheap method to estimate throwing speeds in handball.

scholarly journals Laboratory evaluation of particle size-selectivity of optical low-cost particulate matter sensors

2019 ◽  
Author(s):  
Joel Kuula ◽  
Timo Mäkelä ◽  
Minna Aurela ◽  
Kimmo Teinilä ◽  
Samu Varjonen ◽  
...  
Keyword(s):  
Particle Size ◽  
Particulate Matter ◽  
Low Cost ◽  
Laboratory Evaluation ◽  
Source Analysis ◽  
Ambient Conditions ◽  
Size Selectivity ◽  
Monodisperse Particles ◽  
Aerosol Generation ◽  
On Line

Abstract. Low-cost particulate matter sensors (PM) have been under investigation due to their prospective nature regarding spatial extension of measurement coverage. While majority of the existing literature highlights that low-cost sensors can be useful in achieving this goal, it is often reminded that the risk of sensor misuse is still high, and that the data obtained from the sensors is only representative of the specific site and its ambient conditions. This implies that there are underlying reasons yet to be characterized which are causing inaccuracies in sensor measurements. The objective of this study was to investigate the particle size-selectivity of low-cost sensors. Evaluated sensors were Plantower PMS5003, Nova SDS011, Sensirion SPS30, Sharp GP2Y1010AU0F, Shinyei PPD42NS, and Omron B5W-ld0101. The investigation of size-selectivity was carried out in laboratory using a novel reference aerosol generation system capable of steadily producing monodisperse particles of different sizes on-line. The results of the study showed that none of the low-cost sensors adhered exactly to the detection ranges declared by the manufacturers, and moreover, cursory comparison to a mid-cost aerosol spectrometer (GRIMM 1.108) indicated that the sensors could only achieve independent responses for 1–2 size bins whereas the spectrometer could sufficiently characterize particles with 15 different size bins. These observations provide insight and evidence to the notion that particle size-selectivity may have an essential role in the error source analysis of sensors.

Laboratory Evaluation of Low-Cost, Lightweight PM2.5 Exposure Monitors

2014 ◽  
Vol 2014 (1) ◽  
pp. 2298 ◽  
Author(s):  
Elena Austin* ◽  
Igor Novosselov ◽  
Edmund Seto ◽  
Michael Yost
Keyword(s):  
Low Cost ◽  
Laboratory Evaluation ◽  
Pm2.5 Exposure

scholarly journals Estimating Throwing Speed in Handball Using a Wearable Device

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4925
Author(s):  
Sebastian D. Skejø ◽  
Jesper Bencke ◽  
Merete Møller ◽  
Henrik Sørensen
Keyword(s):  
Cross Validation ◽  
Prediction Models ◽  
Mean Absolute Error ◽  
Low Cost ◽  
Absolute Error ◽  
Specific Load ◽  
Cheap Method ◽  
Novel Method ◽  
3D Motion Capture ◽  
Acceleration Signals

Throwing speed is likely a key determinant of shoulder-specific load. However, it is difficult to estimate the speed of throws in handball in field-based settings with many players due to limitations in current technology. Therefore, the purpose of this study was to develop a novel method to estimate throwing speed in handball using a low-cost accelerometer-based device. Nineteen experienced handball players each performed 25 throws of varying types while we measured the acceleration of the wrist using the accelerometer and the throwing speed using 3D motion capture. Using cross-validation, we developed four prediction models using combinations of the logarithm of the peak total acceleration, sex and throwing type as the predictor and the throwing speed as the outcome. We found that all models were well-calibrated (mean calibration of all models: 0.0 m/s, calibration slope of all models: 1.00) and precise (R2 = 0.71–0.86, mean absolute error = 1.30–1.82 m/s). We conclude that the developed method provides practitioners and researchers with a feasible and cheap method to estimate throwing speed in handball from segments of wrist acceleration signals containing only a single throw.

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