scholarly journals Evaluation of Low-Cost Sensors for Weather and Carbon Dioxide Monitoring in Internet of Things Context

IoT ◽  
2020 ◽  
Vol 1 (2) ◽  
pp. 286-308
Author(s):  
Tiago Araújo ◽  
Lígia Silva ◽  
Adriano Moreira
Keyword(s):  
Carbon Dioxide ◽  
Internet Of Things ◽  
Random Error ◽  
Atmospheric Pressure ◽  
Mean Squared Error ◽  
Low Cost ◽  
Pressure Sensors ◽  
Coefficient Of Determination ◽  
High Positive Correlation ◽  
Very High

In a context of increased environmental awareness, the Internet of Things has allowed individuals or entities to build their own connected devices to share data about the environment. These data are often obtained from widely available low-cost sensors. Some companies are also selling low-cost sensing kits for in-house or outdoor use. The work described in this paper evaluated, in the short term, the performance of a set of low-cost sensors for temperature, relative humidity, atmospheric pressure and carbon dioxide, commonly used in these platforms. The research challenge addressed with this work was assessing how trustable the raw data obtained from these sensors are. The experiments made use of 18 climatic sensors from six different models, and they were evaluated in a controlled climatic chamber that reproduced controlled situations for temperature and humidity. Four CO2 sensors from two different models were analysed through exposure to different gas concentrations in an indoor environment. Our results revealed temperature sensors with a very high positive coefficient of determination (r2 ≥ 0.99), as well as the presence of bias and almost zero random error; the humidity sensors demonstrated a very high positive correlation (r2 ≥ 0.98), significant bias and small-yet-relevant random error; the atmospheric pressure sensors presented good reproducibility, but further studies are required to evaluate their accuracy and precision. For carbon dioxide, the non-dispersive infra-red sensors demonstrated very satisfactory results (r2 ≥ 0.97, with a minimum root mean squared error (RMSE) value of 26 ppm); the metal oxide sensors, despite their moderate results (minimum RMSE equal to 40 ppm and r2 of 0.8–0.96), presented hysteresis, environmental dependence and even positioning interference. The results suggest that most of the evaluated low-cost sensors can provide a good sense of reality at a very good cost–benefit ratio in certain situations.

Application of Artificial Neural Network Over Nickel-Based Catalyst for Combined Steam-Carbon Dioxide of Methane Reforming (CSDRM)

2020 ◽  
Vol 20 (9) ◽  
pp. 5716-5719 ◽  
Author(s):  
Cho Hwe Kim ◽  
Young Chul Kim
Keyword(s):  
Neural Network ◽  
Carbon Dioxide ◽  
Artificial Neural Network ◽  
Mean Squared Error ◽  
Coefficient Of Determination ◽  
Feed Ratio ◽  
Squared Error ◽  
Highly Nonlinear ◽  
Feed Forward Network ◽  
Artificial Neural

The application of artificial neural network (ANN) for modeling, combined steam-carbon dioxide reforming of methane over nickel-based catalysts, was investigated. The artificial neural network model consisted of a 3-layer feed forward network, with hyperbolic tangent function. The number of hidden neurons is optimized by minimization of mean square error and maximization of R2 (R square, coefficient of determination) and set of 8 neurons. With feed ratio, flow rate, and temperature as independent variables, methane, carbon dioxide conversion, and H2/CO ratio, were measured using artificial neural network. Coefficient of determination (R2) values of 0.9997, 0.9962, and 0.9985 obtained, and MAE (Mean Absolute Error), MSE (Mean Squared Error), RMSE (Root Mean Squared Error), and MAPE (Mean Absolute Percentage Error) showed low value. This study indicates ANN can successfully model a highly nonlinear process and function.

scholarly journals Deep Learning-Based Optimal Smart Shoes Sensor Selection for Energy Expenditure and Heart Rate Estimation

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7058
Author(s):  
Heesang Eom ◽  
Jongryun Roh ◽  
Yuli Sun Hariyani ◽  
Suwhan Baek ◽  
Sukho Lee ◽  
...  
Keyword(s):  
Heart Rate ◽  
Deep Learning ◽  
Energy Expenditure ◽  
Mean Squared Error ◽  
Pressure Sensors ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Proposed Model ◽  
Point Pressure

Wearable technologies are known to improve our quality of life. Among the various wearable devices, shoes are non-intrusive, lightweight, and can be used for outdoor activities. In this study, we estimated the energy consumption and heart rate in an environment (i.e., running on a treadmill) using smart shoes equipped with triaxial acceleration, triaxial gyroscope, and four-point pressure sensors. The proposed model uses the latest deep learning architecture which does not require any separate preprocessing. Moreover, it is possible to select the optimal sensor using a channel-wise attention mechanism to weigh the sensors depending on their contributions to the estimation of energy expenditure (EE) and heart rate (HR). The performance of the proposed model was evaluated using the root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). Moreover, the RMSE was 1.05 ± 0.15, MAE 0.83 ± 0.12 and R2 0.922 ± 0.005 in EE estimation. On the other hand, and RMSE was 7.87 ± 1.12, MAE 6.21 ± 0.86, and R2 0.897 ± 0.017 in HR estimation. In both estimations, the most effective sensor was the z axis of the accelerometer and gyroscope sensors. Through these results, it is demonstrated that the proposed model could contribute to the improvement of the performance of both EE and HR estimations by effectively selecting the optimal sensors during the active movements of participants.

Modelling of CO2 Loading in DEA by Using Peak Ratio of Raman Spectroscopy

2014 ◽  
Vol 625 ◽  
pp. 188-191
Author(s):  
Muhammad Zubair Shahid ◽  
Abdulhalim Shah Maulud ◽  
Mohammad Azmi Bustam
Keyword(s):  
Carbon Dioxide ◽  
Raman Spectroscopy ◽  
Processing Time ◽  
Mean Squared Error ◽  
Raman Peak ◽  
Coefficient Of Determination ◽  
Absorption Process ◽  
Peak Ratio ◽  
Squared Error ◽  
Wide Range

Carbon dioxide (CO2) capturing has been an important issue for decades. Alkanoamines, such as diethanolamine (DEA) have been widely used for CO2separation by absorption process. During this process, CO2loading measurement is an imperative action for a proper process control. Currently used methods are titration based which requires a long processing time. In this work Raman spectroscopy is used to model and predict the CO2loading in wide range (0-0.97 CO2mole/amine mole). The models are developed by using Raman peak ratios to minimize the error due to peaks fluctuations. The Raman peak ratio of 1022 cm-1/1461cm-1has been found as a good fit with the coefficient of determination (R2) of 0.92 and mean squared error (MSE) of 0.00656 CO2mole2/ amine mole2in prediction of CO2loading.

scholarly journals Quadcopter altitude estimation using low-cost barometric, infrared, ultrasonic and LIDAR sensors

2021 ◽  
Vol 49 (1) ◽  
pp. 21-28
Author(s):  
Dušan Ranđelović ◽  
Goran Vorotović ◽  
Aleksandar Bengin ◽  
Pavle Petrović
Keyword(s):  
Atmospheric Pressure ◽  
Mean Squared Error ◽  
Low Cost ◽  
Flight Altitude ◽  
Data Filtering ◽  
Squared Error ◽  
The Mean ◽  
Low Altitude ◽  
Accuracy Data ◽  
Altitude Estimation

The goal of this research is to assess the different low-cost sensors for flight altitude measuring of a multirotor UAV at low altitude flight. For optimizing the sensor performances and accuracy, data filtering and other methods were applied. The flight altitude data were collected and stored for later analysis with reference to the true altitude. The correlation coefficient and the mean squared error were calculated in order to assess the sensors' performance. On the basis of the results of the study, it was possible to determine the choice of the adequate sensor for this specific use. The study showed that the best characteristics for this experiment conditions had the Garmin LIDAR-Lite V3HP sensor and the Bosch Sensortech BME280 that combined air humidity, atmospheric pressure, and air temperature sensor.

scholarly journals A Highly Sensitive and Wide-Range Resonant Magnetic Micro-Sensor Based on A Buckled Micro-Beam

2020 ◽  
Author(s):  
Nouha ALCHEIKH ◽  
Sofiane Mbarek ◽  
Mohammad Younis
Keyword(s):  
Resonance Frequency ◽  
Atmospheric Pressure ◽  
State Of The Art ◽  
Low Cost ◽  
Low Power Consumption ◽  
Highly Sensitive ◽  
Wide Range ◽  
Micro Sensor ◽  
Magnetic Applications ◽  
Very High

Abstract We experimentally demonstrate a miniature highly sensitive wide-range resonant magnetic Lorentz-force micro-sensor. The concept is demonstrated based on the detection of the resonance frequency of an in-plane electrothermally heated straight resonator operated near the buckling point. The frequency shift is measured with optical sensing and the device is operating at atmospheric pressure. The magnetometer demonstrates a sensitivity (S) of 33.9/T, which is very high compared to the state of the art. In addition, the micro-sensor shows a good linearity in wide range and low power consumption around 0.2 mW. The above performances make the proposed micro-sensor promising for various low-cost magnetic applications.

scholarly journals Construction of an experimental apparatus to simulate the greenhouse effect and global warming for educational use

2020 ◽  
Vol 8 (8) ◽  
pp. 427-431
Author(s):  
Paulo Renda Anderson ◽  
Carlos Mergulhão Júnior ◽  
Moacy José Stoffes Junior ◽  
Cléver Reis Stein
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Global Warming ◽  
Greenhouse Effect ◽  
Low Cost ◽  
Pressure Sensors ◽  
Experimental Apparatus ◽  
Atmosphere Temperature ◽  
Temperature And Pressure ◽  
Carbon Dioxide Co2

This article describes the construction of a complete experimental apparatus to simulate the greenhouse and global warming for educatioal use. These demonstrations are fundamental for people understand the importance of greenhouse effect to keep that life continues on earth and, know about climate change and the causes of global warming. For development of this devise we used an Arduino UNO, temperature and pressure sensors, and low cost products. The experimental results showed that the average atmosphere temperature increases with the increasing concentration of carbon dioxide (CO2). Moreover, this apparatus can be used in classroom to demonstration these important global phenomena.

Decomposition of the metastable beta titanium alloy Ti-15-3

1983 ◽  
Vol 41 ◽  
pp. 264-265
Author(s):  
Y. L. Chen ◽  
S. Fujlshiro
Keyword(s):  
Low Cost ◽  
High Strength ◽  
Alpha Phase ◽  
Thick Sheet ◽  
Omega Phase ◽  
Beta Titanium Alloy ◽  
Beta Titanium ◽  
Beta Matrix ◽  
Metastable Beta ◽  
Very High

Metastable beta titanium alloys have been known to have numerous advantages such as cold formability, high strength, good fracture resistance, deep hardenability, and cost effectiveness. Very high strength is obtainable by precipitation of the hexagonal alpha phase in a bcc beta matrix in these alloys. Precipitation hardening in the metastable beta alloys may also result from the formation of transition phases such as omega phase. Ti-15-3 (Ti-15V- 3Cr-3Al-3Sn) has been developed recently by TIMET and USAF for low cost sheet metal applications. The purpose of the present study was to examine the aging characteristics in this alloy.The composition of the as-received material is: 14.7 V, 3.14 Cr, 3.05 Al, 2.26 Sn, and 0.145 Fe. The beta transus temperature as determined by optical metallographic method was about 770°C. Specimen coupons were prepared from a mill-annealed 1.2 mm thick sheet, and solution treated at 827°C for 2 hr in argon, then water quenched. Aging was also done in argon at temperatures ranging from 316 to 616°C for various times.

Bringing Security to The Smallest Embedded Systems

2017 ◽  
Author(s):  
JOSEPH YIU
Keyword(s):  
Internet Of Things ◽  
Embedded Systems ◽  
Low Cost ◽  
Security Requirements ◽  
The Internet ◽  
Security Measures ◽  
Significant Challenge ◽  
Iot Devices

The increasing need for security in microcontrollers Security has long been a significant challenge in microcontroller applications(MCUs). Traditionally, many microcontroller systems did not have strong security measures against remote attacks as most of them are not connected to the Internet, and many microcontrollers are deemed to be cheap and simple. With the growth of IoT (Internet of Things), security in low cost microcontrollers moved toward the spotlight and the security requirements of these IoT devices are now just as critical as high-end systems due to:

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