TY  - JOUR
AU  - Topalović, Dušan
AU  - Davidović, Miloš D.
AU  - Jovanović, Maja
AU  - Bartonova, Alena
AU  - Ristovski, Zoran
AU  - Jovašević-Stojanović, Milena
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8372
AB  - The current compliance networks of automatic air-quality monitoring stations in large urban environments are not sufficient to provide spatial and temporal measurement resolution for realistic assessment of personal exposure to pollutants. Small low-cost sensor platforms with greater mobility and expected lower maintenance costs, are increasingly being used as a supplement to compliance monitoring stations. However, low-cost sensor platforms usually provide data with uncertain precision. To improve the precision, these sensor platforms require in-field calibration. Our paper aims to demonstrate that data from each individual sensor system can be corrected using that sensor system's own data to achieve much improved data quality compared to a reference. However, in this procedure, there are practical difficulties such as individual sensor outputs from the multi-sensor system not being sufficiently available due to malfunctions for instance. We explore how this can be dealt with. In our opinion, this is a novel approach, of practical importance both to users and manufacturers. We present a detailed comparative analysis of Linear Regression (univariate), Multivariate Linear Regression and Artificial Neural Networks used with a specific aim of calibrating field-deployed low-cost CO and O3 sensors. For Artificial Neural Network models, the performance of three common training algorithms was compared (Levenberg-Marquardt, Resilient back-propagation and Conjugate Gradient Powell-Beale algorithm). Data for this study were obtained from two campaigns conducted with 25 multi-sensor AQMESH v.3.5 platforms used within the activities of the CITI-SENSE project. The platforms were co-located to reference gas monitors at the Automatic Monitoring Station Stari Grad, in Belgrade, Serbia. This paper demonstrates that Multivariate Linear Regression and Artificial Neural Network calibration models can improve the output signal. This improvement can be measured by changes in the median and interquartile ranges of statistical parameters used for model evaluation. Artificial Neural Networks showed the best results compared to Linear Regression and Multivariate Linear Regression models. The best predictors for CO, in addition to CO low-cost sensor data, were PM2.5 and NO2, while for O3, in addition to O3 low-cost sensor data, the most suitable input predictors were NO and aH. Based on residual error analysis, we have shown that for CO and O3, a certain range of concentrations exists in which calibrated values differ by less than 10% from the reference method results. In addition, it was noted that for all models, CO sensors consistently showed lower variability between platforms compared to O3 sensors. © 2019 Elsevier Ltd
T2  - Atmospheric Environment
T1  - In search of an optimal in-field calibration method of low-cost gas sensors for ambient air pollutants: Comparison of linear, multilinear and artificial neural network approaches
VL  - 213
SP  - 640
EP  - 658
DO  - 10.1016/j.atmosenv.2019.06.028
ER  - 

@article{
author = "Topalović, Dušan and Davidović, Miloš D. and Jovanović, Maja and Bartonova, Alena and Ristovski, Zoran and Jovašević-Stojanović, Milena",
year = "2019",
abstract = "The current compliance networks of automatic air-quality monitoring stations in large urban environments are not sufficient to provide spatial and temporal measurement resolution for realistic assessment of personal exposure to pollutants. Small low-cost sensor platforms with greater mobility and expected lower maintenance costs, are increasingly being used as a supplement to compliance monitoring stations. However, low-cost sensor platforms usually provide data with uncertain precision. To improve the precision, these sensor platforms require in-field calibration. Our paper aims to demonstrate that data from each individual sensor system can be corrected using that sensor system's own data to achieve much improved data quality compared to a reference. However, in this procedure, there are practical difficulties such as individual sensor outputs from the multi-sensor system not being sufficiently available due to malfunctions for instance. We explore how this can be dealt with. In our opinion, this is a novel approach, of practical importance both to users and manufacturers. We present a detailed comparative analysis of Linear Regression (univariate), Multivariate Linear Regression and Artificial Neural Networks used with a specific aim of calibrating field-deployed low-cost CO and O3 sensors. For Artificial Neural Network models, the performance of three common training algorithms was compared (Levenberg-Marquardt, Resilient back-propagation and Conjugate Gradient Powell-Beale algorithm). Data for this study were obtained from two campaigns conducted with 25 multi-sensor AQMESH v.3.5 platforms used within the activities of the CITI-SENSE project. The platforms were co-located to reference gas monitors at the Automatic Monitoring Station Stari Grad, in Belgrade, Serbia. This paper demonstrates that Multivariate Linear Regression and Artificial Neural Network calibration models can improve the output signal. This improvement can be measured by changes in the median and interquartile ranges of statistical parameters used for model evaluation. Artificial Neural Networks showed the best results compared to Linear Regression and Multivariate Linear Regression models. The best predictors for CO, in addition to CO low-cost sensor data, were PM2.5 and NO2, while for O3, in addition to O3 low-cost sensor data, the most suitable input predictors were NO and aH. Based on residual error analysis, we have shown that for CO and O3, a certain range of concentrations exists in which calibrated values differ by less than 10% from the reference method results. In addition, it was noted that for all models, CO sensors consistently showed lower variability between platforms compared to O3 sensors. © 2019 Elsevier Ltd",
journal = "Atmospheric Environment",
title = "In search of an optimal in-field calibration method of low-cost gas sensors for ambient air pollutants: Comparison of linear, multilinear and artificial neural network approaches",
volume = "213",
pages = "640-658",
doi = "10.1016/j.atmosenv.2019.06.028"
}

Topalović, D., Davidović, M. D., Jovanović, M., Bartonova, A., Ristovski, Z.,& Jovašević-Stojanović, M.. (2019). In search of an optimal in-field calibration method of low-cost gas sensors for ambient air pollutants: Comparison of linear, multilinear and artificial neural network approaches. in Atmospheric Environment, 213, 640-658.
https://doi.org/10.1016/j.atmosenv.2019.06.028

Topalović D, Davidović MD, Jovanović M, Bartonova A, Ristovski Z, Jovašević-Stojanović M. In search of an optimal in-field calibration method of low-cost gas sensors for ambient air pollutants: Comparison of linear, multilinear and artificial neural network approaches. in Atmospheric Environment. 2019;213:640-658.
doi:10.1016/j.atmosenv.2019.06.028 .

Topalović, Dušan, Davidović, Miloš D., Jovanović, Maja, Bartonova, Alena, Ristovski, Zoran, Jovašević-Stojanović, Milena, "In search of an optimal in-field calibration method of low-cost gas sensors for ambient air pollutants: Comparison of linear, multilinear and artificial neural network approaches" in Atmospheric Environment, 213 (2019):640-658,
https://doi.org/10.1016/j.atmosenv.2019.06.028 . .

TY  - JOUR
AU  - Jovanović, Maja
AU  - Savić, Jasmina
AU  - Salimi, Farhad
AU  - Stevanović, Svetlana
AU  - Brown, Reece A.
AU  - Jovašević-Stojanović, Milena
AU  - Manojlovic, Dragan
AU  - Bartonova, Alena
AU  - Bottle, Steven
AU  - Ristovski, Zoran
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8677
AB  - To estimate the oxidative potential (OP) of particulate matter (PM), two commonly used cell-free, molecular probes were applied: dithiothreitol (DTT) and dichloro-dihydro-fluorescein diacetate (DCFH-DA), and their performance was compared with 9,10-bis (phenylethynyl) anthracene-nitroxide (BPEAnit). To the best of our knowledge, this is the first study in which the performance of the DTT and DCFH has been compared with the BPEAnit probe. The average concentrations of PM, organic carbon (OC) and elemental carbon (EC) for fine (PM2.5) and coarse (PM10) particles were determined. The results were 44.8 ± 13.7, 9.8 ± 5.1 and 9.3 ± 4.8 µg·m−3 for PM2.5 and 75.5 ± 25.1, 16.3 ± 8.7 and 11.8 ± 5.3 µg·m−3 for PM10, respectively, for PM, OC and EC. The water-soluble organic carbon (WSOC) fraction accounted for 42 ± 14% and 28 ± 9% of organic carbon in PM2.5 and PM10, respectively. The average volume normalized OP values for the three assays depended on both the sampling periods and the PM fractions. The OPBPEAnit had its peak at 2 p.m.; in the afternoon, it was three times higher compared to the morning and late afternoon values. The DCFH and BPEAnit results were correlated (r = 0.64), while there was no good agreement between the BPEAnit and the DTT (r = 0.14). The total organic content of PM does not necessarily represent oxidative capacity and it shows varying correlation with the OP. With respect to the two PM fractions studied, the OP was mostly associated with smaller particles.
T2  - International Journal of Environmental Research and Public Health
T1  - Measurements of Oxidative Potential of Particulate Matter at Belgrade Tunnel; Comparison of BPEAnit, DTT and DCFH Assays
VL  - 16
IS  - 24
SP  - 4906
DO  - 10.3390/ijerph16244906
ER  - 

@article{
author = "Jovanović, Maja and Savić, Jasmina and Salimi, Farhad and Stevanović, Svetlana and Brown, Reece A. and Jovašević-Stojanović, Milena and Manojlovic, Dragan and Bartonova, Alena and Bottle, Steven and Ristovski, Zoran",
year = "2019",
abstract = "To estimate the oxidative potential (OP) of particulate matter (PM), two commonly used cell-free, molecular probes were applied: dithiothreitol (DTT) and dichloro-dihydro-fluorescein diacetate (DCFH-DA), and their performance was compared with 9,10-bis (phenylethynyl) anthracene-nitroxide (BPEAnit). To the best of our knowledge, this is the first study in which the performance of the DTT and DCFH has been compared with the BPEAnit probe. The average concentrations of PM, organic carbon (OC) and elemental carbon (EC) for fine (PM2.5) and coarse (PM10) particles were determined. The results were 44.8 ± 13.7, 9.8 ± 5.1 and 9.3 ± 4.8 µg·m−3 for PM2.5 and 75.5 ± 25.1, 16.3 ± 8.7 and 11.8 ± 5.3 µg·m−3 for PM10, respectively, for PM, OC and EC. The water-soluble organic carbon (WSOC) fraction accounted for 42 ± 14% and 28 ± 9% of organic carbon in PM2.5 and PM10, respectively. The average volume normalized OP values for the three assays depended on both the sampling periods and the PM fractions. The OPBPEAnit had its peak at 2 p.m.; in the afternoon, it was three times higher compared to the morning and late afternoon values. The DCFH and BPEAnit results were correlated (r = 0.64), while there was no good agreement between the BPEAnit and the DTT (r = 0.14). The total organic content of PM does not necessarily represent oxidative capacity and it shows varying correlation with the OP. With respect to the two PM fractions studied, the OP was mostly associated with smaller particles.",
journal = "International Journal of Environmental Research and Public Health",
title = "Measurements of Oxidative Potential of Particulate Matter at Belgrade Tunnel; Comparison of BPEAnit, DTT and DCFH Assays",
volume = "16",
number = "24",
pages = "4906",
doi = "10.3390/ijerph16244906"
}

Jovanović, M., Savić, J., Salimi, F., Stevanović, S., Brown, R. A., Jovašević-Stojanović, M., Manojlovic, D., Bartonova, A., Bottle, S.,& Ristovski, Z.. (2019). Measurements of Oxidative Potential of Particulate Matter at Belgrade Tunnel; Comparison of BPEAnit, DTT and DCFH Assays. in International Journal of Environmental Research and Public Health, 16(24), 4906.
https://doi.org/10.3390/ijerph16244906

Jovanović M, Savić J, Salimi F, Stevanović S, Brown RA, Jovašević-Stojanović M, Manojlovic D, Bartonova A, Bottle S, Ristovski Z. Measurements of Oxidative Potential of Particulate Matter at Belgrade Tunnel; Comparison of BPEAnit, DTT and DCFH Assays. in International Journal of Environmental Research and Public Health. 2019;16(24):4906.
doi:10.3390/ijerph16244906 .

Jovanović, Maja, Savić, Jasmina, Salimi, Farhad, Stevanović, Svetlana, Brown, Reece A., Jovašević-Stojanović, Milena, Manojlovic, Dragan, Bartonova, Alena, Bottle, Steven, Ristovski, Zoran, "Measurements of Oxidative Potential of Particulate Matter at Belgrade Tunnel; Comparison of BPEAnit, DTT and DCFH Assays" in International Journal of Environmental Research and Public Health, 16, no. 24 (2019):4906,
https://doi.org/10.3390/ijerph16244906 . .

TY  - JOUR
AU  - Fishbain, Barak
AU  - Lerner, Uri
AU  - Castell, Nuria
AU  - Cole-Hunter, Tom
AU  - Popoola, Olalekan
AU  - Broday, David M.
AU  - Martinez Iniguez, Tania
AU  - Nieuwenhuijsen, Mark
AU  - Jovašević-Stojanović, Milena
AU  - Topalović, Dušan
AU  - Jones, Roderic L.
AU  - Galea, Karen S.
AU  - Etzion, Yael
AU  - Kizel, Fadi
AU  - Golumbic, Yaela N.
AU  - Baram-Tsabari, Ayelet
AU  - Yacobi, Tamar
AU  - Drahler, Dana
AU  - Robinson, Johanna A.
AU  - Kocman, David
AU  - Horvat, Milena
AU  - Svecova, Vlasta
AU  - Arpaci, Alexander
AU  - Bartonova, Alena
PY  - 2017
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/1343
AB  - Recent developments in sensory and communication technologies have made the development of portable air-quality (AQ) micro-sensing units (MSUs) feasible. These MSUs allow AQ measurements in many new applications, such as ambulatory exposure analyses and citizen science. Typically, the performance of these devices is assessed using the mean error or correlation coefficients with respect to a laboratory equipment. However, these criteria do not represent how such sensors perform outside of laboratory conditions in large-scale field applications, and do not cover all aspects of possible differences in performance between the sensor-based and standardized equipment, or changes in performance over time. This paper presents a comprehensive Sensor Evaluation Toolbox (SET) for evaluating AQ MSUs by a range of criteria, to better assess their performance in varied applications and environments. Within the SET are included four new schemes for evaluating sensors capability to: locate pollution sources; represent the pollution level on a coarse scale; capture the high temporal variability of the observed pollutant and their reliability. Each of the evaluation criteria allows for assessing sensors performance in a different way, together constituting a holistic evaluation of the suitability and usability of the sensors in a wide range of applications. Application of the SET on measurements acquired by 25MSUs deployed in eight cities across Europe showed that the suggested schemes facilitates a comprehensive cross platform analysis that can be used to determine and compare the sensors performance. The SET was implemented in R and the code is available on the first authors website. (C) 2016 Elsevier B.V. All rights reserved.
T2  - Science of the Total Environment
T1  - An evaluation tool kit of air quality micro-sensing units
VL  - 575
SP  - 639
EP  - 648
DO  - 10.1016/j.scitotenv.2016.09.061
ER  - 

@article{
author = "Fishbain, Barak and Lerner, Uri and Castell, Nuria and Cole-Hunter, Tom and Popoola, Olalekan and Broday, David M. and Martinez Iniguez, Tania and Nieuwenhuijsen, Mark and Jovašević-Stojanović, Milena and Topalović, Dušan and Jones, Roderic L. and Galea, Karen S. and Etzion, Yael and Kizel, Fadi and Golumbic, Yaela N. and Baram-Tsabari, Ayelet and Yacobi, Tamar and Drahler, Dana and Robinson, Johanna A. and Kocman, David and Horvat, Milena and Svecova, Vlasta and Arpaci, Alexander and Bartonova, Alena",
year = "2017",
abstract = "Recent developments in sensory and communication technologies have made the development of portable air-quality (AQ) micro-sensing units (MSUs) feasible. These MSUs allow AQ measurements in many new applications, such as ambulatory exposure analyses and citizen science. Typically, the performance of these devices is assessed using the mean error or correlation coefficients with respect to a laboratory equipment. However, these criteria do not represent how such sensors perform outside of laboratory conditions in large-scale field applications, and do not cover all aspects of possible differences in performance between the sensor-based and standardized equipment, or changes in performance over time. This paper presents a comprehensive Sensor Evaluation Toolbox (SET) for evaluating AQ MSUs by a range of criteria, to better assess their performance in varied applications and environments. Within the SET are included four new schemes for evaluating sensors capability to: locate pollution sources; represent the pollution level on a coarse scale; capture the high temporal variability of the observed pollutant and their reliability. Each of the evaluation criteria allows for assessing sensors performance in a different way, together constituting a holistic evaluation of the suitability and usability of the sensors in a wide range of applications. Application of the SET on measurements acquired by 25MSUs deployed in eight cities across Europe showed that the suggested schemes facilitates a comprehensive cross platform analysis that can be used to determine and compare the sensors performance. The SET was implemented in R and the code is available on the first authors website. (C) 2016 Elsevier B.V. All rights reserved.",
journal = "Science of the Total Environment",
title = "An evaluation tool kit of air quality micro-sensing units",
volume = "575",
pages = "639-648",
doi = "10.1016/j.scitotenv.2016.09.061"
}

Fishbain, B., Lerner, U., Castell, N., Cole-Hunter, T., Popoola, O., Broday, D. M., Martinez Iniguez, T., Nieuwenhuijsen, M., Jovašević-Stojanović, M., Topalović, D., Jones, R. L., Galea, K. S., Etzion, Y., Kizel, F., Golumbic, Y. N., Baram-Tsabari, A., Yacobi, T., Drahler, D., Robinson, J. A., Kocman, D., Horvat, M., Svecova, V., Arpaci, A.,& Bartonova, A.. (2017). An evaluation tool kit of air quality micro-sensing units. in Science of the Total Environment, 575, 639-648.
https://doi.org/10.1016/j.scitotenv.2016.09.061

Fishbain B, Lerner U, Castell N, Cole-Hunter T, Popoola O, Broday DM, Martinez Iniguez T, Nieuwenhuijsen M, Jovašević-Stojanović M, Topalović D, Jones RL, Galea KS, Etzion Y, Kizel F, Golumbic YN, Baram-Tsabari A, Yacobi T, Drahler D, Robinson JA, Kocman D, Horvat M, Svecova V, Arpaci A, Bartonova A. An evaluation tool kit of air quality micro-sensing units. in Science of the Total Environment. 2017;575:639-648.
doi:10.1016/j.scitotenv.2016.09.061 .

Fishbain, Barak, Lerner, Uri, Castell, Nuria, Cole-Hunter, Tom, Popoola, Olalekan, Broday, David M., Martinez Iniguez, Tania, Nieuwenhuijsen, Mark, Jovašević-Stojanović, Milena, Topalović, Dušan, Jones, Roderic L., Galea, Karen S., Etzion, Yael, Kizel, Fadi, Golumbic, Yaela N., Baram-Tsabari, Ayelet, Yacobi, Tamar, Drahler, Dana, Robinson, Johanna A., Kocman, David, Horvat, Milena, Svecova, Vlasta, Arpaci, Alexander, Bartonova, Alena, "An evaluation tool kit of air quality micro-sensing units" in Science of the Total Environment, 575 (2017):639-648,
https://doi.org/10.1016/j.scitotenv.2016.09.061 . .

TY  - JOUR
AU  - Jovašević-Stojanović, Milena
AU  - Bartonova, Alena
AU  - Topalović, Dušan
AU  - Lazović, Ivan
AU  - Pokrić, Boris
AU  - Ristovski, Zoran
PY  - 2015
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/851
AB  - Respirable particulate matter present in outdoor and indoor environments is a health hazard. The particle concentrations can quickly change, with steep gradients on short temporal and spatial scales, and their chemical composition and physical properties vary considerably. Existing networks of aerosol particle measurements consist of limited number of monitoring stations, and mostly aim at assessment of compliance with air quality legislation regulating mass of particles of varying sizes. These networks can now be supplemented using small portable devices with low-cost sensors for assessment of particle mass that may provide higher temporal and spatial resolution if we understand the capabilities and characteristics of the data they provide. This paper overviews typical currently available devices and their characteristics. In addition it is presented original results of measurement and modelling in the aim of one low-cost PM monitor validation. (C) 2015 Elsevier Ltd. All rights reserved.
PB  - Elsevier
T2  - Environmental Pollution
T1  - On the use of small and cheaper sensors and devices for indicative citizen-based monitoring of respirable particulate matter
VL  - 206
SP  - 696
EP  - 704
DO  - 10.1016/j.envpol.2015.08.035
ER  - 

@article{
author = "Jovašević-Stojanović, Milena and Bartonova, Alena and Topalović, Dušan and Lazović, Ivan and Pokrić, Boris and Ristovski, Zoran",
year = "2015",
abstract = "Respirable particulate matter present in outdoor and indoor environments is a health hazard. The particle concentrations can quickly change, with steep gradients on short temporal and spatial scales, and their chemical composition and physical properties vary considerably. Existing networks of aerosol particle measurements consist of limited number of monitoring stations, and mostly aim at assessment of compliance with air quality legislation regulating mass of particles of varying sizes. These networks can now be supplemented using small portable devices with low-cost sensors for assessment of particle mass that may provide higher temporal and spatial resolution if we understand the capabilities and characteristics of the data they provide. This paper overviews typical currently available devices and their characteristics. In addition it is presented original results of measurement and modelling in the aim of one low-cost PM monitor validation. (C) 2015 Elsevier Ltd. All rights reserved.",
publisher = "Elsevier",
journal = "Environmental Pollution",
title = "On the use of small and cheaper sensors and devices for indicative citizen-based monitoring of respirable particulate matter",
volume = "206",
pages = "696-704",
doi = "10.1016/j.envpol.2015.08.035"
}

Jovašević-Stojanović, M., Bartonova, A., Topalović, D., Lazović, I., Pokrić, B.,& Ristovski, Z.. (2015). On the use of small and cheaper sensors and devices for indicative citizen-based monitoring of respirable particulate matter. in Environmental Pollution
Elsevier., 206, 696-704.
https://doi.org/10.1016/j.envpol.2015.08.035

Jovašević-Stojanović M, Bartonova A, Topalović D, Lazović I, Pokrić B, Ristovski Z. On the use of small and cheaper sensors and devices for indicative citizen-based monitoring of respirable particulate matter. in Environmental Pollution. 2015;206:696-704.
doi:10.1016/j.envpol.2015.08.035 .

Jovašević-Stojanović, Milena, Bartonova, Alena, Topalović, Dušan, Lazović, Ivan, Pokrić, Boris, Ristovski, Zoran, "On the use of small and cheaper sensors and devices for indicative citizen-based monitoring of respirable particulate matter" in Environmental Pollution, 206 (2015):696-704,
https://doi.org/10.1016/j.envpol.2015.08.035 . .

TY  - CONF
AU  - Pokrić, Boris
AU  - Kreo, Srdan
AU  - Drajic, Dejan
AU  - Pokric, Maja
AU  - Jokic, Ivan
AU  - Jovašević-Stojanović, Milena
PY  - 2014
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/7153
AB  - This paper presents the environmental monitoring solution ekoNET, developed for a real-time monitoring of air pollution and other atmospheric condition parameters such as temperature, air pressure and humidity. The system is based on low-cost gas, PM and meteorological sensors providing cost-efficient, simple to deploy, use and maintain solution targeted for the usage within the Internet of Things domain of smart cities and smart enterprises. The paper gives an overview of the system architecture, encompassing the ekoNET device, back-end cloud infrastructure, data handling and visualization engine as well as the application-level components and modules. Furthermore, initial field trial data of twelve ekoNET devices is presented, enabling the overall system operation performance testing.
T1  - ekoNET - Environmental Monitoring using Low-cost Sensors for Detecting Gases, Particulate Matter and Meteorological Parameters
SP  - 421
EP  - 426
DO  - 10.1109/IMIS.2014.57
ER  - 

@conference{
author = "Pokrić, Boris and Kreo, Srdan and Drajic, Dejan and Pokric, Maja and Jokic, Ivan and Jovašević-Stojanović, Milena",
year = "2014",
abstract = "This paper presents the environmental monitoring solution ekoNET, developed for a real-time monitoring of air pollution and other atmospheric condition parameters such as temperature, air pressure and humidity. The system is based on low-cost gas, PM and meteorological sensors providing cost-efficient, simple to deploy, use and maintain solution targeted for the usage within the Internet of Things domain of smart cities and smart enterprises. The paper gives an overview of the system architecture, encompassing the ekoNET device, back-end cloud infrastructure, data handling and visualization engine as well as the application-level components and modules. Furthermore, initial field trial data of twelve ekoNET devices is presented, enabling the overall system operation performance testing.",
title = "ekoNET - Environmental Monitoring using Low-cost Sensors for Detecting Gases, Particulate Matter and Meteorological Parameters",
pages = "421-426",
doi = "10.1109/IMIS.2014.57"
}

Pokrić, B., Kreo, S., Drajic, D., Pokric, M., Jokic, I.,& Jovašević-Stojanović, M.. (2014). ekoNET - Environmental Monitoring using Low-cost Sensors for Detecting Gases, Particulate Matter and Meteorological Parameters. , 421-426.
https://doi.org/10.1109/IMIS.2014.57

Pokrić B, Kreo S, Drajic D, Pokric M, Jokic I, Jovašević-Stojanović M. ekoNET - Environmental Monitoring using Low-cost Sensors for Detecting Gases, Particulate Matter and Meteorological Parameters. 2014;:421-426.
doi:10.1109/IMIS.2014.57 .

Pokrić, Boris, Kreo, Srdan, Drajic, Dejan, Pokric, Maja, Jokic, Ivan, Jovašević-Stojanović, Milena, "ekoNET - Environmental Monitoring using Low-cost Sensors for Detecting Gases, Particulate Matter and Meteorological Parameters" (2014):421-426,
https://doi.org/10.1109/IMIS.2014.57 . .