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1.
SN Appl Sci ; 3(5): 590, 2021.
Article in English | MEDLINE | ID: mdl-33942027

ABSTRACT

In this paper, we propose three methods for door state classification with the goal to improve robot navigation in indoor spaces. These methods were also developed to be used in other areas and applications since they are not limited to door detection as other related works are. Our methods work offline, in low-powered computers as the Jetson Nano, in real-time with the ability to differentiate between open, closed and semi-open doors. We use the 3D object classification, PointNet, real-time semantic segmentation algorithms such as, FastFCN, FC-HarDNet, SegNet and BiSeNet, the object detection algorithm, DetectNet and 2D object classification networks, AlexNet and GoogleNet. We built a 3D and RGB door dataset with images from several indoor environments using a 3D Realsense camera D435. This dataset is freely available online. All methods are analysed taking into account their accuracy and the speed of the algorithm in a low powered computer. We conclude that it is possible to have a door classification algorithm running in real-time on a low-power device.

2.
Environ Sci Process Impacts ; 19(2): 123-133, 2017 Feb 22.
Article in English | MEDLINE | ID: mdl-28078345

ABSTRACT

Continuous measurements of the optical properties of aerosol particles have been made at Valladolid, Spain, covering the period from June 2011 to July 2012. The measurements were made at two size cuts: sub-10 µm and sub-1 µm (PM10 and PM1). The data measured were the scattering and backscattering coefficients, σs and σbs, obtained from an integrating nephelometer, and the absorption coefficient, σa, obtained from a particle soot absorption photometer. Spectrally resolved data were obtained from both instruments at 3 wavelengths (blue/green/red) at low relative humidity (RH < 40%). The statistical data for the instruments were calculated based on the hourly averages. For the PM10 fraction, the hourly mean values of σs and σa at 550 nm were 33 Mm-1 (StD = 30 Mm-1) and 4 Mm-1 (StD = 3 Mm-1), respectively. For the PM1 fraction, σs and σa mean values were 16 Mm-1 (StD = 14 Mm-1) and 4 Mm-1 (StD = 3 Mm-1), also at 550 nm. The derived parameters analyzed were the single scattering albedo, ω0, the backscatter fraction, σbs/σs, and the Ångström exponents of scattering, absorption and single scattering albedo, αs, αa and αω0. The contribution of the PM10 and the PM1 fractions for all these parameters plays a central role throughout the paper, allowing an improved classification of aerosol types. Our data are dominated by elemental carbon (EC) and elemental carbon/organic carbon mixed (EC/OC). For the PM10 data, dust dominated aerosol is also observed. Although we found that fine particles contribute more than coarse particles for decreasing the ω0 values, results suggest that it is also necessary to quantify the effect of coarse particles. Fine particles were found to produce ω0 spectra that decrease with the wavelength, αω0 > 0, while PM10 fractions were found to produce spectra that can decrease or increase with the wavelength, 0 < αω0 < 0. Both daily cycle and monthly variations are analyzed and related to local features as well as the transport of particles from elsewhere. A diurnal pattern characteristic of urban areas is observed, but it is less evident on weekends. The main long range transport influences are Atlantic advection, anthropogenic events from Central Europe and dust events.


Subject(s)
Air Pollutants/analysis , Particulate Matter/analysis , Aerosols , Air Pollutants/chemistry , Carbon/analysis , Dust/analysis , Environmental Monitoring/methods , Humidity , Nephelometry and Turbidimetry , Optical Phenomena , Particle Size , Particulate Matter/chemistry , Spain
3.
J Environ Monit ; 14(12): 3174-81, 2012 Dec.
Article in English | MEDLINE | ID: mdl-23138695

ABSTRACT

A field campaign was conducted from October 2009 to July 2010 at Covilhã, a small town located in the region of Beira Interior (Portugal) in the interior of the Iberian Peninsula. The ambient light-absorption coefficient, σ(a) (522 nm), obtained from a Particle Soot Absorption Photometer (PSAP), presented a daily mean value of 12.1 Mm⁻¹ (StD = 7.3 Mm⁻¹). The wavelength dependence of aerosol light absorption is investigated through the Ångström parameter, α(a). The α(a) values for the pair of wavelengths 470-660 nm ranged from 0.86 to 1.47 during the period of measurements. The PSAP data were used to infer the mass of light absorbing carbon (LAC) and the daily mean varied from 0.1 to 6.8 µg m⁻³. A detailed study of special events with different aerosol characteristics is carried out and, to support data interpretation, air masses trajectory analysis is performed.


Subject(s)
Aerosols/chemistry , Air Pollutants/chemistry , Carbon/chemistry , Environmental Monitoring/methods , Absorption , Aerosols/analysis , Air Pollutants/analysis , Air Pollution/statistics & numerical data , Carbon/analysis , Light , Particle Size , Portugal
4.
J Environ Manage ; 111: 267-71, 2012 Nov 30.
Article in English | MEDLINE | ID: mdl-22964016

ABSTRACT

In this work, a novel technique is used to estimate the aerosol complex index of refraction of in situ collected samples. Samples of atmospheric particulate matter were collected in El Arenosillo, southern Spain, on polycarbonate filters during summer 2004 as part of an aerosol characterization campaign. These samples were analyzed for the volumetric absorption coefficient in the 320-800 nm spectral region and an estimation of the effective imaginary refractive index was made. The values of the imaginary part of the complex refractive index ranged between 0.0009-0.0215 at 800 nm and 0.0015-0.0114 at 320 nm. Little dependence on the wavelength was observed. Several intense and long lasting desert outbreaks were registered during the campaign and the complex refractive index almost doubles its value during these dust events. Finally, we present a comparison of data obtained in situ with columnar data obtained from the AERONET network. A correlation factor of 0.64 was obtained between both data, which gives an idea of how accurately the in situ ground data represent the total column.


Subject(s)
Aerosols/analysis , Air Pollutants/analysis , Environmental Monitoring/methods , Particulate Matter/analysis , Refractometry/methods , Absorption , Particle Size , Seasons , Spain
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