Autonomous system for real time air pollution monitoring using semiconductor toxic gas sensors

Vasile, Andrei; Caldararu, M.

doi:10.1109/isse.2001.931067

Cited by 5 publications

(3 citation statements)

References 1 publication

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“…As an example, air pollution can be measured using semiconductor sensors for toxic and Fig. 3 The volume describing the coefficient H(l, m, n) in the 3-D phase space flammable gases (TGS; Caldararu et al 2001). These sensors convert the pollutant concentration into a change in the layer resistance of a SnO 2 semiconductor.…”

Section: Modeling the Sensor And Instrumentation Noise νmentioning

confidence: 99%

Filtering effect of wind flow turbulence on atmospheric pollutant dispersion

Yassin

2011

Environ Monit Assess

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This paper presents a model for coupling the statistics of wind velocity distribution and atmospheric pollutant dispersion. The effect of wind velocity distribution is modeled as a three-dimensional finite-impulse response (3D-FIR) filter. A phase space representation of the 3D-FIR filter window is discussed. The resulting pollutant dispersion is the multiplication in the phase space of the 3-D Fourier transform of the pollutant concentration and the volume described by the filter window coefficients. The shape of the filter window in the phase space enables representing such effects as vortex shedding thermal currents, etc. The impact of spatial distribution of the sensors on the resulting pollutant spatial distribution and the 3-D FIR filter model employed also discuss. The case of a neutrally buoyant plume emitted from an elevated point source in a turbulent boundary layer considers. The results show that wind turbulence is an important factor in the pollutant dispersion and introduces expected random fluctuations in pollutant distribution and leads to spreading the distribution due to wind mixing.

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Section: Modeling the Sensor And Instrumentation Noise νmentioning

confidence: 99%

Filtering effect of wind flow turbulence on atmospheric pollutant dispersion

Yassin

2011

Environ Monit Assess

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“…With the rapid development of computer technology, modern control theory technology, sensors, and Internet of Things communication technology, various toxic and harmful gas monitoring technologies based on wireless communication networks are widely used in many industries, including petroleum, petrochemical, coal, municipal, fire, metallurgy, gas, medicine, telecommunications, electricity, and food processing [2,3]. A toxic gas monitoring system featuring intelligence, automation, and online features has also been developed [4,5,6,7,8]. In particular, the mature application of wireless communication technology provides a mature basic network support for the collection, detection, monitoring, and early warnings of toxic and harmful gases in special environments [9,10,11,12,13,14].…”

Section: Introductionmentioning

confidence: 99%

“…(4) The existing toxic and harmful gas monitoring devices do not possess explosion-proof characteristics. However, most of the toxic and harmful gases are flammable gases, so if the electronic equipment does not have explosion-proof characteristics: it is easy to become a source of ignition, resulting in site explosion and secondary disasters [7].…”

Section: Introductionmentioning

confidence: 99%

Design and Application of Toxic and Harmful Gas Monitoring System in Fire Fighting

Yang

Zhu

Sui

et al. 2019

Sensors

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In recent years, fire accidents in petrochemical plant areas and dangerous goods storage ports in China have shown a trend of frequent occurrence. Toxic and harmful gases are diffused in the scenes of these accidents, which causes great difficulties for fire fighting and rescue operations of fire fighting forces, and consequently, casualties of firefighters often occur. In order to ensure the safety of firefighters in such places, this paper designs a monitoring system of toxic and harmful gases specially used in fire fighting and rescue sites of fire forces, and establishes the transmission network, monitoring terminal and data processing software of the monitoring system of toxic and harmful gases, establishing the danger model of the monitoring area of toxic and harmful gas-monitoring terminal, and the danger model of fire fighters’ working area, fusing the field toxic and harmful gas data, terminal positioning data, and field environmental data, designing the data structure of the input data set and the network structure of the RNN cyclic neural network model, and realizing the dynamic early warning of toxic and harmful gases on site.

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Methodologies for data mining and modeling of atmospheric pollutants

Yassin

Gebali

2009

Exhibition

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Autonomous system for real time air pollution monitoring using semiconductor toxic gas sensors

Cited by 5 publications

References 1 publication

Filtering effect of wind flow turbulence on atmospheric pollutant dispersion

Filtering effect of wind flow turbulence on atmospheric pollutant dispersion

Design and Application of Toxic and Harmful Gas Monitoring System in Fire Fighting

Methodologies for data mining and modeling of atmospheric pollutants

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