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[113370] Artykuł:

The Prototype Monitoring System for Pollution Sensing and Online Visualization with the Use of a UAV and a WebRTC-Based Platform

Czasopismo: Sensors   Tom: 22
ISSN:  1424-8220
Opublikowano: 2022
 
  Autorzy / Redaktorzy / Twórcy
Imię i nazwisko Wydział Katedra Do oświadczenia
nr 3
Grupa
przynależności
Dyscyplina
naukowa
Procent
udziału
Liczba
punktów
do oceny pracownika
Liczba
punktów wg
kryteriów ewaluacji
Agnieszka Chodorek orcid logo WEAiIKatedra Elektrotechniki Przemysłowej i Automatyki**Takzaliczony do "N"Automatyka, elektronika, elektrotechnika i technologie kosmiczne3350.0050.00  
Robert Ryszard Chodorek Niespoza "N" jednostki033.00.00  
Aleksander Iwanowicz Jastriebow orcid logo WEAiIKatedra Systemów Informatycznych *Takzaliczony do "N"Automatyka, elektronika, elektrotechnika i technologie kosmiczne3350.0050.00  

Grupa MNiSW:  Publikacja w czasopismach wymienionych w wykazie ministra MNiSzW (część A)
Punkty MNiSW: 100


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Keywords:

field experiment  Internet of Things  unmanned aerial vehicle  pollution monitoring  urban environment  online visualization  WebRTC 



Abstract:

Nowadays, we observe a great interest in air pollution, including exhaust fumes. This interest is manifested in both the development of technologies enabling the limiting of the emission of harmful gases and the development of measures to detect excessive emissions. The latter includes IoT systems, the spread of which has become possible thanks to the use of low-cost sensors. This paper presents the development and field testing of a prototype pollution monitoring system, allowing for both online and off-line analyses of environmental parameters. The system was built on a UAV and WebRTC-based platform, which was the subject of our previous paper. The platform was retrofitted with a set of low-cost environmental sensors, including a gas sensor able to measure the concentration of exhaust fumes. Data coming from sensors, video metadata captured from 4K camera, and spatiotemporal metadata are put in one situational context, which is transmitted to the ground. Data and metadata are received by the ground station, processed (if needed), and visualized on a dashboard retrieving situational context. Field studies carried out in a parking lot show that our system provides the monitoring operator with sufficient situational awareness to easily detect exhaust emissions online, and delivers enough information to enable easy detection during offline analyses as well.