Szczegóły publikacji

Opis bibliograficzny

The prototype monitoring system for pollution sensing and online visualization with the use of a UAV and a WebRTC-based platform / Agnieszka Chodorek, Robert Ryszard CHODOREK, Alexander Yastrebov // Sensors [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 1424-8220. — 2022 — vol. 22 iss. 4, s. 1-27. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 25-27, Abstr. — Publikacja dostępna online od: 2022-02-17

Autorzy (3)

Słowa kluczowe

urban environmentpollution monitoringInternet of Thingsonline visualizationfield experimentWebRTCunmanned aerial vehicle

Dane bibliometryczne

ID BaDAP139224
Data dodania do BaDAP2022-02-24
Tekst źródłowyURL
DOI10.3390/s22041578
Rok publikacji2022
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Creative Commons
Czasopismo/seriaSensors

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.

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