A crowdsensing platform for real-time monitoring and analysis of noise pollution in smart cities
| Autor: | Miloš Radenković, Zorica Bogdanović, Ivan Jezdović, Snežana Popović, Aleksandra Labus |
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| Rok vydání: | 2021 |
| Předmět: |
Decision support system
General Computer Science Database business.industry Computer science Noise pollution Big data 0211 other engineering and technologies 021107 urban & regional planning Cloud computing 02 engineering and technology 010501 environmental sciences computer.software_genre 01 natural sciences Crowdsensing 11. Sustainability Scalability Web application Noise (video) Electrical and Electronic Engineering business computer 0105 earth and related environmental sciences |
| Zdroj: | Sustainable Computing: Informatics and Systems. 31:100588 |
| ISSN: | 2210-5379 |
| DOI: | 10.1016/j.suscom.2021.100588 |
| Popis: | This paper presents a crowdsensing platform for real-time monitoring and analysis of noise pollution in smart cities. The aim is to develop a comprehensive methodology and scalable infrastructure for measuring noise using mobile crowdsensing, storing and analysis of gathered data. The developed system consists of: 1) a mobile application for participatory and opportunistic crowdsensing of noise data from different microlocations, pre-processing of collected data, and sending data to the cloud, 2) a big data infrastructure for storing data and real-time big data analysis, and 3) a web application for decision support. Further, we have created a methodology that lets us select priority microlocations not typically covered by stationary measuring. The system has been evaluated experimentally; more than 4000 measurements were collected at five microlocations in the city of Belgrade, Serbia. Data was analysed in order to find the patterns that could serve for decision support to different stakeholders. |
| Databáze: | OpenAIRE |
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