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Article

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Title

Hardware Efficient Solutions for Wireless Air Pollution Sensors Dedicated to Dense Urban Areas

Authors

[ 1 ] Instytut Architektury i Planowania Przestrzennego, Wydział Architektury, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.1] Architecture and urban planning

Year of publication

2020

Published in

Remote Sensing

Journal year: 2020 | Journal volume: vol. 12 | Journal number: iss. 5

Article type

scientific article

Publication language

english

Keywords
EN
  • air pollution sensors
  • air pollution maps
  • edge computing
  • pollution data processing
  • analog-to-digital converters
  • low power circuits
Abstract

EN This paper proposes novel solutions for the application of air pollution monitoring systems in so called ‘smart cities’. A possibility of the implementation of a relatively dense network of wireless air pollution sensors that can collect and process data in real time was the motive behind our research and investigations. We discuss the concept of the wireless sensor network, taking into account the structure of the urban development in cities and we present a novel signal processing algorithm that may be used to control the communication scheme between particular sensors and an external network. We placed a special emphasis on the computational complexity to facilitate the implementation directly at the transistor level of particular sensors. The algorithm was verified using real data obtained from air pollution sensors installed in Krakow, Poland. To ensure sufficient robustness of the variability of input data, we artificially added high amplitude noise to the real data we obtained. This paper demonstrates the performance of the algorithm. This algorithm allows for the reduction of the noise amplitude by 23 dB and enables a reduction of the number of wireless communication sessions with a base station (BS) by 70%–80%. We also present selected measurement results of a prototype current-mode digital-to-analogue converter to be used in the sensors, for signal resolutions up to 7 bits.

Date of online publication

2020

Pages (from - to)

776-1 - 776-25

DOI

10.3390/rs12050776

URL

https://mdpi.com/2072-4292/12/5/776

Comments

article number: 776

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Full text of article

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Access level to full text

public

Ministry points / journal

100

Ministry points / journal in years 2017-2021

100

Impact Factor

4,848

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