Processing may take a few seconds...

Article


Title

Air Pollution Monitoring System with Prediction Abilities Based on Smart Autonomous Sensors Equipped with ANNs with Novel Training Scheme

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

2022

Published in

Remote Sensing

Journal year: 2022 | Journal volume: vol. 14 | Journal number: iss. 2

Article type

scientific article

Publication language

english

Keywords
EN
  • air pollution
  • monitoring
  • ANN
  • intelligent sensors
Abstract

EN The paper presents a concept of an air pollution monitoring system with prediction abilities, based on wireless smart sensors, that takes into account local conditions (microclimate) prevailing in particular areas of the city. In most cases reported in the literature, artificial neural networks (ANNs) are used to predict future pollution levels. In existing solutions of this type, ANNs are trained with generalized datasets common for larger areas, e.g., cities. Our investigations show, however, that conditions may strongly differ even between particular streets in the city, which may impact prediction quality. This results from varying density of urban development, different levels of insolation, airiness, amounts of greenery, etc. As a result, with similar values of ANN input signals, such as current pollution levels, temperature, pressure, etc., the results of the prediction may differ significantly from reality. For this reason, we propose an innovative solution, in which particular sensors are equipped with miniaturized low-power ANNs, trained with datasets gathered directly from their closest environment, without a need for the obtaining of such data from a base station. This may simplify the installation and maintenance process of a network of such sensors. In a further part of this work, we dealt with solutions that enable the reduction of the computational complexity of ANNs in the case of their implementation on specialized integrated circuits. We propose replacing the most complex mathematical operations used in the learning algorithm with simpler solutions. A prototype chip containing the main blocks of such an ANN was also designed.

Pages (from - to)

413-1 - 413-22

DOI

10.3390/rs14020413

URL

https://www.mdpi.com/2072-4292/14/2/413/htm

Comments

article number: 413

License type

CC BY (attribution alone)

Points of MNiSW / journal

100.0

Impact Factor

4.848 [List 2020]

This website uses cookies to remember the authenticated session of the user. For more information, read about Cookies and Privacy Policy.