The University of Southampton
University of Southampton Institutional Repository

Distributed sensing with low-cost mobile sensors toward a sustainable IoT

Distributed sensing with low-cost mobile sensors toward a sustainable IoT
Distributed sensing with low-cost mobile sensors toward a sustainable IoT
Cities are monitored by sparsely positioned high-cost reference stations that fail to capture local variations. Although these stations must be ubiquitous to achieve high spatio-temporal resolutions, the required capital expenditure makes that infeasible. Here, low-cost IoT devices come into prominence; however, non-disposable and often non-rechargeable batteries they have pose a huge risk for the environment. The projected numbers of required IoT devices will also yield to heavy network traffic, thereby crippling the RF spectrum. To tackle these problems and ensure a more sustainable IoT, cities must be monitored with fewer devices extracting highly granular data in a self-sufficient manner. Hence, this paper introduces a network architecture with energy harvesting low-cost mobile sensors mounted on bikes and unmanned aerial vehicles, underpinned by key enabling technologies. Based on the experience gained through real-world trials, a detailed overview of the technical challenges encountered when using low-cost sensors and the requirements for achieving high spatio-temporal resolutions in the 3D space are highlighted. Finally, to show the capability of the envisioned architecture in distributed sensing, a case study on air quality monitoring investigating the variations in particulate and gaseous pollutant dispersion during the first lockdown of the COVID.19 pandemic is presented. The results showed that using mobile sensors is as accurate as using stationary ones with the potential of reducing device numbers, leading to a more sustainable IoT.
2576-3180
96-102
Cetinkaya, Oktay
6cb457a5-77b8-415d-b524-9e8728c35f0a
Zaghari, Bahareh
a0537db6-0dce-49a2-8103-0f4599ab5f6a
Bulot, Florentin M. J.
47870de2-3ba2-4425-b07a-16ce48ee3956
Damaj, Wissam
1cf14090-963a-40c0-99fe-b77dd30ed885
Jubb, Stephen A.
6ca22f68-3fa5-457f-9c98-bf09e1e9aef9
Stein, Sebastian
fb227373-7242-4982-b84b-90bc79617a50
Weddell, Alex S.
3d8c4d63-19b1-4072-a779-84d487fd6f03
Mayfield, Martin
6edd32cb-ef5d-495b-a5ca-7e826de33df0
Beeby, Steve
ba565001-2812-4300-89f1-fe5a437ecb0d
Cetinkaya, Oktay
6cb457a5-77b8-415d-b524-9e8728c35f0a
Zaghari, Bahareh
a0537db6-0dce-49a2-8103-0f4599ab5f6a
Bulot, Florentin M. J.
47870de2-3ba2-4425-b07a-16ce48ee3956
Damaj, Wissam
1cf14090-963a-40c0-99fe-b77dd30ed885
Jubb, Stephen A.
6ca22f68-3fa5-457f-9c98-bf09e1e9aef9
Stein, Sebastian
fb227373-7242-4982-b84b-90bc79617a50
Weddell, Alex S.
3d8c4d63-19b1-4072-a779-84d487fd6f03
Mayfield, Martin
6edd32cb-ef5d-495b-a5ca-7e826de33df0
Beeby, Steve
ba565001-2812-4300-89f1-fe5a437ecb0d

Cetinkaya, Oktay, Zaghari, Bahareh, Bulot, Florentin M. J., Damaj, Wissam, Jubb, Stephen A., Stein, Sebastian, Weddell, Alex S., Mayfield, Martin and Beeby, Steve (2021) Distributed sensing with low-cost mobile sensors toward a sustainable IoT. IEEE Internet of Things Magazine, 4 (3), 96-102. (doi:10.1109/IOTM.0101.2100007).

Record type: Article

Abstract

Cities are monitored by sparsely positioned high-cost reference stations that fail to capture local variations. Although these stations must be ubiquitous to achieve high spatio-temporal resolutions, the required capital expenditure makes that infeasible. Here, low-cost IoT devices come into prominence; however, non-disposable and often non-rechargeable batteries they have pose a huge risk for the environment. The projected numbers of required IoT devices will also yield to heavy network traffic, thereby crippling the RF spectrum. To tackle these problems and ensure a more sustainable IoT, cities must be monitored with fewer devices extracting highly granular data in a self-sufficient manner. Hence, this paper introduces a network architecture with energy harvesting low-cost mobile sensors mounted on bikes and unmanned aerial vehicles, underpinned by key enabling technologies. Based on the experience gained through real-world trials, a detailed overview of the technical challenges encountered when using low-cost sensors and the requirements for achieving high spatio-temporal resolutions in the 3D space are highlighted. Finally, to show the capability of the envisioned architecture in distributed sensing, a case study on air quality monitoring investigating the variations in particulate and gaseous pollutant dispersion during the first lockdown of the COVID.19 pandemic is presented. The results showed that using mobile sensors is as accurate as using stationary ones with the potential of reducing device numbers, leading to a more sustainable IoT.

This record has no associated files available for download.

More information

e-pub ahead of print date: 7 September 2021

Identifiers

Local EPrints ID: 476851
URI: http://eprints.soton.ac.uk/id/eprint/476851
ISSN: 2576-3180
PURE UUID: c6b75d64-cd68-4627-b873-c27c2d8d2e0a
ORCID for Alex S. Weddell: ORCID iD orcid.org/0000-0002-6763-5460
ORCID for Steve Beeby: ORCID iD orcid.org/0000-0002-0800-1759

Catalogue record

Date deposited: 17 May 2023 17:07
Last modified: 17 Mar 2024 03:05

Export record

Altmetrics

Contributors

Author: Oktay Cetinkaya
Author: Bahareh Zaghari
Author: Florentin M. J. Bulot
Author: Wissam Damaj
Author: Stephen A. Jubb
Author: Sebastian Stein
Author: Alex S. Weddell ORCID iD
Author: Martin Mayfield
Author: Steve Beeby ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×