Ontological Security and Private Car Use in Sydney, Australia

Kent, J

Ontological Security and Private Car Use in Sydney, Australia

Kent, J

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Publisher:: SAGE Publications
Publication Type:: Journal Article
Citation:: Sociological Research Online: an electronic journal, 2020, 21, (2), pp. 1-14
Issue Date:: 2020-06-30

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Field	Value	Language
dc.contributor.author	Kent, J https://orcid.org/0000-0002-8063-9503
dc.date.accessioned	2022-10-04T21:31:07Z
dc.date.available	2022-10-04T21:31:07Z
dc.date.issued	2020-06-30
dc.identifier.citation	Sociological Research Online: an electronic journal, 2020, 21, (2), pp. 1-14
dc.identifier.isbn	978-1-7281-4053-7
dc.identifier.issn	1360-7804
dc.identifier.issn	1360-7804
dc.identifier.uri	http://hdl.handle.net/10453/162310
dc.description.abstract	Transforming our roads into smart roads is an indispensable step towards future self-driving systems, and therefore has drawn increasing attention from both academia and industry. To this end, this paper develops a novel cost-effective IoT-based target detection system utilizing the multi-sensor data fusion technology with a particular focus on pedestrian detection, as an important component of smart road system. Particularly, the developed intelligent pedestrian detection module (iPDM) consists of three major sensors, i.e., Doppler microwave radar sensor, passive infrared (PIR), and geomagnetic sensor. A multisensor data fusion algorithm is developed to fuse the sensor data and achieves reliable target detection. After that, iPDM sends the relevant warning signal wirelessly to nearby base station and vehicles. Experiments are conducted on real traffic environment to evaluate the performance of iPDM. The results validate the high reliability of iPDM with an average 91.7% detection accuracy. Moreover, to our best knowledge, iPDM is the first IoT-based implementation for pedestrian detection of smart roads. It is necessary to highlight that iPDM is a low-cost, low-power, wide-coverage pedestrian detection system where the cost of a single iPDM is only US $30, which makes it suitable to large-scale deployment.
dc.language	en
dc.publisher	SAGE Publications
dc.relation.ispartof	Sociological Research Online: an electronic journal
dc.relation.isbasedon	10.5153/sro.3860
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	1608 Sociology
dc.subject.classification	Sociology
dc.title	Ontological Security and Private Car Use in Sydney, Australia
dc.type	Journal Article
utslib.citation.volume	21
utslib.location.activity	Antwerp, Belgium
utslib.for	1608 Sociology
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Arts and Social Sciences
pubs.organisational-group	/University of Technology Sydney/e-Press
pubs.organisational-group	/University of Technology Sydney/Faculty of Arts and Social Sciences/School of Communication
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-10-04T21:31:06Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	21
utslib.citation.issue	2

Abstract:

Transforming our roads into smart roads is an indispensable step towards future self-driving systems, and therefore has drawn increasing attention from both academia and industry. To this end, this paper develops a novel cost-effective IoT-based target detection system utilizing the multi-sensor data fusion technology with a particular focus on pedestrian detection, as an important component of smart road system. Particularly, the developed intelligent pedestrian detection module (iPDM) consists of three major sensors, i.e., Doppler microwave radar sensor, passive infrared (PIR), and geomagnetic sensor. A multisensor data fusion algorithm is developed to fuse the sensor data and achieves reliable target detection. After that, iPDM sends the relevant warning signal wirelessly to nearby base station and vehicles. Experiments are conducted on real traffic environment to evaluate the performance of iPDM. The results validate the high reliability of iPDM with an average 91.7% detection accuracy. Moreover, to our best knowledge, iPDM is the first IoT-based implementation for pedestrian detection of smart roads. It is necessary to highlight that iPDM is a low-cost, low-power, wide-coverage pedestrian detection system where the cost of a single iPDM is only US $30, which makes it suitable to large-scale deployment.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/162310