A Scheme on Pedestrian Detection using Multi-Sensor Data Fusion for Smart Roads

Wang, H; Li, C; Zhang, Y; Liu, Z; Hui, Y; Mao, G

A Scheme on Pedestrian Detection using Multi-Sensor Data Fusion for Smart Roads

Wang, H Li, C Zhang, Y Liu, Z Hui, Y Mao, G

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: IEEE Vehicular Technology Conference, 2020, 2020-May, pp. 1-5
Issue Date:: 2020-05-01

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Field	Value	Language
dc.contributor.author	Wang, H
dc.contributor.author	Li, C
dc.contributor.author	Zhang, Y
dc.contributor.author	Liu, Z
dc.contributor.author	Hui, Y
dc.contributor.author	Mao, G https://orcid.org/0000-0002-3598-4949
dc.date	2020-05-25
dc.date.accessioned	2021-05-21T21:50:34Z
dc.date.available	2021-05-21T21:50:34Z
dc.date.issued	2020-05-01
dc.identifier.citation	IEEE Vehicular Technology Conference, 2020, 2020-May, pp. 1-5
dc.identifier.isbn	9781728152073
dc.identifier.issn	1550-2252
dc.identifier.uri	http://hdl.handle.net/10453/149052
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 ({i}PDM) consists of three major sensors, i.e., Doppler microwave radar sensor, passive infrared (PIR), and geomagnetic sensor. A multi-sensor data fusion algorithm is developed to fuse the sensor data and achieves reliable target detection. After that, {i}PDM sends the relevant warning signal wirelessly to nearby base station and vehicles. Experiments are conducted on real traffic environment to evaluate the performance of {i}PDM. The results validate the high reliability of {i}PDM with an average 91.7% detection accuracy. Moreover, to our best knowledge, {i}PDM is the first IoT-based implementation for pedestrian detection of smart roads. It is necessary to highlight that {i}PDM is a low-cost, low-power, wide-coverage pedestrian detection system where the cost of a single {i}PDM is only US 30, which makes it suitable to large-scale deployment.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	IEEE Vehicular Technology Conference
dc.relation.ispartof	2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring)
dc.relation.isbasedon	10.1109/VTC2020-Spring48590.2020.9128855
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	A Scheme on Pedestrian Detection using Multi-Sensor Data Fusion for Smart Roads
dc.type	Conference Proceeding
utslib.citation.volume	2020-May
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2021-05-21T21:50:33Z
pubs.finish-date	2020-05-28
pubs.publication-status	Published
pubs.start-date	2020-05-25
pubs.volume	2020-May

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 ({i}PDM) consists of three major sensors, i.e., Doppler microwave radar sensor, passive infrared (PIR), and geomagnetic sensor. A multi-sensor data fusion algorithm is developed to fuse the sensor data and achieves reliable target detection. After that, {i}PDM sends the relevant warning signal wirelessly to nearby base station and vehicles. Experiments are conducted on real traffic environment to evaluate the performance of {i}PDM. The results validate the high reliability of {i}PDM with an average 91.7% detection accuracy. Moreover, to our best knowledge, {i}PDM is the first IoT-based implementation for pedestrian detection of smart roads. It is necessary to highlight that {i}PDM is a low-cost, low-power, wide-coverage pedestrian detection system where the cost of a single {i}PDM is only US 30, which makes it suitable to large-scale deployment.

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http://hdl.handle.net/10453/149052