Road vehicle alert system using IOT

Chaczko, Z; Jiang, F; Ahmed, B

Road vehicle alert system using IOT

Chaczko, Z

Jiang, F Ahmed, B

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 25th International Conference on Systems Engineering, ICSEng 2017, 2017, 2017-January pp. 488 - 496
Issue Date:: 2017-11-27

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Field	Value	Language
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510	en_US
dc.contributor.author	Jiang, F	en_US
dc.contributor.author	Ahmed, B	en_US
dc.date.issued	2017-11-27	en_US
dc.identifier.citation	Proceedings - 25th International Conference on Systems Engineering, ICSEng 2017, 2017, 2017-January pp. 488 - 496	en_US
dc.identifier.isbn	9781538606100	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126433
dc.description.abstract	© 2017 IEEE. The consequence of road accidents that involves a motorcycle is far more fatal for the rider than the other drivers. Yet, there has not been an effective vehicle alert system that can eliminate these avoidable motorcycle accidents caused by other drivers where they fail to notice the motorcycles. One of the major flaws with the existing vehicle alert systems is that it should not treat motorcycles as same as other vehicles as they take much longer time to brake than a cars do. Therefore, this project aimed to find an effective method to identify motorcycles and alert the other drivers when motorcyclists are around them in 20-meter radius. After extensive literature review, the best method to solve the problem is to use road side infrastructure based Internet of Things (IOT) that divides the network into a set of clusters. In this method to identify a vehicle, it is identifying the driver and the rider from their smartphone application that beacons custom, unique Media Access Control (MAC) addresses via Bluetooth or Wi-Fi to the IOT probes. The probe differentiates the users, registers them when they arrive into the network, alerts the driver about motorcycles around them and removes them from the database when they move to other cluster. The whole scenario is simulated using the OMNET++ simulator and INET framework to demonstrate how the methodology works. If the concept is implemented in real-life, many valuable lives of motorists will be much safer on the road.	en_US
dc.relation.ispartof	Proceedings - 25th International Conference on Systems Engineering, ICSEng 2017	en_US
dc.relation.isbasedon	10.1109/ICSEng.2017.72	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Road vehicle alert system using IOT	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2017-January	en_US
utslib.for	0902 Automotive Engineering	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
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/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	2017-January	en_US

Abstract:

© 2017 IEEE. The consequence of road accidents that involves a motorcycle is far more fatal for the rider than the other drivers. Yet, there has not been an effective vehicle alert system that can eliminate these avoidable motorcycle accidents caused by other drivers where they fail to notice the motorcycles. One of the major flaws with the existing vehicle alert systems is that it should not treat motorcycles as same as other vehicles as they take much longer time to brake than a cars do. Therefore, this project aimed to find an effective method to identify motorcycles and alert the other drivers when motorcyclists are around them in 20-meter radius. After extensive literature review, the best method to solve the problem is to use road side infrastructure based Internet of Things (IOT) that divides the network into a set of clusters. In this method to identify a vehicle, it is identifying the driver and the rider from their smartphone application that beacons custom, unique Media Access Control (MAC) addresses via Bluetooth or Wi-Fi to the IOT probes. The probe differentiates the users, registers them when they arrive into the network, alerts the driver about motorcycles around them and removes them from the database when they move to other cluster. The whole scenario is simulated using the OMNET++ simulator and INET framework to demonstrate how the methodology works. If the concept is implemented in real-life, many valuable lives of motorists will be much safer on the road.

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

http://hdl.handle.net/10453/126433