Using Internet of Things for vehicle’s emission monitoring

Akbari, Seyedmojtaba (2016) Using Internet of Things for vehicle’s emission monitoring. [USQ Project]

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Abstract

Out of literally hundreds of applications that have been listed in the literature about the usage of Internet of Things in industry, health, security, home automation and so on, perhaps intelligent transportation systems are the most tangible ones in people daily lives. Automotive manufacturers install so many sensors and actuators on their modern cars these days to provide more safety and convenience to their customers. Town planners and government authorities are constantly trying to improve road safety issues, provide easier traffic flow for citizens and decrease road fatalities. That is because the Internet of Things has been identified as a contributing solution.

As can be seen in Chapter 2 of this document, there is an ongoing research about the ways and possibilities to efficiently and securely facilitate a communication between a particular vehicle and its surrounding objects in the road or the communication between a car and road infrastructure for instance. The objective for such interactions on the road may vary greatly depending on the purpose of the research. Likewise, this research finds Internet of Things as an opportunity to fill an identified gap in the literature in regard to continuously monitor vehicle’s emission level and notify the driver if the vehicle is polluting the air more than what it is permitted to. To do so, this research has done literature review, identified relevant applications and then proposed a conceptual model from ground up plus some optimisation at the end.

In a nutshell, the proposed model is to get some data through pre-existing sensors in the vehicles which has been extensively explained in Chapter 4 of this document. After obtaining the raw emission data from sensors successfully, the plan is to pass them to an active RFID tag which has to be installed on vehicles for communication purposes. Next, data will be transmitted to data collection points mounted at specific points in the traffic region and later on relayed to a remote control centre to log the received data, analyse them and extract a meaningful information out of them accordingly. Consequently, a notification message will be issued to the driver if processing unit residing in the remote control centre realises that a particular vehicle needs attention because the amount of emission out of exhaust manifold seems to be abnormal.

This research has argued that, out of several identified issues toward implementing this solution, minimising the cost is something which worth further studying because cutting down the project expenditure costs will probably motivate authorities to invest on such pilot studies. Therefore, a numerical approach in conjunction with a mathematical theory have been leveraged in this study to provide a mean to minimise the expenditure cost as much as possible. To evaluate aforementioned cost optimisation process, a thorough discrete event software simulation has been done with the aid a software from Rockwell Automation called Arena Simulation. To be more specific, a decent size traffic portion of Sydney’s CBD area has been randomly opted to demonstrate the feasibility of cost optimisation. As a result of such simulation, it turned out that 50 percent of costs associated with data collection points can be cut. As the trade-off, up to 40 percent of the passing vehicles in the chosen traffic area can be successfully monitored for their emission level.


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Item Type: USQ Project
Item Status: Live Archive
Additional Information: Bachelor of Engineering (Honours) Major Electrical & Electronic Engineering project
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering
Supervisors: Kist, Alexander
Date Deposited: 19 Jul 2017 00:27
Last Modified: 19 Jul 2017 23:40
Uncontrolled Keywords: Internet of things, vehicle emission, remote control centre
Fields of Research : 09 Engineering > 0906 Electrical and Electronic Engineering > 090602 Control Systems, Robotics and Automation
URI: http://eprints.usq.edu.au/id/eprint/31292

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