Candidate
Salman Almishari
Title
Real Time Vehicle Tracking System and Energy Reduction
Supervisor
Kshirasagar Naik
Abstract
Technology has been growing rapidly and different fields of technology can be combined to advance societies. Internet of Things (IoT) is one of these technologies that combine and connect a variety of things to come up with some more beneficial information. In this thesis, an example of IoT portable system has been built and tested.
The system is called Smart Vehicle System (SVS), which includes three main parts: Tracking Unit, Cloud, and Android application. The Tracking Unit is positioned inside a vehicle to sense the vehicle’s temperature, speed, and location then uploads them to the cloud via GSM network. All the component and communication of this Tracking Unit is described in details. The cloud includes web panel to view and manage the data, web server to do some data processing, and database to store all the information. However, the Android application is used to receive notifications and to view the vehicle’s current temperature and location.
Some constraints were included in the system to notify the administrator and the driver of certain events. The emphasis was on two main constraints which are high or low temperature inside the vehicle and location restrictions. The administrator set up these constraints using the web panel. If there is any violation of these constraints, notifications are issued and sent to the administrator via email and to the Android application. The processes of these constraints are described in more details. This system intends to help transportation companies to manage their fleets more effectively.
The SVS is a portable system, which makes it function on batteries. Therefore, a power reduction algorithm was recommended and examined. We have performed 19 different experiments, before and after applying the proposed algorithm, four of them are dynamic and 15 are at a fixed location. With the power reduction algorithm, we are able to reduce the energy consumption of the tracking unit up to 17%. All the setup and results are presented. Monsoon Power Monitor device and a laptop were used to measure the power consumption and compare the results. Finally, we conclude that there is a need for data processing before uploading them to the cloud which saves power and database size.