Real Time Tracking System and Data Reduction

IoT;Tracking;Temperature;GPRS;GPS;GSM;Vehicle;Cloud;Data;Data Size;Database;SIM908;System;SQL;NoSQL

Ababtein, Noradvisor:Naik, Kshirasagar ; affiliation1:Faculty of Engineering ; Naik, Kshirasagar ;

University of Waterloo

关键词: GSM;    SIM908;    Temperature;    Tracking;    Master Thesis;    Data;    GPRS;    GPS;    System;    IoT;    SQL;    Vehicle;    NoSQL;    Data Size;    Cloud;    Database;   

Others  :  https://uwspace.uwaterloo.ca/bitstream/10012/12269/1/Ababtein_Nor.pdf

瑞士|英语

来源: UWSPACE Waterloo Institutional Repository

【 摘 要 】

Today, for various purposes, vehicle tracking systems are used for determining the geographic location of vehicles and transmitting this information to a data center. For detecting the location, a GPS is used, and for the transmission mechanism, a satellite or cell tower is deployed. Tracking systems are producing a massive data since they monitor moving vehicles continuously and report vehicle status. Since the amount of collected data is large and needs a storage unit that can handle all the transmitted data, storage becomes more challenging. The cost of transmitting, processing, storing, and accessing the data grows as the number of vehicles being tracked increases. The amount of data collected by the system depends on the uploading frequency. For example, the amount of data will increase as the uploading frequency (seconds) decreases and vice versa.This work provides a storage management solution that reduces the size of cloud databases, both SQL and NoSQL databases, by eliminating repeated data. One of the causes of massive data in the tracking system is the high uploading frequency that causes a huge amount of repetitive values. We propose two algorithms for minimizing database storage: The Reducing Data Redundancy algorithm and the Data Lifetime algorithm. We implement these two algorithms in the cloud, for both SQL and NoSQL databases. For evaluation, a vehicle tracking system is developed by using Global Positioning System (GPS) and GSM/GPRS module. Our experiments use two different approaches: Static testing for when a vehicle is not in motion mode, and dynamic for when it is. The result of the experiments shows the effectiveness of these two algorithms in decreasing storage size and increasing process time. The system has four parts, which are the tracking unit, cloud database, web application, and Android Application. The tracking unit is installed inside a vehicle to detect the vehicle’s location, speed, and temperature then uploads this information to a cloud database. The main functions of the system are to track a vehicle, transmit the information to the cloud, and send notifications to the system administrator and users. The Android application is designed to receive notifications and view the vehicle’s information such as the current location and temperature. The administrator of the system uses the web application to set constraints for users’ vehicles, such as the temperature range and location restriction.