Tracking vehicles is becoming more essential in the present world of logistics market, as delay in delivery and pick-up of goods is costing more especially for startups. Keeping track of the vehicles help in managing resources in a more efficient way, and increasing profit. The tracking must be done in a more efficient way with less latency. This work proposes an online GPS vehicle tracking framework which tracks vehicles continuously. This work outputs vehicles status, position and also includes features like driver well-being by observing the level of vehicle control, weariness anticipation utilizing the EYE-BLINK and MEMS sensor. The proposed system stores the complete details about the travel of a vehicle like the route, distance travelled, driver control over the vehicle, and the cautions happened. This work will help in understanding the condition of the vehicle and the driver efficiency also

1. http://www.iaeme.com/IJCIET/index.asp 105 editor@iaeme.com
International Journal of Civil Engineering and Technology (IJCIET)
Volume 9, Issue 11, November 2018, pp. 105–111, Article ID: IJCIET_09_11_011
Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=9&IType=10
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
©IAEME Publication Scopus Indexed
TRUCK TRACKING AND ALERTS
MONITORING SYSTEM
V. Kanchana Devi
School of Computer Science and Engineering, VIT University Chennai, India
A. David Maxim Gururaj*
Mathematics Division, School of Advanced Sciences, VIT University Chennai, India
A. Kavya
School of Computer Science and Engineering, VIT University Chennai, India
E. Umamaheswari
School of Computer Science and Engineering, VIT University Chennai, India
*Corresponding Author E-mail: davidmaxim.gururaj@vit.ac.in
ABSTRACT
Tracking vehicles is becoming more essential in the present world of logistics
market, as delay in delivery and pick-up of goods is costing more especially for
startups. Keeping track of the vehicles help in managing resources in a more efficient
way, and increasing profit. The tracking must be done in a more efficient way with
less latency. This work proposes an online GPS vehicle tracking framework which
tracks vehicles continuously. This work outputs vehicles status, position and also
includes features like driver well-being by observing the level of vehicle control,
weariness anticipation utilizing the EYE-BLINK and MEMS sensor. The proposed
system stores the complete details about the travel of a vehicle like the route, distance
travelled, driver control over the vehicle, and the cautions happened. This work will
help in understanding the condition of the vehicle and the driver efficiency also.
Key words: Vehicle Tracking, Vehicle Condition Monitoring, Sensors, GSM - Global
System for Mobile, GPS - Global Positioning System, Location Monitoring.
Cite this Article: V. Kanchana Devi, A. David Maxim Gururaj, A. Kavya,
E. Umamaheswari, Truck Tracking and Alerts Monitoring System, International
Journal of Civil Engineering and Technology (IJCIET) 9(11), 2018, pp. 105–111.
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=9&IType=11
1. INTRODUCTION
The proposed methodology is about the truck administration and alerts monitoring, in which a
web application is developed for an organization to track the location of their vehicles. In this,
the proprietor or the person in-charge for tracking vehicles will be able to view the location of

2. Truck Tracking and Alerts Monitoring System
http://www.iaeme.com/IJCIET/index.asp 106 editor@iaeme.com
a vehicle on multiple devices like mobile, desktop and tablet. The owner of a vehicle can also
view the cautions given to the driver of a particular vehicle. With quick increment in the
vehicles it is necessary to automate the tracking process, this will also help in tracking theft
and hijacking of vehicles. This will also help in finding out the efficiency of the driver in
maintaining the time and skills in handling the vehicle. This will also help in finding out if the
driver has exercised any non-business related works which has in-term delayed the trip. This
will help the vehicle owners in tracking a device from a remote location anywhere anytime.
This work also observes the driver well-being by observing the level of vehicle control,
weariness anticipation by using EYE-BLINK and MEMS sensor [1]. By using these sensors,
alerts will be given to the drivers when there is a possibility of disaster. These entire data of
will be saved in cloud for processing in finding out ways to improve the vehicle and driver
efficiency [2] [3]. The condition of vehicles can also be assessed using the cloud [4] data and
special training can be given to drivers if their driving patterns are delaying the trips.
2. ARCHITECTURE
Figure 1 System Architecture
3. VEHICLE TRACKING
The most important module in the proposed system is to track the truck and monitor in web
application using IoT devices. The vehicle direction is observed using accelerometer sensor or
MEMS sensor [5][6]. The following framework gives the position of vehicles in a more
accurately. The objective of this module is to track vehicles and screen the location details
using the programming unit that gets the data and exchanges motion through GPS satellite[7]
[8]. Programmed vehicle area framework utilized online, portable correspondence and Web
based stage for correspondence. This framework empowers to gather and examine the data
about area of vehicle progressively. It is equipped for following an extensive number of
transports at the same time and distinguishes the stationary truck naturally. Tilt sensor is also
used to check the condition of the vehicle, thereby alerting the system in case of any
emergencies [9] [10]. A neural system obtains the satellite related data to get a yield flag
illustrative of recipient related route data, where in the neural system involves one of the
versatile learning for the blunder decrease and ideal count[11] [12]. This system enhances the
normal precision of GPS flag gathering at the transport station. The constant vehicle
monitoring framework includes GPS module deployed in the vehicles, which transmits the
ongoing area of vehicle to the collector sheets deployed in the vehicle stops [13] [14]. The

3. V. Kanchana Devi, A. David Maxim Gururaj, A. Kavya, E. Umamaheswari
http://www.iaeme.com/IJCIET/index.asp 107 editor@iaeme.com
GPS information of the vehicle areas is send to servers and the same is updated same in the
web application for the organization to monitor. Fig 1: shows the entire proposed system
architecture and Fig 2: shows the tracking map saved in the server for future data processing.
Figure 2 Tracking Vehicle Map
4. SENSORS INTERFACING
The framework is appropriate for screening transport vehicles movement in desktop, mobile,
tablet devices inside open transport stations and can advise directors at whatever point the
transport is touching base on time, ahead of time or behind time. Then the data is updated and
displayed on the diverse remote inside and outside the transport station. The Versatile
terminal unit is an installed framework containing RFID per user, GPS and a simple compass
as information gadget to obtain area and position. The vehicle data can be seen on electronic
guide by means of web programming. Alerts can also be sent using sensors which includes
MEMS, Tilt and Eye-blink. MEMS can be used for direction observation. Tilt is used to
determine whether the vehicle is in normal position. Eye blink is used to check the fatigue of
the driver. These all sensors are interfaced in Arduino. GPS module is also incorporated with
that. This level of mechanization is conceivable through an arrangement of calculations that
utilizations GPS follows gathered from travel vehicle to decide the type of alerts encountered.
It involves vehicle-mounted GPS beacons, a focal server framework and an online
application. The area has to be checked graphically and significant alarms data of vehicle.
This system is intended to serve undertakings with a boundless number of vehicles and
complex use necessities. It also empowers client to peruse area track on outline created web
application implant Google Map and associate with database server for vehicles track subtle
elements. This item is one stop answer for all your truck following and ready needs. Fig 3:
Shows the architecture of the interface of the proposed system, Figure 4: Shows the circuit
diagram of the proposed system.

4. Truck Tracking and Alerts Monitoring System
http://www.iaeme.com/IJCIET/index.asp 108 editor@iaeme.com
Figure 3 Architecture of the interface
Figure 4 Circuit Diagram
5. DRIVER MONITORING AND ALERTING
Remote sensor organizes utilized for checking of transport transportation framework and
record of entry time of alerts at transport stops. Here eye blink is used to detect the driver’s
health status. If found any abnormalities in the data produced, the driver can be alerted or any
nearby emergency services can be notified to look after the truck. This type of application is
achieved using this system. Vehicle monitoring systems deals with the GPS and GSM
innovation which gives the area of vehicle to the vehicle proprietor on account of vehicle is
stolen. It can likewise be utilized as a part of natural life following, resource following and in
stolen vehicle recuperation. Transportation is a vital shared asset that empowering productive
and compelling utilization of assets like WSN and GPS units that can be deployed on to the
vehicle and these units will help in tracking the location of the vehicle. Figure 5: Shows the
various functionalities of the proposed system.

5. V. Kanchana Devi, A. David Maxim Gururaj, A. Kavya, E. Umamaheswari
http://www.iaeme.com/IJCIET/index.asp 109 editor@iaeme.com
Figure 5 Functionalities of the proposed system
6. ALERT SYSTEM
The proposed methodology will help users to track their vehicles remotely. The proposed
vehicle tracking system will notify the location and route being travelled by vehicle. The
information sent by tracking system can be viewed in any device, from any remote location.
The accuracy of the location of the vehicle has been improved compared to existing
methodologies. The user can track the vehicles in bad weather conditions also. The tracking
system uses a tracking device with WSN using GPS tracking devices to manage, control and
to know the identity and current location of the vehicle. Alerts given to the driver can also be
viewed by the user from any remote location.
Numerous methods are being used by various authors for vehicle tracking, vehicle
monitoring and for the alerting driver and the system. These existing methods are deployed in
different types of vehicles like bike, car, bud, truck, cargo lorry etc. [15]. The microcontroller
obtains the data from the GPS module and transmits it to the control point with the help of
WSN. In these existing methodologies GSM - Global System for Mobile & GPS - Global
Positioning System are used to send information regarding the location and driver alerts to the
cloud server. Using this data the vehicle can be tracked and stop anywhere in case of
emergency. The Real time passenger information system uses various technologies to track
location of vehicles like bus, train etc., in real-time to generate predictions of vehicle arrival
time at a particular stop along the travel route. This system can also be used for real time
tracking of vehicles, monitor the passengers in the vehicle, predict arrival time at a particular
stop and send all these information to the base station.
In the proposed system, the performance and accuracy of tracking is improved by using
WSN. Google Map is used in the proposed methodology for tracking. The proposed system
comes with both the advantages and complexity of Google maps. This proposed system tracks
the location of the vehicles and send alerts to the drivers but doesn’t predict the arrival time of
the vehicle. The observation and experimental results, it is proved that the proposed system
overcomes the problems in the existing system. Tracking accuracy and the reader efficiency
are also increased with operating frequency and extending the range of the reader. The rate of
data transmission, processing speed of the system has also been enhanced in the proposed
system compared to the existing system. Vehicle tracking, monitoring and alerting system can
be enhanced by using GPS, GSM/GPRS, RFID reader and ARM 11 processor for
development of the vehicle tracking system. The proposed methodology is cost effective and
user friendly when compared with the existing methodologies.

6. Truck Tracking and Alerts Monitoring System
http://www.iaeme.com/IJCIET/index.asp 110 editor@iaeme.com
7. RESULTS & SCREEN SHOTS
Figure 6 depicts the screen shots of the proposed system and route map travelled by the
vehicle.
Figure 6 Screen Shots of the System developed & Route Map Travelled by the vehicle
8. CONCLUSION & FUTURE WORK
The main objective of the project is to develop a GPS tracking system that tracks the vehicle
and alert the system in case of emergencies, to a website where it can be viewed remotely.
The proposed system stores the complete details about the travel of a vehicle like the route,
distance travelled, driver control over the vehicle, and the cautions happened. This work will
help in understanding the condition of the vehicle and the driver efficiency also. The project
has wide range of scope in the future. The project can also be implemented as non-GPS in
future using only the sensor values. The process of updating can be performed easily, as the
methodology proposed in flexible for expansion as per the requirement. With the proposed

7. V. Kanchana Devi, A. David Maxim Gururaj, A. Kavya, E. Umamaheswari
http://www.iaeme.com/IJCIET/index.asp 111 editor@iaeme.com
system, business owners can now able to control their fleet remotely and fully functional alert
system is now able to give information about the conditions of the vehicle.
REFERENCES
[1] Umamaheswari E; Ajay D.M and Umang Sindal. Scope of Internet of Things: A Survey.
Asian Journal of Pharmaceutical and Clinical Research, 2017, pp. 187-190.
[2] Ajay D.M and Umamaheswari.E. An initiation for testing the security of a cloud service
provider. Smart Innovation, Systems, Technologies. Switzerland: Springer Publications;
2016. pp. 35-41.
[3] Ajay D.M and Umamaheswari.E. Why, how cloud computing- How not and cloud
security issues?. Global Journal of Pure and Applied Mathematics (GJPAM) , 12(1), 2016,
pp.1-8.
[4] D M Ajay and Umamaheswari E. Evaluating the Efficiency of Security Mechanisms in
Cloud Environments. International Journal of Control Theory and Applications, Vol. 9,
No.51, 2016, pp.75-85.
[5] I. Skog and P. Handel. In-car positioning and navigation technologies – A survey. IEEE
Trans. Intell. Transp. Syst., vol. 10, no. 1, 2009, pp. 4-21.
[6] DachuanLi; Qing Li; Liangwen Tang; Sheng Yang; Nong Cheng and Jingyan Song.
Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied
Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors.
Micromachines, vol. 6, no. 4, 2015, pp. 487-522.
[7] E. Costa. Simulation of the effects of different urban environments on GPS performance
using digital elevation models and building databases. IEEE Trans. Intell. Transp. Syst.,
vol. 12, no. 3, Sep. 2011, pp. 819-829.
[8] X. Zhang; B. Xian; B. Zhao and Y. Zhang. Autonomous Flight Control of a Nano
Quadrotor Helicopter in a GPS-denied Environment Using On-board Vision. IEEE Trans.
Ind. Electron., vol. 62, no. 10, Oct. 2015 pp. 6392-6403.
[9] M. Barczyk and A. F. Lynch. Invariant observer design for a helicopter UAV aided
inertial navigation system. IEEE Trans. Control Syst. Technol., vol. 21, no. 3, 2013, pp.
791-806.
[10] A. Noureldin; T. B. Karamat; M. D. Eberts and A. El-Shafie, Performance enhancement
of MEMS-based INS/GPS integration for low-cost navigation applications. IEEE Trans.
Veh. Technol., vol. 58, no.3, 2009, pp. 1077-1096.
[11] D. Bhatt; P. Aggarwal; V. Devabhaktuni and P. Bhattacharya. A novel hybrid fusion
algorithm to bridge the period of GPS outages using low-cost INS. Expert Systems with
Applications, vol. 41, no. 5, 2014, pp. 2166-2173.
[12] S. Adusumilli; D. Bhatt; H. Wang; P. Bhattacharya and V. Devabhaktunia. A low-cost
INS/GPS integration methodology based on random forest regression. Expert Systems
with Applications, vol. 40, no. 11, 2013, pp. 4653-4659.
[13] A. Noureldin; A. El-Shafie, and M. Bayoumi. GPS/INS integration utilizing dynamic
neural networks for vehicular navigation. Information Fusion, vol. 12, no. 1, Jan. 2011,
pp. 48-57.
[14] R. Sharaf, and A. Noureldin. Sensor integration for satellite-based vehicular navigation
using neural networks. IEEE Trans. Neural Netw., vol. 18, no. 2, 2007, pp.589-594,
[15] Z. Xu; Y. Li; C. Rizos and X. Xu. Novel hybrid of LS-SVM and kalman filter for
GPS/INS integration. Journal of Navigation, vol. 63, no. 02, 2010, pp. 289-299.