DESIGN OF A GPS/INS EMBEDDED SYSTEM FOR VEHICLE TRACKING AND
REMOTE CONTROLLING
Huy-Tien Bui1, Thanh-Trung Duong2, Ngoc-Tan Bui Thi3, Tsung-Fu Chien4
PhD student, Department of Mechanical Engineering, National Cheng Kung University
No.1, University Rd., Tainan City 70101, Taiwan;
E-mail: huytien_bk@yahoo.com
1
2
PhD student, Department of Geomatics, National Cheng Kung University
No.1, University Rd., Tainan City 70101, Taiwan;
E-mail: duong_trung2004@yahoo.com
3
Master student, Department of Geomatics, National Cheng Kung University
No.1, University Rd., Tainan City 70101, Taiwan;
E-mail: ngoctankhtn@gmail.com
4
Professor, Department of Electrical Engineering, Southern Taiwan University of Science and Technology
No. 1, Nan-Tai Street, Yungkang Dist., Tainan City 710, Taiwan;
E-mail: jeng12@mail.ncku.edu.tw
KEY WORDS: Remote control, Remote monitor, Wi-Fi, GPS, INS.
ABSTRACT: Safety for vehicles during movement and emergency response is necessary for most vehicle owners.
Information about vehicle technique parameters, position, and orientation during operating is also useful for owners
and managers. Therefore, this article develops an INS/GPS/Wi-Fi embedded system for vehicle tracking, remote
controlling and remote monitoring. The main purpose of the integrated system is to on-line monitor the position and
orientation of the vehicle from a control station. Some functions of vehicles are able to be remotely activated in cases
of emergency.
1. INTRODUCTION
In recently, most vehicles have been mounted a global positioning system (GPS) device to track the position of the
vehicles on the road. Some companies used GPS devices in order to manage the vehicle in transport. In the most these
systems, information of position was send to station base center via general packet radio service (GPRS) network
under short message service (SMS) (Dinkar and Shaikh, 2011), (Bilgic and Alkar, 2011). Another application of GPS
was used in a secure tracking system. The current location was sent to web server through GPRS. Basically, operation
of this system likes sending a message between two GPS embedded-mobile phones. One of them was embedded in
system need to secure as shown in Figure 1.
Figure 1. The structure of a secure tracking system using GPRS (Bilgic and Alkar, 2011).
The system was composed of a mobile phone attached to secure tracking system and web interface designed on
personal computer (PC) or smart phone to monitor the track maps or current locations of secure-needed system. The
users can set boundaries of locations being tracked so that an alert may be activated if a boundary violation has been
detected and owner can send short message service (SMS) to switch off the vehicle (Montaser et al., 2012).
The remote tracking and monitoring are two important problems widely used in life, transport, army and medical. In
this paper, en embedded system is proposed to identify and monitor a vehicle location in transport line with real time.
The vehicle location information is remotely managed and controlled to turn off the vehicle power supply via
Wi-Fi/GSM modules. The GPS module provided the current vehicle location is sent from moving part which is
installed in the vehicle, to personal computer (PC) or smart phone devices via Wi-Fi signal for short distance about
1-2 Km up to 50 Km and via GSM signal for long distance. A simple sensor is used to sense the safety state of vehicle.
When the vehicle is in emergency, stolen for example, the signal from sensor will be coded then sent immediately to
PC or smart phone devices for informing vehicle owner. Vehicle owner can then use that PC or smart phone device to
track the vehicle location, which current road address the vehicle at, and control back to the vehicle for turning off the
vehicle power supply or given alarm to theft. A graphic user interface (GUI) was developed based on visual studio C#
to manage the vehicle location and control feed-back to vehicle. A diagram of proposed embedded system used in this
research was shown in Figure 2.
Figure 2. A proposed embedded system used for tracking and remote controlling the vehicle
2. EXPERIMENT WORKS
A proposed embedded system composed of two main parts; a control base station and a moving station. In the moving
station, an integrated system (modules) including Inertial Navigation System (INS) and Global Positioning System
(GPS) was attached on the vehicle to provide information about position and orientation of the vehicle. These
modules were connected to a microcontroller unit – ATmega 2560 for processing and then transmitting signal to
control base station via Wi-Fi/GPS modules. In the control base station, a PC or smart phone devices were used to
receive the signal from the moving station.
For experiment works, an integrated system was setup. In the moving station, a low cost inertial navigation system
(INS)-MPU-6050 of 6 dimensions: three accelerometers and three gyroscopes, a GPS receiver module, a
microcontroller-ATmega 2560, a Wi-Fi module and a camera module were attached for collecting, decoding and
transmitting data to the control station. In the control base station, a PC was used to receive and analyze the data
transmitted from the moving station. Components used in this paper were shown in Figure 3.
GPS GS-91module
Microcontroller-ATmega 2560
INS module-MPU-6050
Wi-Fi module-RM04
Mobile phone-embedded Camera
A proposed embedded system-moving part
Figure 3. Components used in research
The GPS and IMU data read and processed by microcontroller was sent to PC and Android environment
operation-based smart phone via Wi-Fi module or GSM/3G module for post-processing as shown in Figure 4.
Algorithm of extended Kalman filter will then used for the obtained GPS and IMU data to get more accurate
location.
Figure 4. Structure of main unit of embedded system used in research
Power supply - battery used in vehicle is 12 voltages, but that is 5 voltages in microcontroller unit. A component
named relay that transfers electrical signal between microcontroller unit and vehicle switching circuit was therefore
used. The microcontroller received comment from PC or smart phone by owner can send a signal to the relay to cut
off the vehicle power supply. The microcontroller processes the GPS and IMU data and transmits it to the user via
Wi-fi or GSM module. A visual studio C# interface on PC and Android environment interface on smart phone was
programmed to process GPS and IMU data. The location information data of vehicle was saved as a text file. To
transfer this information to Google Earth, the text file was converted to Keyhole Markup Language (KML) format.
Google Earth interprets KML file and shows vehicle’s location on the map. Figure 5 shows the external view of
hardware implementation. The system was designed to be powered by the vehicle 12 voltages of battery via 7805
IC.
Figure 5. Hardware implementation of proposed embedded system
3. IMU AND GPS INTEGRATION OVERVIEW
IMU and GPS are integrated in the processing engine to derive the navigation solution of the system.
Loosely-coupled (LC) integration scheme is applied in this research due to its simplicity. Extended Kalman filter
(EKF) is employed as the main estimator for data fusion. The integrated architecture is shown in Figure 6. The raw
data provided by IMU is firstly decoded to obtain angular rate and specific force, those measurements are then
processed by an INS mechanization for a navigation solution in a local-level frame. The GPS receiver provides
position and velocities in the local level frame (latitude, longitude and ellipsoid height) and then send the solutions as
measurement update to the EKF. By comparing the navigation solutions provided by INS mechanization with those
solutions provided by GPS processing engine, those navigation states can be optimally estimated.
Figure 6. General loosely-coupled (LC) IMU/GPS integration schematic
For EKF, system and measurement models are firstly established based on (Titterton and Weston, 2004). With a high
sampling rate and seamless output, the INS is used to form system model. GPS measurements are used to build
measurement models.
The system model is derived based on error model of a strap-down inertial navigation system in a navigation frame.
“Psi” model is chosen to apply in the INS/GPS integrated system due to its advantages of simpler attitude error
dynamic equation. The detail of derivation can be seen in (Titterton and Weston, 2004). The discrete-time form used
for EKF is formed as:
xk   k 1;k xk 1  wk
(1)
𝑇
where 𝑥 = [𝛿𝑅 𝛿𝑉 𝛿𝜓 𝑏𝑎 𝑏𝑔 𝑠𝑎 𝑠𝑔 ]
is state vector, Φ𝑘−1;𝑘 is the state transition matrix from epoch k − 1 to k,
21×1
wk is system noise.
4. RESULTS AND DISCUSSION
A GUI was developed on PC based on visual studio C# to connect to moving part then obtain locations of vehicle
such as longitude, latitude for post processing. The obtained location was embedded in Google map to see current
address which vehicle is at. PC was connected to moving part via Wi-Fi module through IP address and Port number.
Objects of this paper include three parts. First is to get current location of vehicle then see that location on Google
map, second is to turn off the power supply of vehicle when vehicle is in emergency. Finally, a camera was embedded
in moving part. In GUI interface on PC, user can see the current situation where vehicle is in real-time.
4.1 Obtaining current location of vehicle and embedding the location in Google map
A GUI interface developed based on Visual studio C# environment on PC and Android environment on smart phone
to read GPS receiver’s data from moving part through Wi-Fi module is shown in Figure 7. IP
address-“192.168.16.254” and Port number-‘9999” of local wireless was generated and set configuration by Wi-Fi
module-RM04. PC will use this IP and Port to connect to moving part. The obtained location of vehicle was
embedded in Google Earth to see the current address which vehicle is in.
a) An interface on PC
b) An interface on smart phone
Figure 7. A GUI interface used to obtain current location of vehicle
Figure 8. Google Earth showing the location of the vehicle
Google Earth was used for tracking and viewing the state of the vehicle. The received data was processed and saved in
text file by a Visual studio C# program. This text file was exported to a KML file that is compatible with Google Earth
software. Hence, Google Earth will show the location of the vehicle on the map as shown in Figure 8.
4.2 Remote controlling turn off power supply of vehicle when in emergency
A LED was used to indicate the state of vehicle in emergency. In emergency, user can send a command to moving
part in order to turn off the power supply of vehicle. The operation of this was shown in Figure 9 with PC and in
Figure 10 with smart phone.
GUI interface
Moving part
GUI interface
Moving part
a) In safe status-LED CLOSED
b) In emergency status-LED OPENED
Figure 9. Remote turning off power supply of vehicle when in emergency by PC
a) In safe state-LED CLOSED
b) In emergency state-LED OPENED
Figure 10. Remote turning off power supply of vehicle when in emergency by smart phone
4.3 Remote monitoring vehicle in real-time
User can not only see current location of vehicle on Google map, user can also see the Webcam that embedded in
moving part. In this paper, this function was developed to see current location of vehicle under Web-camera as show
in Figure 11.
Figure 11. Camera function embedded in system for monitoring in real-time
5. CONCLUSIONS
In this paper, a low-cost vehicle tracking and monitoring embedded system including GPS/INS/Wi-Fi and camera
modules was proposed. The current location of vehicle was not only embedded in Google map but also monitored in
real-time via camera attached in moving part. With a GUI interface developed on PC based on visual studio C# and
Android on smart phone, user can easily view the current location and status of vehicle in real time or analyze the data
for post processing and cut off power supply of the vehicle when in emergency.
References
Bilgic, H.T., and Alkar, A.Z., 2011. A Secure Tracking System for GPS-Enabled Mobile Phones. Proceedings of
the 5th International Conference on IT&Multimedia at UNITEN, Malaysia,
Dinkar, A.S., Shaikh, S.A., 2011. Design and Implementation of Vehicle Tracking System Using GPS. Journal of
Information Engineering and Application, 1(3), pp.1-6.
Montaser, N.R., Mohammad, A.A., Sharaf, A.A., 2012. Intelligent Anti-Theft and Tracking System for
Automobiles. International Journal of Machine Learning and Computing, 2(1), pp. 88-92.
Titterton, D.H., and Weston, J.L., 2004. Strapdown Inertial Navigation Technology (2nd Edition). The Institution of
Electrical Engineers.