International Journal of Science and Engineering Applications

Volume 8–Issue 05,131-135, 2019, ISSN:-2319–7560

Web-based Clinic Management System (CMS)

Jibrin Muhammad Salisu Garba

Department of Mathematics and Computer Science Department of Mathematics & Computer Science
Sule Lamido University, Kafin Hausa. Sule Lamido University, Kafin Hausa.
Jigawa State, Nigeria Jigawa State, Nigeria

Abstract: In healthcare services, patient medical records are becoming large in size and the complexity of exchanging patient records
such as prescription detail, referral data, diagnosis status and appointment schedules between various clinic-units can be a problem
without a fully integrated system. Moreover, access to patient records requires privacy. Quite a number of works have been conducted
on healthcare services to address issues such as medical record inconsistency, lack of immediate record storage and retrieval and
paper-based approach. Consequently, this work tries to automate and enhance the clinical services of Sule Lamido University Clinic
by developing a web-based application. The application will allow both the clinicians and patients to have access to electronic records
easily, which will, in turn, minimize the cost, difficulties, and ineffectiveness of working with patients’ records manually and to
enhance the benefits and profits in running the clinic services. It can be used in decision making as it provides complete, reliable,
accessible and understandable information pointing to the clinic progress and shortcomings. Initially, the problems of the current
system were identified, the requirements were however specified and analyzed. Model of the system was designed and implemented
using SDLC and finally, the system was tested and validated. The results revealed that the system complies with the specified
requirements. Hence, the objectives under which the system is defined were achieved.

Keywords: CMS, Clinic, healthcare, HMS, management, System, information system, SLU

records, inventory stocks and data of other sources. As the

1. INTRODUCTION complexity in healthcare services increases, healthcare
Over the years, a wide range of literature has revealed the
practitioners find it difficult to manually exchange patient
roles being played by Information System (IS) in healthcare
information from one file to another and from one healthcare
services. [3] defines information systems based on two terms;
practitioner to another. Hence, some among the major
these are information and system. In the process of advancing
problems include; lack of immediate information storage and
the idea, information is an analyzed data, while System is a
retrieval, poor preparation of accurate and prompt reports,
collection of a finite set of elements joined together to’
lack of prompt updates, Error prone manual calculation.
achieve objectives. More often than not, information systems
normally consist of smaller systems known as subsystems, In this paper, a web-based application for managing the
which all function towards ensuring the efficacy of the large services of Sule Lamido University Clinic is developed to
systems [7]. deal with the above-mentioned problems. The rest of this
paper is organized as follows; the related works are discussed
Significant improvement in clinical workflow, administration
in section 2. The proposed clinic management system is
as well as revenue enhancement are some among the benefits
discussed in section 3. The conclusion and future work are
that outweigh the challenges of Information System in
discussed in section 4.
healthcare industries. Furthermore, another key thing to
remember is access to clinical information; electronic access 2. RELATED WORK
to medical records helps clinicians to save time and an Tremendous efforts have been made to address problems in
enormous amount of resources. Thus, IS provides a complete, healthcare industries, and various researches have been
reliable, accessible and understandable information in a timely embarked to provide solutions to the existing problems. They
manner as well as in the effective management of patient employed different approaches and tools for requirement
medical records [4]. analysis, project design and implementation as steps towards
Consequently, the need for effective IS in healthcare services enhancing the effective processes needed for a modern
is considered substantial since it depicts organizational healthcare system. As raised by [2], healthcare information
performance which in turn helps in predicting the future of systems are developed to meet the following goals: improve
possible challenges and at the same time provides appropriate quality of care, reduce organizational expense, and produce’ a
solutions that can be built with streamlined operations towards data stream for electronic billing. The CMS meets these goals
the enhancement of proper administration and control over the through workflow automation, connectivity, and consistent
untimely threats. data sharing.

The CMS is an integration of patient information systems that In research projects conducted by [8] and [9], there were no
captures and stores demographic, financial, and medical functionalities such as online consultation and report
information from ancillary services such as registration, generation. However, the systems (mentioned above) need to
billing, lab, radiology, pathology, pharmacy, and be adjusted to comply with current requirements needed in
transcription. The CMS also includes the network that links modern healthcare services. In view of this, functionalities
these systems, databases, interfaces, physician’ order entry, such as online consultation, appointment scheduling,
electronic communication systems, and the clinical diagnosis manager, report generator are added to the new
workstations [2]. system.

Patient medical records accumulate during the clinical Hospitals and clinics can be regarded as organizations based
operations, information such as records of patients, treatment on high technology and information’ intensive processes.

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Such organizations are not hierarchically structured overseen by Pharmacist. The administrative section handles
bureaucracies but are often based on democratic control data processing services. Such services are being managed by
mechanisms with institutionalized stakeholder influence in assistant data processing officer and clerical officer using file
decision processes. It is also expected’ that health care processing approach. Therefore, with the ill-equipped
budgets and funding will depend significantly on the Information System, the stock cannot be managed properly.
sophisticated patient and diagnosis classifications. The use of Most of these problems can only be addressed if a proper
IT in diagnostic and treatment’ processes will add to the Information System is developed.
development of networks of clinical, hospital and healthcare
processes. 3. THE WEB-BASED CLINIC
A considerable amount of literature has indicated that; MANAGEMENT SYSTEM
healthcare management is a growing profession with CMS is designed for both patients and practitioners. It will
increasing opportunities in both direct and non-direct care allow patients to create an appointment, print appointment
settings. [9] similarly opined that direct-care settings are those card, generate medical reports, search for health tips, view
organizations that provide care directly to’ a patient, resident doctor’s profile, send emergency reports and chat with doctors
or client who seeks’ services from the organization. Non- online. The system will, however, allow practitioners to
direct care settings are not directly involved in providing’ care confirm, edit or cancel patient appointment request, diagnose
to persons needing health services, but rather support the care patients, prescribe medicines to the patient, manage inventory,
of individuals through products and services made available to manage both patient and clinic staff records. As a step toward
direct care settings. integrating the clinic operations, the proposed system
composes of various modules, which are dependent on one
Sule Lamido University clinic is currently operating
another. The data flow between subsystems is illustrated in
manually. Its various services include; patient consultation,
Figure 1. The sequence diagram of CMS appointment module
resuscitation and admission for observation during working
is shown in Figure 2 and Use case diagram of CMS is shown
hours, follow-up for hypertensive patients, treatment of minor
in Figure 3.
trauma and counseling with medical issues, patient treatment
services such as wound dressing and bandaging. The Clinic
has full stocked pharmacy for provision of drugs and is being

Figure 1: Level one DFD of CMS

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Volume 8–Issue 05,131-135, 2019, ISSN:-2319–7560

Figure 2: Sequence diagram of CMS Appointment Module

Figure 3: Use case diagram of CMS

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Volume 8–Issue 05,131-135, 2019, ISSN:-2319–7560

Table 1. The programming languages used in the system implementation

Programming Language Purpose Environment for testing
Hypertext Pre-Processor (PHP) Servers-side scripting Web browser and XAMPP server
JavaScript GUI behaviors and alerts Web browser
AJAX HTTP requests Web browser and XAMPP server
Hypertext Markup Language (HTML) Page structure Web browser
Cascading Style Sheet (CSC) Presentation and styling Web browser
Structured Query Language (SQL) Database queries Web browser and MySQL DBMS

3.4 Pharmacy and Inventory Module

The database of this application is implemented using This acts as a medicine store, where medicines are kept.
MySQL. It is an incredibly popular and powerful Relational Patient from observation units is sent to the pharmacy for
Database Management System (RDBMS) that allows the collecting medicines. There is a waiting panel for patients to
creation of. MySQL is an open’ source relational database wait while another patient is being attended. The module
management system (RDBMS) that uses Structured Query keeps track of the pharmacist who offers the medicine, the
Language (SQL), the most popular language for adding, patient who collects the medicine, date and time for the
accessing, and processing’ data in a database. MySQL is a medication. The module also includes a sub-module for
true multi-user, multi-threaded SQL database server [12]. prescribing patient during medication. It has a panel for
adding and updating medicines if in case there is a need for
PHP is one of the programming language used in designing any of such operations.
the program. Hypertext Pre-Processor (PHP) is a server-side
scripting language, usually used to create web applications in 3.5 Online Consultation Module
combination’ with a web server, such as Apache. PHP can This module acts as a messaging system where both patient
also be used to’ create command-line scripts akin to Perl or and doctor discuss health-related issues in real time. It,
shell scripts, but such use is much less common than PHP’s however, provides a panel which shows active users online to
use as a web language [12]. The reason why PHP is used, indicate whether the user is available or not.
because PHP is free, as there is’ no ’cost to develop in and run
programs made with PHP. PHP is compatible with the leading
web servers: Apache HTTP Server for Linux/Unix and
Windows’ and Microsoft Internet Information Server. It also
works with several’ lesser-known servers. Specific web server
compatibility with MySQL is not required since PHP will
handle all the dirty work. There are other programming
languages used such as JavaScript, SQL, HTML. The
remaining details can be seen in Table 1. The modules that
make up the system are discussed in the subsections below.

3.1 Appointment Scheduling Module

This module is designed to have two sections (patient section
and staff section), each of these sections is only accessible to
the authorized user; patient accesses patient section and staff Figure 4: System Interface
accesses staff section. The patient section allows the patient to
send an appointment request, while the other section of the 4. ACKNOWLEDGMENTS
staff provides the detail of each patient request, the CMS is designed and developed to automate the manual
functionalities of confirming, editing and deleting the patient system of Sule Lamido University Clinic and oust the manual
appointment request. If a patient appointment is confirmed, method of record/file keeping. Both the practitioners and
then he can print his visiting card instantly. patients will find this system useful, to aid in their
computerization. Thus, the system will promote effective,
3.2 Observation and Diagnosis Module efficient and quality services. Clinic Management System
After the appointment is confirmed, then the patient record
(CMS) currently focuses only on the relationships between
goes to the observation module where he will be diagnosed by
patients, receptionist, physicians, and pharmacists. It is part of
a doctor. However, this module saves the diagnosis record.
the future plan for this project to incorporate other healthcare
After the diagnosis, the patient record may be sent to either
facilities and professionals, such as laboratory technicians
admission module for the patient’s admission, pharmacy
who perform, report tests and analysis requested by
module for medication or referral module if the patient is to
physicians. However, another plan is to enhance the system to
be referred to a different hospital. Observation module is only
investigate whether our Clinic and Pharmacy modules can be
accessible by staff.
interfaced to applications supplied by pharmaceutical
3.3 Patient Referral Module companies that provide information on medications and
This module deals with the information sent from the dosages. In addition to that, the future plan extends to develop
observation module for patient referral. It is designed a mobile phone application that will work with the system
purposefully if the patient is needed to be referred to another over the internet network.
clinic or hospital. Here in this module, other information like
hospital facility to be referred and the result of the diagnosis is
provided.

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5. ACKNOWLEDGMENTS Management Review. Retrieved from

Our thanks to the Sule Lamido University Clinic for and other http://findarticles.com/p/articles/mi_qa5362/is_200501/ai
staffs of the university who have contributed towards the _ n21371132/ on March 4th, 2017
development of this system. [7] Babu, K.V.S.N.J., & Sekhar, B.M.R (2012). MIS. Vs.
DSS in Decision Making, Global Journal of Management
6. REFERENCES and Business Research, Volume 12.
[1] Almasri R. & Navathe B. S. (2010). Fundamentals of
[8] Basir, A. A. B. (2015). Darul Ridzuan Clinic
database systems sixth edition. Addison-Wesley, USA.
Management System (Doctoral dissertation, Universiti
ISBN-13:978-0-136-086208
Malaysia Sabah).
[2] Erstad L. (2007). Analyzing Computer-based patient
[9] Lau, F., Price, M., & Keshavjee, K. (2011). Making
record: A review of literature; Journal of Healthcare
sense of health information system success in Canada.
Information Management Vol. 17 No. 4
Healthc Q, 14(1), 39-46.
[3] Kumar, P. K. (2006). Information System-Decision
[10] Lingham, L. (2006). Managing a business/ Management
Making IndianMBA. Retrieved from
information system. All Experts. Retrieved from
http://www.indianmba.com/Faculty_Column/FC307/fc30
http://en.allexperts.com/q/ManagingBusiness1088/manag
7.html on April 2, 2017
ement-information-system.htm on March 4th, 2017
[4] Besson, P., Rowe, F. (2012). Strategizing information
[11] O’ Brien, J.A.,& Marakas, G.M. (2007). Management
systems-enabled organizational transformation: A trans
information systems-10th edition. McGraw-Hill/Irwin,
disciplinary review and new directions. Journal of
The McGraw-Hill Companies.
Strategic Information Systems, 21, 103–124
[12] Suehring S. (2009). PHP6 and MySQL6 bible. Wiley
[5] Hosseini, J. (2005). Strategic Technology Planning for
Publishing, Inc., Indianapolis, Indiana ISBN: 978-0-470-
the e-Commerce Enabled Enterprise. International
38450-3
Conference on Information Technology: Coding and
Computing (ITCC’05). [13] S.K, J. (2009). System analysis and design. New Delhi,
India: S.K & Sons.
[6] Jahangir, K. (2005). Improving organizational best
practice with information systems. Knowledge

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Real-Time Video Display System in Articulated Vehicle for

Road Safety Enhancement

Timothy Gambo Elijah E. Omizegba Alfred Baamani Ba’ams

Department of Electrical and School of Engineering and Department of Electrical and
Electronics Engineering Engineering Technology Electronics Engineering
Modibbo Adama University of Abubakar Tafawa Balewa Modibbo Adama University of
Technology University, Bauchi, Bauchi State, Technology
Yola, Adamawa State, Nigeria Nigeria Yola, Adamawa State, Nigeria
Bauchi State, Nigeria

Abstract- Nowadays, auto crashes are being recognised relatively slow, overtaking it is a problem because of its size and
as a major public health problem; with higher fatalities in third the inability of the driver to see ahead of it. Moreover, Bhumkar
world countries. Wrongful overtaking has been one of the major et al. (2012) showed that wrong overtaking is the second highest
causes of road traffic accidents (RTAs) especially that involving leading cause of road accidents. As at the year 2013, in Nigeria,
large sized vehicles (LSVs) or articulated vehicles. Driving behind 6,450 people lost their lives in road accidents (Adedokun, 2015)
such a vehicle has being a nightmare to most drivers especially on and 183, 531 people were injured as a result of RTAs between
a single – lane highway. Even though the movement of LSV is 2009 – 2013, (Agbokhese et al.2013).
relatively slow, overtaking it is a problem because of its size and According to Federal Road Safety Commission, FRSC (2015),
the inability of the driver to see ahead of it. However, Real-Time there were a total of 21,199 road accidents in 2013 out of which
Video Display System (RTVDS) in articulated vehicle for road 1,495 involved articulated vehicles such as tankers, trailers or
safety enhancement provides a solution to such problems; by buses which represent 7.05 % of the accidents. In 2014, a total of
providing overtaking drivers with visual information on the state of 16,779 vehicles were involved in crashes, out of which 998 were
the road ahead of the articulated vehicle so as to assist the driver tankers or trailer-related, representing 5.94 % of the total crashes
in deciding on whether to overtake or not. Such information may that year. As at first quarter of 2015, a total of 1,193 vehicles
also reduce the risk of accidents caused by sudden braking or caused Road Traffic Crashes (RTCs) out of which 49 were
animals crossing the road. The system basically consists of a articulated vehicles, representing 4.11 %, (FRSC, 2015).
digital camera mounted in front of the truck, a control unit Researchers and vehicle manufacturers have come up with
(raspberry pi - RPi) and an exterior display unit located behind the different strategies in an effort to curtail RTAs and to ensure
truck. Shaky images captured by the camera were stabilized using safety on the road. Some safety mechanisms currently used in
Optical Flow algorithm of video stabilization before being vehicles include (Kannan et al., 2010):
displayed. The design was implemented using Python as the
programming language. Results obtained from the design show that i. Adaptive Cruise Control
the system is capable of producing stable video images required for
decision making before overtaking. Hence, reducing the rate of ii. Collision Avoidance System
RTAs associated with LSVs if fully developed.
iii. Lane Departure Warning System
Keywords: Auto Crashes, Articulated Vehicle, Road Safety,
Raspberry Pi, Video Stabilization, Python iv. Driver Drowsiness Detection System

1.0 INTRODUCTION v. Night Vision Assistance Systems

vi. Visual packing and reversing aid

The total number of serious auto crashes has been on the
increase regardless of improvements in modern vehicular designs The idea behind this study is to reduce cases of accidents
and road network for driver safety. Record from World Health caused by poor decision before and during overtaking of
Organisation (WHO) shows that about 1.24 million people lose articulated vehicles by providing a system for monitoring
their lives in Road Traffic Accidents (RTAs) annually and another activities on the road ahead of such vehicles. This is to be
20 – 50 million are injured (WHO, 2015); with higher fatalities in achieved by capturing and displaying (in real-time) the image of
developing countries. Record also revealed that without check, the road ahead of the articulated vehicle on a display unit
about 1.9 million lives could be lost by the year 2020. These high mounted behind the truck. This visual information can be
numbers of human deaths and injuries as well as losses in utilised by the overtaking driver as a guide for decision making
country’s economy show how vital it is to deal with this menace. before overtaking. Figure 1 shows the conceptual diagram of
RTVDS.
Report by Mutya and Rudra (2015) indicated that 60% of
deaths in RTAs were associated with Large Sized Vehicles
(LSVs) such as buses, trucks and mini buses. Driving behind such
a vehicle has being a nightmare to most drivers especially on a
single – lane highway. Even though the movement of LSV is

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Server or Host Vehicle on the rear vehicle). These algorithms provided a new mechanism
Display Unit for avoiding accidents due to overtaking by mutual
communication between them. The safe range space around the
vehicle was considered to be an ellipse shaped boundary. The
algorithm refrained to allow overtaking if there was a significant
amount of overlap between the ellipse regions of the vehicle.
With the simulation result, it was shown that algorithms dynamic
Proximity Sensor Position implementation in real-time scenario would potentially reduce the
Client or Beneficiary Driver
Front Mounted Camera Unit number of accidents occurring due to overtaking. However, this
Figure 1 Conceptual Diagram of Real-Time Video model is still in the development stage and requires more work
before it can be implemented on real roads.
Display System
In an effort to warn or alert other drivers that a collision may
2.0 RELATED WORK ON ROAD take place, Mutya and Rudra, (2015) came up with a safety
mechanism for accident prevention during overtaking. The
TRAFFIC SAFETY system consists of proximity sensors, a camera, microcontroller
and a display unit for sensing, capturing, image processing and
Telematic technology, which is the art of processing and displaying of the processed images respectively. This system
transmitting computer data over long distance, was introduced as also employed mechanical switches and indicators as human
vehicular digital video recorder system, for the recording of driver’s controlled sub-system. The design was cheap and gave the
behaviour during journey (Lin and Wang, 2010; RoSPA, 2013). An required result on road safety. However, the manual operation
embedded microcontroller was employed as the hardware system. It of the switches is a distraction which a driver may forget to
operated online and in real-time, it also supports an offline video data switch ON or give a wrong command which may lead to a
viewer. The video data recorder was waterproofed to prevent it from serious problem. Thus, this work unveiled a cheap and
being tempered with. Results from the application of this system automated model that will guide drivers in their decision making
indicated that rate of accident was reduced by 20 % and rate of during overtaking of LSVs using Raspberry pi platform.
specific unsafe driving behaviours were reduced up to 82 % (RoSPA,
2013). Information from the offline video viewer can be used to
reveal facts on the status of the vehicle when accident occurred much 2.1 Related Work on Image Stabilization
like those of air craft flight data recorder. Other than safety, the device
also increased savings in maintenance cost. The major obstacles to Video images captured from moving vehicle consist of
the system were its installation and maintenance costs and lack of unwanted translations due to vibration from the vehicle engine
acceptance by drivers; other challenges were handling and analyzing and uneven nature of the road. Thus, image stabilization is
the data and ensuring that the technology was not used for negative required to compensate the frames and to avoid losing of any
assessments and punitive actions. useful information during image capturing. Various approaches
have been used for the stabilization of captured images. These
Similarly, on driver assisted systems, Kannan et al. (2010) can be broadly classified as (Rawat and Singhai, 2013):
proposed an “Intelligent Driver Assistance System” (I-DAS) for
alerting driver during critical situations, using an ontology modelling i. Mechanical stabilization
method (a method of modelling which interprets information in an ii. Optical stabilization
intelligent and decisive manner). The design was aimed at developing iii. Digital image stabilization
a system which focused on generating alert messages based on
context aware parameters such as driving situations, dynamics of the Both the mechanical and the optical methods were
considered as hardware techniques (Reddy et al., 2015).
vehicle, driver activity as well as environment. The parameter
representations, consisting of date/maintenance of the system were Mechanical stabilizer adopted gyroscopic sensor to stabilize the
managed in extensible mark up language, XML format while entire camera while Optical stabilization approach activated an
ontology modelling was applied for the interpretation of critical optical system to adjust camera motion sensor. On the other
condition. Simulation of the system also incorporated other related hand, the mechanical methods are not suitable for small camera
safety technologies such as Collision Avoidance System, Adaptive modules due to their bulk nature and cost associated with it.
Cruise Control, Drowsiness Detection System, and Parking Thus, image processing approach tries to smooth and
Assistance System, which generated warning and alert to driver compensate the undesired motions through digital video
continuously. Java framework was used for the simulation test bed to processes.
generate safety alerts in various driving conditions. Best, average and
Digital image stabilization (DIS) techniques, as opposed to
worst cases of the simulation were studied to determine the effective
mechanical or optical devices, are most preferable due to their
performance of the driving scenarios in different modes like day and
compact nature, fast response and lower cost (Naidu et al.,
night for single, 2-way and 4-way road scenario; the approach showed
2016). This technique uses feature tracking method to obtain
that the simulation can be implemented on all vehicles in real-time
camera motion path using suitable motion model and motion
scenario. However, this system lacks knowledge base on overtaking
compensation to stabilize the video. Generally, all digital video
situation.
stabilization algorithm consist of three stages (Lim et al., 2017):
Mounica et al. (2014) came up with “The Intelligent
i. Motion estimation (ME)
Overtaking Model for Reducing Road Accidents Based on
ii. Motion smoother (MS)
Animal Group Behaviour” by mapping the behaviour of Zoo
iii. Motion compensation (MC)
Planktons to that of traffic on the road; in which safe distances
were given high priority. Two novel algorithms were developed:
The flow of the process is shown in Figure 2.
the overtaking possibility check (OPC) algorithm (operating on
the front vehicle) and the overtaking (OT) algorithm (operating

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ME MS MC 3.4 Materials
Shaky Stabilized
video video Table 1 shows the list of materials used for the
Figure 2 Video Stabilization Process Flow implementation of the RTVDS system.

To achieve real-time video stabilization in Unmanned

Aerial Vehicles (UAVs), Lim et al. (2017), proposed “Real-
Time Optical Flow – based Video Stabilization for Unmanned Table 1 List of Materials
Aerial Vehicles” for fast video stabilization. The algorithm used
optical flow corner tracker detection for the key points matching, A Major Hardware Materials
hybrid mechanism for motion estimation and average window i Raspberry Pi 3 board
smoothing for motion compensation and image composition. ii Raspberry Pi camera module
The algorithm is capable of processing up to 100 frames per iii 3.2” Thin film transistor(TFT) raspberry Pi
second for all the 3 stages of the algorithm; making it suitable Liquid crystal display(LCD) module
for real-time video stabilization processes. iv Buzzer unit
v HC-SR04 Ultrasonic Sensor
Optical flow is the pattern of apparent motion of image vi Buck converter module
objects between two consecutive frames caused by the B Software Materials
movement of camera or object. It is a 2D vector field in which i Python Version 2.7
each vector is a displacement vector, indicating the motion of
ii OpenCV
points from first to second frames (Fleet and Weiss, 2005).
3.4.1 Implementation of Processing Stage
3.0 MATERIALS AND METHODS This is the backbone of the entire RTVDS system. A
raspberry pi 3 model B was used for the implementation of this
The implemented system consists of three basic stages which stage, the camera, LCD and other peripherals were connected
were powered by the battery of the host vehicle; using a 12V – and configured using the programming language, python.
5V buck converter as the regulator. These stages are: Input, Plate 1 shows raspberry pi 3 model B mother board. It is
Processing and Output stages as shown in Figure 3. basically a microcontroller with small field programmable
gate array (FPGA) on the same chip. It is sometimes called
programmable system on chip (PSOC) or a credit card size
INPUT PROCESSING OUTPUT Linux computer used for simple programming (Deepa and
STAGE STAGE STAGE Parkali, 2016). One of the main advantages of using RPi is that
it makes design easy and compact. From Plate 1, the required
Figure 3 Block Diagram of the Basic Stages connections to the RPi were:

3.1 Input Stage i. Camera serial interface (CSI)

ii. General purpose input output
The input stage serves as the eye of the system. It consists of headers (GPIO)
a digital camera, which captures events on the road ahead of the iii. Micro SD card slot
articulated vehicle and feed the processing unit with real-time iv. 5V micro USB input power port
images of the events. It also incorporated three (3) proximity
sensors which detect(s) vehicle behind the server vehicle.

3.2 Processing Stage

The shaky and blurred images captured by the camera are
being stabilized and processed in this stage, the processing stage
consist of a microcontroller (raspberry pi - RPi) which executes
this function using its embedded codes and libraries. Its output
signal serves as input to the output stage.

3.3 Output Stage

This stage consists of a Thin Film Transistor (TFT) liquid
crystal display (LCD) unit and a Buzzer system; through which
the stabilized and processed images are being displayed and for
alerting of the host vehicle driver respectively.

Plate 1 Raspberry Pi 3 Model B Mother Board

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3.4.1.1 Configuration of the Raspberry Pi b. The Formatting Tool was Installed and run

Every Raspberry Pi requires an operating system (OS), c. “FORMAT SIZE ADJUSTMENT” option
which need to be installed, to enable it function as expected. was set to “ON” in the “options” menu
This is because the RPi does not come with an OS. The
traditional OS of the RPi is called raspbian operating system; d. The SD card inserted was then inspected to
it is contained in software called New out of box software ensured it matches the one selected by the
(NOOBS). NOOBS is an operating system manager that Tool
makes it easy to download, install, and set up RPi.
e. The “Format” button was then Clicked
3.4.1.1.1 Steps for the installation of NOOBS ii. The files contained in NOOBS zip file were
extracted and copied onto the formatted SD card
Materials used for the installation were:
iii. Raspbian OS was then down loaded from the
official website of RPi
i. Keyboard
(https://downloads.raspberrypi.org/raspbian_lat
ii. 32GB micro SD card
est) and installed onto the 32GB SD card
iii. Laptop
iv. The raspbian image was also written onto the
iv. HDMI Cable
32GB SD card using Win32Disk imager
v. USB Cable
v. The SD Card was then inserted in the micro SD
vi. 5V power supply
Card slot of the raspberry pi
The above materials were set up as shown in Plate 2; all
vi. After plugging the peripherals (keyboard, mouse
connected to the RPi.
and HDMI Display) the system was powered
using a 5V power supply unit

vii. The file system was expanded to the full length

of the SD Card

viii. After the expansion was carried out, the system

rebooted automatically and gave screen display
as shown in Plate 3; this shows that the OS was
successfully installed and that the RPi was ready
for use with other peripherals required for the
design.

Plate 3 Screen Display for Successful Installation of

Raspbian Operating System

Plate 2 Set up for the Installation of Raspbian OS

The following steps were taken for setting up of the RPi:

i. A 32GB SD card was inserted into a laptop via

the SD card reader.

The SD card was then formatted using the platform-

specific instructions listed below:

a. The SD Association’s Formatting Tool was

downloaded from

https://www.sdcard.org/downloads/formatter_4/eula_w
indows/

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camera module.

3.4.1.2 General Purpose Input and Output

(GPIO) header

Plate 4 Raspberry Pi Camera Module

3.4.2.1 Camera Module Configuration

The camera was configured and enabled using the following
Linux commands at the command line interface (CLI) of python
(using the available network signal):

Sudo apt-get update

Sudo apt-get upgrate

Sudo raspi-config

In addition, three (3) HC-SR04 ultrasonic sensors were used

as the proximity sensors, each with 1200 angle of coverage. As
shown in Plate 5, the HC-SR04 is an ultrasonic range finder with
Figure 4 Raspberry Pi 3 GPIO Header 4 terminals (Vcc, Trigger, Echo and ground). Commonly called
a transducer or transceiver, it works on a principle similar to
radar or sonar; which evaluates attribute of a target by
Figure 4 shows an alternative interfacing region on the RPi interpreting the echo to determine distance to an object. It
through which other electronic devices were interfaced with the consists of a transmitter, a receiver and control unit.
raspberry pi. For this work, this section was used for the
interfacing of the proximity sensors, the 3.2” TFT LCD display
and the alarm module with the raspberry pi. A library called
Python Library was then installed to enable the control of the
GPIO pins (https://pypi.python.org/pypi/RPi.GPIO).

This gives a gate way for interfacing with other electronic

devices by selecting the required GPIO pin(s) base on the
function of the component(s) to be use.

3.4.2 Implementation of Input Stage Plate 5 HC-SR04 Ultrasonic Sensor Module

A camera Rpi NoIR Module was used for the implementation The main advantage of ultrasonic sensor is that it provides
of this unit. It is a camera designed specifically for raspberry pi highest reliability in getting proximity and has lesser absorption
interface. It has a field of vision of about 56 degrees (Myklebust, than RF and IR frequencies (Vidhya et al., 2016).
2015), a full high definition (HD) recording capability
(Kaundaya et al., 2017), a resolution of 8MP and video 3.4.2.2 Implementation of the Sensor Unit
resolution of 1080p30, 720p60 and 640 x 480p30. The camera
was plugged to its dedicated camera serial interface (CSI) port The three sensors were connected together with their
on the raspberry pi via its 15pin ribbon cable. Plate 4 shows the respective pins to the general purpose input and output (GPIO)
header as outlined below:

a. Vcc to 5V supply
b. Ground to Ground
c. Trigger terminals to GPIO 21
d. Echo pins to GPIO 20, GPIO 19 and GPIO 6

However, each of the Echo pins were connected to the

GPIO header pins through 3.3V Zener diode, to protect the

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terminals from high 5V supply since the GPIO header are rated ii. The terminal was then lunched and
3.3V. Final Implementation was carried out on a dedicated PCB the following commands were executed:
before being connected to the RPi via a three input OR gate;
which was executed in software form. See Plate 6. Extraction of the drivers

tar xvf LCD-show-*.tar.gz

cd LCD-show/

This toggles the mode from HDMI to LCD display:

chmod +x LCD32-show./LCD32-show

iii. The RPi LCD was ready for use,

after system reboot.

Plate 6 Implementation of Sensor Unit on Printed 3.4.3.2 Alarm System

Circuit Board
For this work, a piezoelectric buzzer of single tone was
The sensor unit was moulted at the back used for the alarm system. See Plate 8. It alerts the driver of the
bomber of the host vehicle for the detection test at articulated vehicle that a vehicle is behind and may overtake. It
various distances to determine its performance. was installed inside the tractor cabinet of the articulated vehicle.

3.4.3 Implementation of the Output Stage:

As shown in Plate 7, a thin film transistor (TFT) RPi LCD
module was selected as the display unit for this work. Though
any display system with HDMI input can be use for this purpose
but this was used for the convenience of the prototype. It has a
screen resolution of 320 x 240. Advantages derived from using
the LCD include (Kumar and Reddy, 2016): Plate 8 Buzzer Module
i. Lightweight with few thickness The entire system is expected to be powered using the
ii. Less power consumption truck battery via 5V buck converter with a USB cable. However,
iii. Does not generate heat for the prototype, a power bank of 5V, 2.1A specification was
iv. It is less costing used as the power supply unit.
v. Have long life and wide operating temperature Finally, the various units were cascaded to form a
range complete circuit of RTVDS system. See Figure 5.

Plate 7: 3.2” TFT Raspberry Pi LCD Display Module

3.4.3.1 Configuration of the 3.2” TFT Rpi LCD

Module
Figure 5 Complete Circuit Diagram of Real-Time Video
This unit was configured by initial installation of the drivers of
the 3.2” LCD board; since the RPi OS came with only the HDMI Display System
display pre-installed drivers. The LCD module was plugged
directly on the GPIO header of the RPi through it 26 pin
connectors; then, the following procedures were carried out for the
installation of the drivers:

i. The drivers were downloaded

from(http://www.waveshare.com/w/upload/4/4b/LCD-
show-161112.tar.gz)

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3.5 Image Stabilization v. Finally, the new transformation was then

applied to the video.

To achieve the stabilization and processing functions, 3.6 System Prototyping

open source computer vision (OpenCV) library was installed.
This library is highly efficient, and known to work well with Having completed the design of the various units of
real-time applications. Though written in C++, it has many RTVDS, a prototype of the system was implemented on a toy
language interfaces include Python. Optical flow algorithm of truck as shown in Plate 9.
video stabilization was adopted for this work, using python
interface of OpenCV library
(http://www.docs.opencv.org/master/d7/d8b/tutorial_py_luca
s_kanade.html). This method of image stabilization was
selected for this work because it is simple and has high
processing speed; making it suitable for real-time applications.

The procedure to carry out the stabilization function is

described in the algorithm as shown in Figure 6.

Input Shaky video

Plate 9 Prototype of the Implemented RTVDS

4.0 RESULTS

Optical Flow Calculation 4.1 Proximity Sensor

Figure 7 shows the plots for the actual and desired
distances against numbers of readings taking as obtained from
the sensor unit
Camera Motion Estimation
5
4
Distance (m)

ACTUAL
Smoothing Camera Motion 3
RANGE
2
DESIRED
1 RANGE
Image Warping 0
1 2 3 4 5 6 7 8
. Number of Readings
Stabilized Output Video

Figure 7 Plots of Distances against Number of Readings

Figure 6 Flow Chart of Optical Flow Video
Stabilization Algorithm Sum error
Mean error (ME) =
Total number reading
The following steps describe the components of the flow
chart: 0.35
= = 0.04375
8
i. Transformation from previous to current
frame using optical flow for all frames was Percentage error is 4.4%
determined. The transformation consists of
only three parameters: dx, dy and da (angle). This error may be as a result of the roughness of the
Basically, a rigid Euclidean transform, no surface where readings were taken or error due to
scaling, no sharing. But for this work, da was parallax. However, this shows that the sensors are 95.6%
neglected since angular changes were not effective; thus meet the design range specification.
observed.
ii. The transformations were accumulated to get
the “trajectory” for x, y, at each frame.
iii. The trajectory was Smooth out using a sliding
average window; with 25 frames as applied
window radius.
iv. A new transformation was created such that
new_ transformation = transformation +
(smoothed trajectory – trajectory).

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4.2 Camera Output Figure 9 X Trajectory

Plate 10 shows the output image of the road on the LCD

display as captured by the RPi camera; with resolution of
3.15MP, equivalent of 2048 x 1536 pixels. Applying the Official
Highway Code (OHC) rules of overtaking, using rule 162 – 169
(www.highwaycodeuk.co.uk), the output is good enough to be
used by any driver for judgement before overtaking.

Plate 10 LCD Output Display on Live scenario

4.3 Image Stability

System stability data were converted from text file to
Excel before plotting; the Excel data were used for the
determination of the system stability using MATLAB
software for the plots. Figure 8 shows the plot of
transformation from previous to current frames before
stabilization. Figure 8 covers step (i) of the Optical Flow
algorithm for all the frames by providing dx and dy
parameters with da being neglected, since there was less
change in rotational movement in this work. The Figure 10Y Trajectory
clustered ripples of the plots correlate with the shaky
images captured by the camera due to uneven surface of The downward movement of the plots in Figure 9 and
the road. Figure 10 correlate with the forward movement of the
camera, as the vehicle was moving against images being
captured. Figure 11 reveals the final transformation
applied to the video with both dx and dy being smoothed
compared with the earlier plot of Figure 8.

Figure 8 Plots of Transformation from Previous to

Current Frames before Stability

Figure 9 and Figure 10 indicate the accumulated transformation

which yield X and Y trajectories at each frame for both originals and
smoothed versions of X and Y trajectories. For this work, + - 25 frames Figure 11 Smoothed Frame to Frame Transformation
was used as the smoothing radius. The blue indicates the original
trajectories while the red shows the smoothed trajectories for both X
and Y trajectory plots. These defined steps (ii) and (iii) of the algorithm.

The stability results indicated that the system is

capable of providing proving images without distortions

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using the Optical Flow algorithm, when the host vehicle Kalivaradhan, R. (2010). An Intelligent Driver
is in motion. With this, the beneficiary driver can get the Assistance System ( I-DAS ) for Vehicle
right information that will assist him during overtaking Safety Modelling using Ontology Approach.
scenario at real-time. International Journal of UbiComp (IJU), 1(3).
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using Raspberry Pi and Face Recognition.
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From the results obtained, a novel road safety 7
system for overtaking manoeuvre was implemented. (9) Kumar, A. Sunil and Reddy, P. . R. (2016). An
This system is capable of providing an overtaking driver Internet of Things Approach for Motion
with detail information on the state of the road ahead of Detection using Raspberry Pi. International
the articulated vehicle; for judgement on whether to Journal of Advanced Technology and
overtake or not. If fully developed in real-live scenario, Innovative Research, 8(19), 3622–3627.
loss of lives and properties as a result of road traffic (10) Lim, A., Ramesh, B., Yang, Y., Xiang, C.,
accidents especially those involving large sized vehicles Gao, Z., and Lin, F. (2017). Real-Time
will be greatly reduced; thus, contributing to improve Optical flow-based Video Stabilization for
safety on our roads as declared by WHO for decade of Unmanned Aerial Vehicles. Real-Time Image
action on road safety. Processing Manuscript. Retrieved from
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IEEE/ACM International Conference on
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Green Computing and Communications,
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GreenCom 2010, 2010 IEEE/ACM
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International Conference on Cyber, Physical
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and Social Computing, CPSCom 2010, 907–
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We, the Authors, especially want to acknowledge Dr Iliya Mugada, S., and Uttam, M. (2014). The
Tuku of School of Engineering and Engineering Technology of intelligent overtaking model for reducing road
MAUTEC Yola and Engineer Ahmed Tijani of AJISAT Nigeria accidents based on animal group behavior.
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