IEEE Paper: https://ieeexplore.ieee.org/abstract/document/7789886/

1. A Low-cost IoT Application for
the Urban Traffic of Vehicles,
based on Wireless Sensors using
GSM Technology

2. Problem
Urban traffic congestion is a burning issue in many
cities due to growth of vehicles in use.
Which results in:
• High amount of accidents
• Imminent road violence
• Increased air pollution
• Increased noise pollution
• More fuel consumption

3. Cont
To overcome these traffic related problems an
application required which
– Observe Real time flow
– Enhance simulation of traffic
– Focus on traffic trends

4. Solution
1. Implemented a low-cost wireless application.
2. Supported on a distributed multilayer model.
3. 2 arduino in master-slave mode are used.
4. A laser based detection sensor used
5. GSM module used
6. Mining Techniques being applied

7. Functional Software
Requirements
• Web application, which records in the database
the count of vehicles.
• Web application that allows the user to observe
traffic in real time.
• Pentaho tool used for applying analysis on data.

9. Software
Architecture
• Software Architecture has
been divided into three
subsystems, having specific
functions and interacting with
the database.
• The first subsystem is a
Web application receiving
data, which is developed in
PHP and communicates by
means of the HTTP
protocol.

10. Software
Architecture
• The Second subsystem
monitors that what has been
developed in PHP and uses the
Laravel Framework that
implements three-tier
architecture.

11. Software
Architecture
• The last system is a data
mining process, which
improves system performance
monitoring by means of
Pentaho.
• Pentaho prepares data
integration, and blends data to
create a complete picture of this
issue that drives actionable
insights.
• This platform delivers accurate,
analytics-ready data to users
from a monitoring device
source.

12. Data mining and Business Intelligence
• For detailed information about the behavior of the
traffic at the study site, the technological module
Business Intelligent platform of Pentaho has been
applied (i.e. BI server) that allows to work with
cubes and multidimensional databases.

13. Star schema to represent behavior collected
by sensors.
This figure indicates
the Star model of the
multidimensional
database used. All
data collected during
the two week period
of our study were
recorded in the
Mysql DBMS.
Afterwards, these
data were copied and
transformed to the
multidimensional
Postgres DBMS.

14. Functionality Tests
• Testing revealed that the functions of the software
are operating, the inputs were accepted and that
there has been a correct output.
• Two agile methodologies as Scrum and Xtreme
Programming (XP) were combined.
• Scrum is responsible to the planning,
implementation and documentation of the project.
• While, XP focuses on the coding of software for
the experiment.

15. Development
• Development divided into three iterations
• The methods used were:
– Test-driven development (TDD), which is a method of software
development in which unit testing is repeatedly performed on source
code;
– The incremental design which split a main problem into smaller
problems;
– The continuous integration, which main aim has been to prevent
integration problems. In this last phase, several units for each of the
iteration tests were carried out using Scrum.
• The PHP-Unit tool of Laravel Framework has been used to
generate necessary testing.

16. End Product

17. Statistical Validation
• A statistical approximation has been used to the
number of vehicles that pass by.
• We have used the Poisson distribution, which is
applicable to random events that occur over
time.
• Then we applied the Exponential distribution
that models the elapsed time between two
consecutive events modeled by the Poisson
distribution, and determined its Probability and
Density functions.

18. Results obtained by Data mining
Percentage of flow by lanes.

19. Hourly flow illustrate per hours/ lanes.

20. Linear dispersion per day and per road.

21. Hourly flow recorded in lanes with different weather conditions.

22. Future Work
Focus on improvement of:
•Detection algorithm
•Classify vehicles according
to height, size & weight etc

23. Conclusion
This system evaluate a classic problem of cities with
a classically high traffic density.
Benefits & Strengths are:
•monitoring traffic in normal conditions
•congestion traffic even in different weather
conditions
•Inexpensive ($200/device)

24. Conclusion
System also contains a mining technique:
•extraction of meaningful information from huge
databases
• allows users to make predictions that solve
problems associated with urban traffic congestion.
Helpful for:
•researchers,
•teachers and students,
•Traffic Division authorities to propose strategies to
redistribute the vehicular circulation