Application of IoT in Monitoring and Improving Automobiles

This document discusses the application of IoT in monitoring and improving automobiles. It explores the integration of IoT with artificial intelligence to facilitate real-time monitoring with greater accuracy. The document covers the sensors used, data analysis methods, and AI calculations applied for efficient and intelligent monitoring. It also discusses the use of IoT in improving theft protection, vehicle restoration process, fuel range measurement, and air pollution monitoring in automobiles.

NAME: PRANEETH.MULA
STUDENT ID: 11669192
SUBJECT: ITC 560 (INTERNET OF THINGS) ASSIGNMENT NO: IOT RESEARCH
REPORT – MILESTONE 2
LECTURE’S NAME: MALKA N HALGAMUGE

Literature review:
Application of IoT has an important role to play in monitoring of automobile. However, the
integration of IoT with artificial intelligence is aimed at improving this monitoring system to
facilitate real-time monitoring of automobile and with greater accuracy [1]. Information that
is obtained from this automobile is collected through different sensors attached to IoT
devices. Once data is gathered from these sensors they are required to be analyzed properly to
collect intelligence from these data and obtain different information about the automobile,
which is important from an analysis point of view. Hence, the proper method is required for
acquiring and analyzing these data properly. In order to collect data, the authors have
considered speed sensor, pressure sensor that includes pressure and cooperation, vibration
sensor, temperature sensor, emission sensor, GPS coordinates sensor and fuel level indicator
sensor. Data from these sensors are then collected through the OBD-II devices, which are
integrated with raspberry pi. Data after being processed in this system, it is then stored in the
cloud. Now in analysing these further in the cloud people intelligent algorithmic required
gathering intelligent information from this stored data. The authors have considered various
AI calculation for this purpose. Two important AI calculation that the authors have applied is
KNN calculation and naive bias calculation. Now if any issues are found during data analysis,
an alarm is sent to the consumers based on the calculation, which makes this process efficient
and intelligent.
Improving the theft protection of automobile have been one of the key concern of applying
IoT in the automobile industry. The authors in this article have proposed a device that is
designed with microcontroller and GPS receiver, GSM magnetic sensor transfer and mercury
sensor. GPS sensor for the GPS receiver collect coordinates of particular automobile and send
those data to microcontroller [2]. The microcontroller after processing the data send it to the
website, which displays the result through graphs on mobile applications. As GPS receiver

shares the coordinate position of the automobile in real-time and it is then processed with
microcontroller to offer accurate information about the position of the car hence this increase
the safety of the automobile and makes it difficult to steal the car without acknowledgement
of the owner.
That has provided a model for making the process of vehicle restoration process easy and
effective for average consumers [3]. The model is based on Diagnostic trouble codes that are
associated with the emergency engine. The model consists of various sensors such as speed
sensor, pressure sensor that included pressure and cooperation, vibration sensor, temperature
sensor, emission sensor, GPS coordinates sensor and fuel level indicator sensor. Data about
any issues that are associated with the car is recorded through obd2 device, electronic control
unit or ECU and dashboard camera attached to the smart vehicles. This data then stored in the
cloud for processing and offer insight about this data such as the procedure to manage issues
to the consumers so that they do not need to be dependent on others to resolve the issues
related to their vehicles.
The authors have proposed for applying it in measuring fuel range and gasoline rate area. A
tank level sensor is attached to the vehicle and it helps in determining gasoline level and
allows the user to set the preferred rate for fuel charge. Based on the information the model
offers direction for identifying fuel station and this information is displayed on Android
mobile application [4]. Communication between the car and gas station is done through RPi
Bluetooth. This model is aimed at providing the best strategy for the consumers to save their
time and cost for fuel consumption based on their preference.
Air pollution from the car has been a significant issue in recent years. Hence, smart
monitoring tool is required to tackle this issue. The authors here have proposed for a lot based
smart monitoring tool that helps in determining the level of pollution [5]. This model

integrates a sensor that is capable of measuring the quality of air. This sensor continuously
monitors different types of emissions from a particular vehicle and send this information to
Arduino through an analogue to digital converter. This information is then provided to
Raspberry Pi, which is an important part of this model. Information is stored in the cloud for
better accessibility. This information about emission is then measured and analyzed in detail
to identify the percentage of various contaminant present in the emission from a particular
vehicle. it is capable of offering insight to the consumer about their contribution to the air
pollution through their vehicle.so it will help them to reduce pollution by intelligently
monitoring their vehicle and reducing consumption of those fuels that are responsible for
degrading Air quality and creating air pollution.
Pollution through car is increasing vehicle manufacturers is looking for some alternative
solutions that reduce air pollution and enhance the quality of vehicles as well. Hence, there is
an effort to make vehicles energy efficient and intelligent at the same time. In order to
achieve this aim the authors have proposed for integration of IoT and big data in automobile
industry. As data that is collected from various IoT sensors which is not structured hence
traditional data analysis method is not efficient for analysing the state in addition to that the
data that is collected from it sensors if not only huge in volume but also huge in frequency
which demands an intelligent data analytic solutions for processing of this data. Hence, the
authors have proposed for big data Technology that is an advanced analytics tool [6]. It is
capable of analysing data that is not structured and huge in volume. As proper analysis of
collected data from the sensors is important for IoT applications, it is extremely important to
ensure quality in Data Analytics too as intelligence is only gathered from this collected data.
If the processing of the data is not proper, that application or IoT is not proper as well.

Requirements of the project:
With analysis of the existing literature, following requirements are identified in this context:
 Analysis of data security issues for IoT devices
 Design proper algorithm to provide data authentication
 Review of data authentication algorithm
 Evaluation of proposed algorithm with respect to other data authentication algorithm
suggested by previous researchers
 Propose best algorithm for data authentication
Problem statement
Although the application of IoT in smart vehicle Technology has an important role to play, it
is still important to ensure that their application is secure as the applications collect data
including vehicle position and hence it is important to ensure that data collection process is
not only proper, it is secured too. Hence, the security of data in the IoT network is an
important aspect, which needs proper analysis, and the proper mechanism is required for that.
Hence, a data authentication algorithm needs to be designed in this context.
Now authentication of in IoT network is an important requirement to ensure that data is
secured. However, while designing an authentication mechanism, especially in an IoT
environment, it is important to note that a sophisticated mechanism for data security is not
applicable in this context as it might require powerful computing resources, which is an
important constraint for IoT applications. Hence, in this context, an authentication
mechanism should be designed such that it is light on resources, yet secured enough to

provide data security. This mechanism should also ensure data authentication for securing
IoT applications.

References
[1] James Manyika Michael Chui Brad Brown Jacques Bughin Richard Dobbs Charles
Roxburgh Angela Hung Byers "Big data: The next frontier for innovation competition and
productivity" in McKinsey Global Institute May 2011.
[2] J. Cui, X. Wang, "Research on Google map algorithm and implementation", Journal of
Information and Computational Science, vol. 5, no. 3, pp. 1191-1200, May 2014.
[3] M.L. Han J. Lee A.R. Kang S. Kang J.K. Park H.K. Kim "A Statistical-Based Anomaly
Detection Method for Connected Cars in Internet of Things Environment" Internet of
Vehicles-Safe and Intelligent Mobility vol. 9502 pp. 89-97 Nov 2015.
[4] M. Amarasinghe S. Kottegoda A.L. Arachchi et al. "Cloud-based Driver Monitoring and
Vehicle Diagnostic with OBD2 Telematics" Advances in ICT for Emerging Regions (ICTer)
2015 Fifteenth International Conference Aug 2015.
[5] Sheenu Chhabra Gajendra Tyagi Ankit Mundra Nitin Rakesh "Location based coordinator
election algorithm in distributed environment" Computer and Computational Sciences
(ICCCS); IEEE pp. 183-188 2015.
[6] Malintha Amarasinghe, Sasikala Kottegoda, Asiri Liyana, Arachchi Shashika, H. M. N.
Muramudalige, Dilum Bandara, Afkham Azeez, "Cloud-based driver monitoring and vehicle
diagnostic with OBD2 telematics", 2015 Fifteenth International Conference on Advances in
ICT for Emerging Regions (ICTer).