Introduction to IOT 22ETC15H
MODULE -5
IOT CASE STUDIES AND FUTURE TRENDS
5.1 INTRODUCTION
In this chapter, we discuss the application of IoT in connected vehicular systems. The use of
connected vehicles is increasing rapidly across the globe. Consequently, the number of on-road
accidents and mismanagement of traffic is also increasing. The increasing number of vehicles
gives rise to the problem of parking. However, the evolution of IoT helps to form a connected
vehicular environment to manage the transportation systems efficiently. Vehicular IoT systems
have penetrated different aspects of the transportation ecosystem, including on-road to off-road
traffic management, driver safety for heavy to small vehicles, and security in public
transportation. In a connected vehicular environment, vehicles are capable of communicating and
sharing their information. Moreover, IoT enables a vehicle to sense its internal and external
environments to make certain autonomous decisions. With the help of modern-day IoT
infrastructure, a vehicle owner residing in Earth’s northern hemisphere can very easily track his
vehicular asset remotely, even if it is in the southern hemisphere. In this chapter, we discuss the
importance and applications of IoT in the vehicular systems. Figure 5.1 represents a simple
architecture of a vehicular IoT system. The architecture of the vehicular IoT is divided into three
sublayers: device, fog, and cloud.
• Device:
The device layer is the bottom-most layer, which consists of the basic infrastructure of the
scenario of the connected vehicle. This layer includes the vehicles and road side units (RSU).
These vehicles contain certain sensors which gather the internal information of the vehicles. On
the other hand, the RSU works as a local centralized unit that manages the data from the
vehicles.
• Fog:
In vehicular IoT systems, fast decision making is pertinent to avoid accidents and traffic
mismanagement. In such situations, fog computing plays a crucial role by providing decisions in
real-time, much near to the devices. Consequently, the fog layer helps to minimize data
transmission time in a vehicular IoT system.
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, Introduction to IOT 22ETC15H
• Cloud:
Fog computing handles the data processing near the devices to take decisions instantaneously.
However, for the processing of huge data, fog computing is not enough. Therefore, in such a
situation, cloud computing is used. In a vehicular IoT system, cloud computing helps to handle
processes that involve a huge amount of data. Further, for long-term storage, cloud computing is
used as a scalable resource in vehicular IoT systems
Figure 5.1: Architecture of vehicle IOT
5.1.1 Components of vehicular IoT
Modern cars come equipped with different types of sensors and electronic components. These
sensors sense the internal environment of the car and transmit the sensed data to a processor. The
on-road deployed sensors sense the external environment and transmit the sensed data to the
centralized processor. Thereafter, based on requirements, the processor delivers these sensed data
to fog or cloud to perform necessary functions. These processes seem to be simple, but
practically, several components, along with their challenges, are involved in a vehicular IoT
system. Figure 5.2 depicts the components required for vehicular IoT systems
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, Introduction to IOT 22ETC15H
Figure 5.2: Components of vehicle IOT
• Sensors: We have already discussed how sensors play a crucial role in an IoT-based ecosystem.
Similarly, in vehicular IoT, sensors monitor different environmental conditions and help to make
the system more economical, efficient, and robust. Traditionally, two types of sensors, internal
and external, are used in vehicular IoT systems
(i) Internal: These types of sensors are placed within the vehicle. The sensors are
typically used to sense parameters that are directly associated with the vehicle. Along
with the sensors, the vehicles are equipped with different electronic components such
as processing boards and actuators. The internal sensors in a vehicle are connected
with the processor board, to which they transmit the sensed data. Further, the sensed
data are processed by the board to take certain predefined actions. A few examples of
internal sensors are GPS, fuel gauge, ultrasonic sensors, proximity sensors,
accelerometer, pressure sensors, and temperature sensors.
(ii) External: External sensors quantify information of the environment outside the
vehicle. For example, there are sensors used in the smart traffic system that are
capable of sensing vacant parking lots in a designated parking area. The still images
and videos from cameras are important inputs to generate decisions in a vehicular IoT
system. Therefore, on-road cameras are widely used as external sensors to capture
still images and videos. The captured images and videos are processed further, either
in the fog or in the cloud layer, to take certain pre-programmed actions. As an
example, camera sensor can capture the image of the license plate of an over speeding
3
MODULE -5
IOT CASE STUDIES AND FUTURE TRENDS
5.1 INTRODUCTION
In this chapter, we discuss the application of IoT in connected vehicular systems. The use of
connected vehicles is increasing rapidly across the globe. Consequently, the number of on-road
accidents and mismanagement of traffic is also increasing. The increasing number of vehicles
gives rise to the problem of parking. However, the evolution of IoT helps to form a connected
vehicular environment to manage the transportation systems efficiently. Vehicular IoT systems
have penetrated different aspects of the transportation ecosystem, including on-road to off-road
traffic management, driver safety for heavy to small vehicles, and security in public
transportation. In a connected vehicular environment, vehicles are capable of communicating and
sharing their information. Moreover, IoT enables a vehicle to sense its internal and external
environments to make certain autonomous decisions. With the help of modern-day IoT
infrastructure, a vehicle owner residing in Earth’s northern hemisphere can very easily track his
vehicular asset remotely, even if it is in the southern hemisphere. In this chapter, we discuss the
importance and applications of IoT in the vehicular systems. Figure 5.1 represents a simple
architecture of a vehicular IoT system. The architecture of the vehicular IoT is divided into three
sublayers: device, fog, and cloud.
• Device:
The device layer is the bottom-most layer, which consists of the basic infrastructure of the
scenario of the connected vehicle. This layer includes the vehicles and road side units (RSU).
These vehicles contain certain sensors which gather the internal information of the vehicles. On
the other hand, the RSU works as a local centralized unit that manages the data from the
vehicles.
• Fog:
In vehicular IoT systems, fast decision making is pertinent to avoid accidents and traffic
mismanagement. In such situations, fog computing plays a crucial role by providing decisions in
real-time, much near to the devices. Consequently, the fog layer helps to minimize data
transmission time in a vehicular IoT system.
1
, Introduction to IOT 22ETC15H
• Cloud:
Fog computing handles the data processing near the devices to take decisions instantaneously.
However, for the processing of huge data, fog computing is not enough. Therefore, in such a
situation, cloud computing is used. In a vehicular IoT system, cloud computing helps to handle
processes that involve a huge amount of data. Further, for long-term storage, cloud computing is
used as a scalable resource in vehicular IoT systems
Figure 5.1: Architecture of vehicle IOT
5.1.1 Components of vehicular IoT
Modern cars come equipped with different types of sensors and electronic components. These
sensors sense the internal environment of the car and transmit the sensed data to a processor. The
on-road deployed sensors sense the external environment and transmit the sensed data to the
centralized processor. Thereafter, based on requirements, the processor delivers these sensed data
to fog or cloud to perform necessary functions. These processes seem to be simple, but
practically, several components, along with their challenges, are involved in a vehicular IoT
system. Figure 5.2 depicts the components required for vehicular IoT systems
2
, Introduction to IOT 22ETC15H
Figure 5.2: Components of vehicle IOT
• Sensors: We have already discussed how sensors play a crucial role in an IoT-based ecosystem.
Similarly, in vehicular IoT, sensors monitor different environmental conditions and help to make
the system more economical, efficient, and robust. Traditionally, two types of sensors, internal
and external, are used in vehicular IoT systems
(i) Internal: These types of sensors are placed within the vehicle. The sensors are
typically used to sense parameters that are directly associated with the vehicle. Along
with the sensors, the vehicles are equipped with different electronic components such
as processing boards and actuators. The internal sensors in a vehicle are connected
with the processor board, to which they transmit the sensed data. Further, the sensed
data are processed by the board to take certain predefined actions. A few examples of
internal sensors are GPS, fuel gauge, ultrasonic sensors, proximity sensors,
accelerometer, pressure sensors, and temperature sensors.
(ii) External: External sensors quantify information of the environment outside the
vehicle. For example, there are sensors used in the smart traffic system that are
capable of sensing vacant parking lots in a designated parking area. The still images
and videos from cameras are important inputs to generate decisions in a vehicular IoT
system. Therefore, on-road cameras are widely used as external sensors to capture
still images and videos. The captured images and videos are processed further, either
in the fog or in the cloud layer, to take certain pre-programmed actions. As an
example, camera sensor can capture the image of the license plate of an over speeding
3
