IoT

Io T Enabling Technology
• IoT Enabling Technologies: Wireless Sensor
Networks
• A Wireless Sensor Network (WSN) is a
collection of devices which communicate
through wireless channels. A WSN consists of
distributed devices with sensors which are
used to monitor the environmental and physical
conditions.
•
• A WSN consists of a number of end nodes,
routers and coordinators. End nodes can also
act as routers. A coordinator collects data from
all the nodes and is connected to Internet.
Examples of WSNs used in IoT systems:
• Weather monitoring systems
• Indoor air quality monitoring systems
• Soil moisture monitoring systems
• Surveillance systems
• Smart grids
• Structural health monitoring systems
Sensor Node - consist of
• sensing unit- Temp. Humidity
• processing unit
• communication unit
• storage unit
• ADC
• Power
IoT Enabling Technologies:
Cloud Computing
• Cloud computing is a computing model in
which applications and services are delivered
over Internet.
• The resources provisioned by cloud can be
compute, networking or storage.
• Cloud allows the users to access resources
based on utility model
The characteristics of cloud
computing are:
• On demand: The resources in the cloud are available based
on the traffic. If the incoming traffic increases, the cloud
resources scale up accordingly and when the traffic
decreases, the cloud resources scale down accordingly.
• Autonomic: The resource provisioning in the cloud
happens with very less to no human intervention. The
resources scale up and scale down automatically.
• Scalable: The cloud resources scale up and scale down
based on the demand or traffic. This property of cloud is
also known as elasticity.
• Pay-per-use: On contrary to traditional billing, the cloud
resources are billed on pay-per-use basis. You have to pay
only for the resources and time for which you are using
those resources.
• Ubiquitous: You can access the cloud resources from
anywhere in the world from any device. All that is needed is
Internet. Using Internet you can access your files,
databases and other resources in the cloud from anywhere.
Users can subscribe to cloud resources. These
service models are:
• Infrastructure-As-A-Service (IAAS)
• Platform-As-A-Service (PAAS)
• Software-As-A-Service (SAAS)
• The four cloud deployment models are:
• Public cloud
• Private cloud
• Community cloud
• Hybrid cloud
• In a public cloud the resources are shared
between several users. maintained and
management of the resources is taken by the
cloud service provider. In a private cloud all the
resources are used by a single organization. Such
organization has the complete control on the
cloud and can follow all the necessary
regulations.
• A community cloud is one whose resources are
shared by two or more companies having shared
goals. Such clouds are generally used for
conducting collaborated research. A combination
of the previous three clouds is a hybrid cloud.The
companies generally store the sensitive data in
the private cloud and other non-sensitive data in
the public cloud.
IoT Enabling Technologies:
BigData Analytics
• BigData is a collection of data coming from
various types of sources. The data is often
huge which cannot be handled by the traditional
databases(MICROSOFT SQL Server ,Oracle
Database MY sQL & IBM) and data warehouses.
BigData(Hadoop - help in storing & Analyzing,
Spark - for Real Time processing &Analyzing
large amounts of data) is often characterized
by six Vs
• Volume: Refers to the huge volume of data
aggregated from various sources.
• Variety: Refers to different types of data. Data
can be structured, semi-structured or
unstructured.
• Velocity: Refers to the speed at which the data is
generated. Now-a-days the amount of data
available on the Internet per minute is several peta
bytes or even more.
• Veracity: Refers to the degree to which the data
can be trusted. If the data collected is incorrect or
has manipulated or wrong values, the analysis of
such data is useless.
• Value: Refers to the business value of the
collected. Even though we have huge amount of
data, but it is not useful for gaining profits in the
business, such data is useless.
• Variability: Refers to the ways in which the big
data can be used and formatted
• The data analytics framework consists of six
steps namely: collection, cleaning, integration,
analysis, visualization and alerting
IoT Enabling Technologies:
Communication Protocols
• Communications protocols form the backbone
for IoT systems. They allow devices to
communicate with each other. Protocols define
the data exchange formats, data encoding and
addressing schemes for devices. Protocols
also provide flow control, error control, and
other functions.
IoT Enabling Technologies:
Embedded Systems
• Embedded system can be imagined as
computing hardware with software embedded in
it. An embedded system can be an independent
system or it can be a part of another larger
system.
• An embedded system is a microcontroller or
microprocessor based system which is designed
to perform a specific task. The key components
include microcontroller/micrprocessor, memory,
networking units, I/O, and storage. It runs Real-
Time Operating Systems (RTOS).
IoT Enabling Technologies:
Embedded Systems

• An embedded system has three components.
They are:
• Hardware
• Software
• Real Time Operating system: (RTOS) that
supervises the application software and
provide mechanism to let the processor run a
process as per schedule by following a plan to
control the latencies.
IoT Enabling Technologies:
Embedded Systems
• The characteristics of an embedded system
are:
• Single-functioned
• Tightly constrained
• Reactive and Real time
• Memory
• Connected
IoT Enabling Technologies:
Embedded Systems
• 1. Single-Functioned: Embedded systems are designed to perform a
specific task or a set of related tasks. Unlike general-purpose
computers, which can run a variety of applications, embedded
systems are optimized for particular functions.
• 2. Tightly Constrained: These systems often operate under strict
limitations regarding computational power, memory, and energy
consumption. Their design must optimize the use of limited resources.
• 3. Reactive and Real-Time: Embedded systems frequently need to
respond to external events or inputs in real-time. This means they
must be able to process data and generate outputs within a specific
time frame to maintain system performance and reliability.
• 4. Memory: Due to their specific functions, embedded systems
generally have a limited amount of memory compared to general-
purpose systems.
• 5. Connected: Many modern embedded systems are connected to
other systems or networks. This connectivity allows them to exchange
data and interact with other devices or systems, enhancing their
functionality and integration within larger systems.
• These characteristics help differentiate embedded systems from
general-purpose computing systems.