UNIT-2

BASIC ARCHITECTURE OF IOT

Internet of Things (IoT) technology has a wide range of applications and the use of the
Internet of Things is growing so faster. It is the networking of physical objects that
contain electronics embedded within their architecture to communicate and sense
interactions amongst each other or to the external environment.

Architecture of IoT
The architecture of IoT is divided into 4 different layers i.e. Sensing Layer, Network
Layer, Data processing Layer, and Application Layer.
Sensing Layer: The sensing layer is the first layer of the Internet of
Things architecture and is responsible for collecting data from different sources.
This layer includes sensors and actuators that are placed in the environment to
gather information about temperature, humidity, light, sound, and other physical
parameters. Wired or wireless communication protocols connect these devices to
the network layer.
Network Layer: The network layer of an IoT architecture is responsible for
providing communication and connectivity between devices in the IoT system. It
includes protocols and technologies that enable devices to connect and
communicate with each other and with the wider internet. Examples of network
technologies that are commonly used in IoT include WiFi, Bluetooth, Zigbee, and
cellular networks such as 4G and 5G technology. Additionally, the network layer
may include gateways and routers that act as intermediaries between devices
and the wider internet, and may also include security features such as encryption
and authentication to protect against unauthorized access.
Data processing Layer: The data processing layer of IoT architecture refers to
the software and hardware components that are responsible for collecting,
analyzing, and interpreting data from IoT devices. This layer is responsible for
receiving raw data from the devices, processing it, and making it available for
further analysis or action. The data processing layer includes a variety of
technologies and tools, such as data management systems, analytics platforms,
and machine learning algorithms. These tools are used to extract meaningful
insights from the data and make decisions based on that data. Example of a
technology used in the data processing layer is a data lake, which is a centralized
repository for storing raw data from IoT devices.
Application Layer: The application layer of IoT architecture is the topmost layer
that interacts directly with the end-user. It is responsible for providing user-friendly
interfaces and functionalities that enable users to access and control IoT devices.
This layer includes various software and applications such as mobile apps, web
 portals, and other user interfaces that are designed to interact with the underlying
IoT infrastructure. It also includes middleware services that allow different IoT
devices and systems to communicate and share data seamlessly. The application
layer also includes analytics and processing capabilities that allow data to be
analyzed and transformed into meaningful insights. This can include machine
learning algorithms, data visualization tools, and other advanced analytics
capabilities.

Architecture of IoT

Advantages of IoT
Execute multiple tasks at a time like a computer.
Easiest internet connectivity
Works on GUI (Graphical User Interface) mode because of HDMI port.
Best suited for server-based applications i.e., can be connected via SSH–Secure
Shell-to access the Rpi command line remotely and file sharing via FTP–File
Transfer Protocol.
More reliable for software applications.

Disadvantages of IoT
Security concerns and potential for hacking or data breaches.
Privacy issues related to the collection and use of personal data.
Dependence on technology and potential for system failures.
Limited standardization and interoperability among devices.
 Complexity and increased maintenance requirements.
High initial investment costs.
Limited battery life on some devices.
Concerns about job displacement due to automation.
Limited regulation and legal framework for IOT,which can be lead to confusion and
uncertainty.
FROM M2M TO IOT:-

1. Internet of Things : IOT is known as the Internet of Things where things are said to
be the communicating devices that can interact with each other using a
communication media. Usually every day some new devices are being integrated
which uses IoT devices for its function. These devices use various sensors and
actuators for sending and receiving data over the internet. It is an ecosystem where
the devices share data through a communication media known as the internet or Iot is
an ecosystem of connected physical object that are accessible through internet. Iot
means anything which can be connected to internet and can be controlled or
monitored using internet from smart devices or PC.
2. Machine to Machine : This is commonly known as Machine to machine
communication. It is a concept where two or more than two machines communicate
with each other without human interaction using a wired or wireless mechanism. M2M
is an technology that helps the devices to connect between devices without using
internet. M2M communications offer several applications such as security, tracking
and tracing, manufacturing and facility management.
M2M is also named as Machine Type Communication (MTC) in 3GPP ( 3rd Generation
Partnership Project).
M2M is communication could carried over mobile networks, for ex- GSM-GPRS, CDMA
EVDO Networks .
In M2M communication, the role of mobile networks is largely confined to server as a
transport networks.
M2M is only subset of IoT .
Difference between IoT and M2M :

Basis of IoT M2M

Abbreviation Internet of Things Machine to Machine

Devices have objects that are Some degree of intelligence is

Intelligence
responsible for decision making observed in this.

Connection type The connection is via Network and The connection is a point to
used using various communication types. point

Traditional protocols and

Communication Internet protocols are used such
communication technology
protocol used as HTTP, FTP, and Telnet.
techniques are used
 Basis of IoT M2M

Data is shared between other

Data is shared with only the
Data Sharing applications that are used to improve
communicating parties.
the end-user experience.

Internet connection is required for Devices are not dependent on

Internet
communication the Internet.

Type of It supports point-to-point

It supports cloud communication
Communication communication.

Involves the usage of both Hardware Mostly hardware-based

Computer System
and Software. technology

A large number of devices yet scope

Scope Limited Scope for devices.
is large.

Business Type Business 2 Business(B2B) and

Business 2 Business (B2B)
used Business 2 Consumer(B2C)

There is no support for Open

Open API support Supports Open API integrations.
APIs

It requires Generic commodity devices. Specialized device solutions.

Communication and device

Centric Information and service centric
centric.

Vertical system solution

Approach used Horizontal enabler approach
approach .

Devices/sensors, connectivity, data Device, area networks, gateway,

Components
processing, user interface Application server.

Smart wearables, Big Data and Sensors, Data and Information,

Examples
Cloud, etc. etc.

M2M TOWARDS IOT:-

Machine-to-machine (M2M) communication is a subset of the Internet of Things (IoT),
focusing on direct communication between devices without human intervention. M2M enables
devices to exchange information and perform actions autonomously, forming a foundation for
broader IoT applications.

Here's a more detailed breakdown:

 M2M as a Subset:
 M2M is a specific type of communication within the broader IoT ecosystem.
 Direct Device-to-Device:
M2M emphasizes direct communication between devices, often using specialized protocols like
MQTT.
 Automation and Efficiency:
M2M enables automation and efficiency in various applications, such as remote monitoring, asset
tracking, and industrial control.
 Broader IoT Context:
IoT encompasses a wider range of interconnected devices that interact with each other and with
cloud services, enabling more comprehensive data collection and analysis.
 Connectivity Foundation:
M2M provides essential connectivity for IoT devices, allowing them to share data and work
together seamlessly.

M2M value chain

IoT value chains
I
AN EMERGING INDUSTRIAL STRUCTURE OF IOT:-
An emerging industrial structure for IoT involves leveraging interconnected devices,
sensors, and networks to gather, transmit, and analyze data from industrial operations. This
data is then used to optimize processes, improve efficiency, and enable predictive
maintenance across various industries.

Key Components of an Emerging Industrial IoT Structure:

 Sensors and Devices:
These collect data from various points in the industrial process, such as machinery, equipment,
and facilities.
 Networking:
This enables the communication and data transfer between sensors, devices, and the cloud or
edge computing infrastructure.
 Edge Computing:
Processing data locally near the source reduces latency and bandwidth requirements, enabling
real-time decision-making.
 Cloud Computing:
Centralized storage and processing of large datasets for analytics and long-term data storage.
 Big Data Analytics:
Analyzing the massive amounts of data generated by IoT devices to identify trends, patterns, and
potential problems.
 Applications:
Software applications that utilize the data from IoT devices to provide insights, automate
processes, and improve decision-making.

Emerging Trends in Industrial IoT:

 Cyber-Physical Systems (CPS):

Integrating physical systems with computing and networking capabilities to enable automation and
real-time control.
 Blockchain Technology:
Ensuring secure and transparent data sharing among different parties in an IIoT network.
 Fog Computing:
Extending the reach of cloud computing to the edge of the network, enabling low-latency
processing and real-time analysis.
 Edge Computing:
Processing data locally near the source, reducing latency and enabling real-time decision-making.
 Predictive Maintenance:
Using data analytics to predict equipment failures and schedule maintenance proactively, reducing
downtime and costs.
 Digital Twins:
Creating virtual representations of physical assets and processes, allowing for simulations,
optimization, and remote monitoring.

Examples of Industrial IoT Applications:

 Transportation and Logistics: Tracking shipments, optimizing routes, and predicting maintenance
needs.
 Oil and Gas: Monitoring pipelines, detecting leaks, and improving safety.
 Utilities: Optimizing energy distribution, reducing energy waste, and improving grid stability.
 Healthcare: Remote monitoring of medical equipment, improving patient care, and reducing
healthcare costs.

Challenges and Considerations:

 Security: Protecting IoT devices and data from cyber threats is crucial.
 Data Management: Handling the massive amounts of data generated by IoT devices requires
robust infrastructure and analytics capabilities.
 Interoperability: Ensuring that different IoT devices and systems can communicate and share data
seamlessly.
 Cost: The cost of implementing and maintaining an IoT system can be significant.
 Scalability: Ensuring that the IoT system can handle increasing numbers of devices and data
streams.