FUNDAMENTALS OF IoT Evolution of Internet of Things, Enabling Technologies, IoT Architectures,oneM 2 M, IoT World Forum

INTRODUCTION TO
INTERNET OF THINGS
(21A050505)
IV-I ECE

UNIT – I
FUNDAMENTALS OF IoT: Evolution of Internet of Things,
Enabling Technologies, IoT Architectures,oneM2M, IoT World
Forum (IoTWF) and Alternative IoT models, Simplified IoT
Architecture and Core IoT Functional Stack, Fog, Edge and Cloud
in IoT, Functional blocks of an IoT ecosystem, Sensors, Actuators,
Smart Objects and Connecting Smart Objects.

What is IoT ?
➢Goal of IoT:
➢Connect the unconnected
Objects that are not currently joined to a computer network-Internet, will
be connected so that they can communicate and interact with people and
other objects.
➢IoT is a technology transition in which the devices will allow us to sense and
control the physical world by making objects smarter and connecting them
through an intelligent network.
➢When objects and machines can be sensed and controlled remotely by across
a network, a tighter integration between physical world and computers are
enabled. This allows enablement of advanced applications.

In the Internet of Things, all the things that are being connected to the
internet can be put into three categories:
➢Things that collect information and then send it.
➢Things that receive information and then act on it.
➢Things that do both.
1. Collecting and Sending Information
Sensors could be temperature sensors, motion sensors, moisture sensors, air
quality sensors, light sensors.
These sensors, along with a connection, allow us to automatically collect
information from the environment which, in turn, allows us to make more
intelligent decisions.
On a farm, automatically getting information about the soil moisture can tell
farmers exactly when their crops need to be watered. Instead of watering too
much (which can be an expensive over-use of irrigation systems) or watering too
little (which can be an expensive loss of crops), the farmer can ensure that crops
get exactly the right amount of water. This enables farmers to increase their crop
yield while decreasing their associated expenses.

2.Receiving and Acting on Information
The machines get information and then acting.
Ex: printer receives a document and it prints it.
A car receives a signal from your car keys and the doors open. The examples are
endless.
Whether it’s a simple as sending the command “turn on” or as complex as
sending a 3D model to a 3D printer, we know that we can tell machines what to
do from far away. Things that collect information and send it, but also receive
information and act on it.
3.Doing Both: The Goal of an IoT System
Farming example: The sensors can collect information about the soil moisture to
tell the farmer how much to water the crops, but you don’t actually need the
farmer. Instead, the irrigation system can automatically turn on as needed, based
on how much moisture is in the soil.

➢History:
What is IoT ?
➢Kevin‘s Explanation:
➢IoT involves the addition
of senses to computers.
➢In the 20th centaury,
computers were brains
without senses.
➢In the 21st centaury,
computers are sensing
things for themselves.

The Internet of Things (IoT) refers to a network of physical objects, or
"things," that are embedded with sensors, software, and other
technologies that enable them to connect and exchange data with other
devices and systems over the internet
"Things":
These can be anything from simple sensors to complex machines,
vehicles, appliances, and even living organisms (like people with
wearable technology).
The basic goal of IoT is to connect the unconnected things so that they
can communicate and interact with people and other objects
IoT is not single technology, but it is good to view it as an umbrella of
various concepts, protocols, and technologies

Sensors:
These devices collect data about the environment or the "thing"
itself, such as temperature, location, or movement.
Connectivity:
This allows the "things" to communicate with each other and with
other systems, typically over the internet.
Data Exchange:
The core function of IoT is the ability to gather data and share it,
often in real-time, to facilitate various applications.
Automation:
By connecting devices and enabling data exchange, IoT allows for
automated processes and tasks, reducing the need for human input.

UNIT - I
Fundamentals of IoT
Genesis of IoT (Evolution of Internet of Things )
▪The Internet of Things (IoT) era began around 2008 - 2009
when more devices were connected to the internet than
people.
▪Kevin Ashton coined the term "Internet of Things" in 1999.
▪IoT enables computers to sense things on their own,
marking a major technology shift.

Genesis of IoT:
➢The age of IoT is started in 2008 and 2009. In these years, more
things connected to the Internet than people in the world.

Evaluation of Internet
The evolution of the Internet can be categorized into four phases.
▪ IOT explains a way of connecting of different set of things and objects to the
internet. while digitization focuses on the way of connecting objects, things, people
with the data which emerges as a business process.
▪ Every field is marching towards digitization. For example photography, video retail
industry, transportation (eg.ola and Uber). Home automation is an good example of
digitization where sensors play a vital role (eg.Nest).

These four phases of internet further defined as
Internet Phase Definition
Connectivity
(Digitize Access)
This phase connected people to email, web services
and search, so that information is easily accessed.
Networked Economy
(Digitize Business)
This phase enabled e-commerce and supply chain
enhancements along with collaborative engagement to
drive increased efficiency in business.
Immersive Experiences
(Digitize Interactions)
This phase extended the Internet Experience to
encompass widespread video and social media while
always being connected through mobility. More and more
applications are moved to Cloud.
Internet of Things
(Digitize the World)
This phase is adding connectivity to Objects and
machines to the world around us to enable new
services and experiences. It is connecting the
unconnected.

Evolutionary Phases of the Internet
➢Each phase of evolutionary phases builds on the previous one.
➢With each subsequent phase, more value becomes available
for businesses, governments and society in general.
Internet Phase: first
Phase
Connectivity(Digitize Access)
➢ Began in the mid 1990s.
➢ Email and getting Internet were luxuries for universities and
corporations.
➢ Dial-up modems and basic connectivity were involved.
➢ Saturation occurred when connectivity and speed was not a
challenge.
➢ The focus now was on leveraging connectivity for efficiency and
profit.

➢Evolutionary Phases of the Internet
Internet Phase:
Second Phase
Networked Economy (Digitize Business)
➢ E-Commerce and digitally connected supply chains become the
rage.
➢ Caused one of the major disruptions of the past 100 years..
➢ Vendors and suppliers became closely interlinked with producers.
➢ Online Shopping experienced incredible growth .
➢ The economy become more digitally intertwined as suppliers,
vendors and consumers all became more directly connected.

Internet Phase:
Third Phase
Immersive Experiences (Digitize
Interactions)
➢ Immersive Experiences, is characterized by the emergence of
social media, collaborations and widespread mobility on a variety
of devices.
➢ Connectivity is now pervasive, using multiple platforms from
mobile phones to tablets to laptops and desktop computers.
➢ Pervasive connectivity enables communications and collaboration
as well as social media across multiple channels via email, texting,
voice and video.
➢ Person to person interactions have become digitized.

Internet Phase:
Forth(last) Phase
Internet of Things (Digitize the World)
➢ We are in beginning of the IoT phase.
➢ 99% of things are still unconnected.
➢ Machines and objects in this phase connect with other machines
and objects along with humans.
➢ Business and society are using and experiencing huge increase in
data and knowledge.
➢ Increased automation and new process efficiencies, IoT is changing
our world to new way.

IoT and Digitization
➢At a high level, IoT focuses on connecting things such as objects
and machines, to a computer network, such as the Internet.
➢Digitization encompasses the connection of things with the data they
generate and the business insights that result.
Example: Wi-Fi devices in Malls detecting customers, displaying
offers, based on the spends, mall is segregated, changes the location
of product displays and advertising.
➢Digitization: It is the conversion of information into a digital format.

IoT and Digitization
Example:
1.Digital camera- No films used, mobile phones with camera.
Digitization of photography changed experience of capturing images.
2.Video rental industry and transportation , no one purchases video
tapes or DVDs. With digitization, everyone is streaming video
content or purchasing the movies as downloadable files.
3.Transportation- Taxi Uber, Ola use digital technologies.
4.Home Automation – Popular product: Nest – sensors determine the
climate and connects to other smart objects like smoke alarm, video
camera and various third party devices.
➢Ex: Nest Learning Thermostat, Nest Protect and Nest Cam enable users
to set heating, check in-house cameras and smoke levels from their
smartphone or another Wi-Fi device.

Internet of Things – Enabling Technologies

Internet of Things – Enabling Technologies
IoT (Internet of Things) relies on several key enabling technologies
The Internet of Things (IoT) is a growing network of connected
objects with IP addresses, enabling internet connectivity and communication
between devices and systems.
Key Aspects
▪ Extended Connectivity: Beyond
traditional devices (PCs, mobile phones,
tablets) to various everyday objects.
▪ Interaction with Environment: Devices
utilize inbuilt technology to sense and
interact with the external environment
via the Internet.
▪ Massive Scale: 50 billion devices
connected worldwide via IoT
technology.
IoT enables communication between objects and systems, transforming the way we
live and work.

IoT (Internet of Things) relies on several key enabling technologies
IOT has grown in many fields which have created an impact on connected
roadways, connected factory, smart connected building and smart creatures.

Self driving cars are introduced by Google which uses the sensors
to monitor the operating conditions of the vehicles. The challenges
encountered by the smart roadways are safety, mobility and
environment of the vehicle. This smart roadway has reduced the
possibility of congestion due to traffic. As vehicles are connected
with internet it gets information regarding the weather conditions
on the road and it makes necessary decisions.
Connected Roadways:

Connected factory
The main challenges facing manufacturing in a factory environment
today include the following:
1. Accelerating new product and service introductions to meet customer
and market opportunities
2. Increasing plant production, quality, and uptime while decreasing cost
3. Mitigating unplanned downtime (which wastes, on average, at least 5%
of production)
4. Securing factories from cyber threats
5. Decreasing high cabling and re-cabling costs (up to 60% of
deployment
costs)
6. Improving worker productivity and safety
Industries are retooling their factories with advanced technologies and
architectures to resolve these problems and boost manufacturing
flexibility and speed.

There are four industrial revolution namely
Industry 1.0, (It deals with the mechanical innovations),
Industry 2.0 (Production level was increased by Companies in this
revolution),
Industry 3.0 ( automation by electronics and information technology),
Industry 4.0 (IOT sensors integrated with the environment)

Smart connected building
Building management systems are used
in building smart building systems
which controls the ventilation,
temperature inside the room. Digital
ceiling will have an Wi-Fi access point,
sensors, surveillance cameras, HVAC,
Lighting control.
HVAC (Heating, ventilation and air
conditioning system)
BMS (building management system)
BAS (Building automation system),
BACnet (Building automation and
control network) are few smart
building systems are incorporated with
the help of IOT.

Smart creatures:
Smart devices are placed on the animals, through which we gain access to
the information and behavior of the animal in an controlled environment.
This helps in finding out the diseases and its cause.
Sensors are placed on the roaches to predict the disaster events which are
going to occur.
The dutch company laid device on cows war, North Carolina state
university experimented with cockroaches

IoT challenges:
There are significant challenges faced by IOT Industry. They are scalability
of the system, security and privacy of the system, interoperability and in
handling of big data and data analytics.
Scale: It refers to the number of people connected to a IOT system. For
example: Through IPV6 millions of devices are connected to the network.
Security: Many devices connected together so any device can attack the
other devices connected to each other. So security is considered to be major
challenge in IOT industry.
Privacy: The sensors gather data and provide health information, shopping
patterns to business people. They may even misuse that data.

IoT challenges:
Big data and data analytics. Huge amount of data is collected from
various devices connected to internet. Handling large set of data
becomes a major challenge.
Interoperability: Different protocols are used by different devices. So
interoperability between devices occurs. Many Iot standards are
developed to handle these issues and challenges.

IoT Architectural Drivers.
Challenges Description IoT Architectural
Changes required
Scale
The massive scale of
IoT endpoints (sensors)
is far beyond that of
typical IT networks.
• The IPv4 address space has reached
exhaustion and
is unable to meet IoT’s scalability
requirements.
• Scale can be met only by IPv6.
• IT networks continue to use IPv4
through features like Network Address
Translation.
Security
IoT devices, especially
those on wireless sensor
networks(WSNs) are often
physically exposed to
the world.
• Security is required at every level of the IoT
network.
• Every IoT endpoint node on the
network must be part of the overall
security strategy and must support
device level authentication and
link encryption.
• It must also be easy to deploy with some
type of a zero – touch deployment model.

Challenges Description IoT Architectural Changes
required
Devices
and
networks
constrained
by power,
CPU
memory
and link
speed
Due to the massive scale
and longer distances, the
networks are often
constrained, lossy and
capable of supporting
only minimal data rates
(10s of bps to 100s of
kbps)
• New-last mile wireless
technologies are needed to support
constrained IoT devices over long
distances.
• The network is also constrained,
i.e modifications need to be made to
the traditional network-layer
transport mechanisms.
The
massive
volume of
data
generated
The sensors generate
the massive amount of
data on daily basis,
causing network
bottlenecks and slow
analytics in the cloud.
• Data analytics capabilities need
to be distributed throughout the IoT
network, from the edge to the cloud.
• In traditional IT networks, analytics
and applications
typically run only in the cloud.

Challenges Description IoTArchitectural Changes required
Support for
legacy
systems
An IoT network often
comprises a collection
of modern, IP capable
end points as well as
legacy , non-IP
devices that rely
on serial or
proprietary protocols.
• Digital transformation is a long
process that may take many years ,
and IoT networks need to support
translation and / or tunneling
mechanisms to support legacy
protocols over standards-based
protocols, such as Ethernet and IP.
The need
for data to
be analyzed
in real time
Where as Traditional
IT networks perform
scheduled batch
processing of data,
IoT data needs to
be analyzed and
responded to in real –
time.
• Analytics software need to be
positioned closer to the edge and
should support real-time streaming
analytics.
• Traditional IT analytics software
(such as relational database or even
Hadoop), are better suited to batch-
level analytics hat occur after the fact.

IoT Network Architecture
1.Importance of Architecture: Careful planning and design are crucial for
IoT networks, just like building a house.
2. Differences from IT Networks: IoT networks have unique challenges
and requirements, such as scale, security, and constrained devices.
Key Challenges
1. Scale: IoT networks need to support millions of devices.
2. Security: IoT devices are vulnerable to cyber attacks and require
robust security measures.
3. Constrained Devices: IoT devices have limited power, CPU, and
memory.
4. Legacy Device Support: IoT networks need to support older devices
with different protocols

IoT Architectures
1. oneM2M: A standardized architecture for IoT.
2. IoT World Forum: A framework for IoT architecture.
The one M2M IoT Standardized Architecture
▪ Global Initiative: oneM2M is a global initiative to promote
efficient M2M communication systems and IoT.
▪ Common Services Layer: oneM2M aims to create a common
services layer for IoT devices and applications.
Overview

The one M2M IoT Standardized Architecture
▪ M2M: Machine-to-Machine communication, standardized by ETSI
▪ Architecture: 3 layers
▪ Application Layer: Connectivity between devices and applications,
standardizes business intelligent systems
▪ Service Layer: Represents physical network, includes management
protocol, hardware, and middleware, supports Restful APIs
▪ Network Layer: Incorporates relationships between communication
domains and end systems, various wireless and wired networking
standards
▪ Key Features: Enables communication between devices and application
servers, focuses on IoT services and applications (smart grid, smart city,
smart vehicles)
▪ Benefits: Supports various industries (business domains, industrial
automation, healthcare), enables smart applications
▪ Technology: Supports LoRaWAN, IEEE 802.15.4, IEEE
802.11ah, IEEE 1901, etc.

Fig: The Main Elements of the oneM2M IoT Architecture

Architecture of oneM2M
▪Three Domains: The oneM2M architecture consists of three domains:
Application Layer, Services Layer, and Network Layer.
▪ Application Layer: Focuses on connectivity between devices and
applications, with standardized northbound API definitions.
▪Services Layer: A horizontal framework that provides APIs and middleware
for third-party services and applications.
▪Network Layer: The communication domain for IoT devices and endpoints,
including wireless and wired connections.
Benefits
▪ Interoperability: oneM2M promotes interoperability at all levels of the IoT
stack.
▪ Standardization: oneM2M develops technical specifications for a common
M2M Service Layer.

IoT World Forum (IoTWF) Architecture
▪ 7-Layer Reference Model: Published in 2014, it provides a technical
perspective on IoT.
▪ IoTWF 7-Layer Architecture- Developed by Cisco, IBM, and Rockwell
Automation in 2014.
▪ Key Features:
Edge computing, data storage, and access
Security across all 7 layers
Service provision from data center or cloud
▪ Benefits:
Simplifies IoT problems
Identifies relationships between technologies
Differentiates components from various vendors
Addresses interoperability issues
Deploys security at each layer
▪ This architecture provides a comprehensive framework for IoT solutions,
ensuring security, interoperability, and efficient data management.

The IoT World Forum (IoTWF) Standardized Architecture:
➢The IoT Reference Model defines a set of levels with control flowing
from the center (this could be either a cloud service or a dedicated data
center), to the edge, which includes sensors, devices, machines and
other types of intelligent end nodes.
➢In general, data travels up the stack, originating from the edge, and goes
northbound to the center.
➢Using this reference model, we are able to achieve the following:
▪ Decompose the IoT problem into smaller parts
▪ Identify different technologies at each layer and how they relate to
one another
▪ Define a system in which different parts can be provided by
different vendors
▪ Have a process of defining interfaces that leads to interoperability
▪ Define a tiered security model that is enforced at the transition
points between levels

7-Layer Reference Model: Published in 2014, it provides a technical
perspective on IoT.
Fig: IoT Reference Model Published by the IoT World Forum

7 layers in the IoT Reference Model:
➢1. Physical Devices: Includes sensors, actuators, and other devices that
interact with the physical world.
➢2. Connectivity: Encompasses communication protocols and networks
(wired/wireless) for device-to-device and device-to-cloud interactions.
➢3. Edge Computing: Involves data processing and analysis at the edge of
the network, closer to the devices.
➢4. Data Accumulation: Focuses on collecting, storing, and managing IoT
data.
➢5. Data Abstraction: Provides APIs and interfaces for data access and
manipulation.
➢6. Application: Includes software applications that utilize IoT data and
insights.
➢7. Collaboration and Processes: Integrates IoT with business processes,
workflows, and other systems.
➢These layers work together to enable efficient, scalable, and secure IoT
solutions.

Layer 1: Physical Devices and Controllers Layer
▪ The first layer of the IoT Reference Model is the physical devices and
controllers layer.
▪ This layer is home to the things in the Internet of Things, including the
various endpoint devices and sensors that send and receive information.
▪ The size of these things can range from almost microscopic sensors to
giant machines in a factory.
▪ Their primary function is generating data and being capable of being
queried and/or controlled over a network.
▪Sensors, devices and controllers.

Layer 2: Connectivity Layer
▪Reliable transmission of data
▪ In the second layer of the IoT Reference Model, the focus is on connectivity.
▪ The most important function of this IoT layer is the reliable and timely
transmission of data.
▪ More specifically, this includes transmissions between Layer 1 devices and
the network and between the network and information processing that
occurs at Layer 3 (the edge computing layer).
▪ The connectivity layer encompasses all networking elements of IoT and
doesn‘t really distinguish between the last-mile network, gateway, and
backhaul networks.

Layer 3: Edge Computing Layer
▪Data reduction, filtering, and processing

▪ Edge computing is often referred to as the foglayer .
▪ At this layer, the emphasis is on data reduction and converting network
data flows into information that is ready for storage and processing by
higher layers.
▪ One of the basic principles of this reference model is that
information processing is initiated as early and as close to the edge of
the network as possible.
▪ Another important function that occurs at Layer 3 is the evaluation of
data to see if it can be filtered or aggregated before being sent to a
higher layer.
▪ This also allows for data to be reformatted or decoded, making
additional processing by other systems easier.
▪ Thus, a critical function is assessing the data to see if predefined
thresholds are crossed and any action or alerts need to be sent
Layer 3: Edge Computing Layer

Upper Layers: Layers 4–7
▪ The upper layers deal with handling and processing the IoT data generated
by the bottom layer.

IT and OT Responsibilities in the IoT Reference Model
➢In the IoT Reference Model, IT (Information Technology) and OT (Operational
Technology) responsibilities intersect and overlap.
OT (Operational Technology) typically focuses on:
➢1. Managing and controlling physical devices, sensors, and actuators.
➢2. Ensuring the operation and maintenance of industrial equipment and processes.
➢3.Focusing on reliability, availability, and safety.
IT (Information Technology) typically focuses on:
➢ 1. Data management, processing, and analytics.
➢ 2.Application development and integration.
➢ 3.Ensuring data security, privacy, and governance.
In IoT, IT and OT converge, requiring collaboration and alignment between these
two domains.
This convergence enables:- Better decision-making through data-driven insights-
Improved operational efficiency and automation- Enhanced innovation and
business opportunities
The IoT Reference Model helps bridge the gap between IT and OT, facilitating a
more integrated and effective approach to IoT solution development and
deployment.

IT and OT Responsibilities in the IoT Reference Model
❑IT Responsibilities
▪ Data Management: Storage, processing, and analysis of data generated by
devices.
▪ Applications: Development and deployment of applications that utilize
IoT data.
❑OT Responsibilities
▪ Device Management: Monitoring, control, and management of devices
and sensors.
▪ Operational Processes: Management of operational processes and
workflows.
Key Differences between IT and OT
▪ Focus: IT focuses on data, while OT focuses on devices and operational
processes.
▪ Functionality: IT handles data processing and analysis, while OT handles
device control and monitoring.

Fig: IoT Reference Model Separation of IT and OT

Benefits of IoTWF Reference Model
▪ Decompose IoT problems: Break down IoT issues into smaller parts.
▪ Identify technologies: Determine different technologies at each layer and
their relationships.
▪ Multi-vendor support: Enable different vendors to provide different parts
of the system.
▪ Interoperability: Define interfaces for seamless interaction between
components.
▪ Tiered security: Implement a security model enforced at transition points
between levels.

Alternative IoT Models
These are the models endorsed by various organizations and standards
bodies and are often specific to certain industries or IoT applications.

A Simplified IoT Architecture
The IoT architecture consists of two parallel stacks:
1. Core IoT Functional Stack: Things (sensors, devices), Communication
Network & Applications
2. IoT Data Management and Compute Stack: Edge Computing, Fog
Computing & Cloud Computing.
This simplified architecture separates core IoT functionality from data
management, enabling industry-specific use cases and efficient data processing.
Fig: Simplified IoT Architecture

A Simplified IoTArchitecture:
➢ The framework separates the core IoT and data management into parallel and
aligned stacks, allowing us to carefully examine the functions of both
the network and the applications at each stage of a complex IoT system.
➢ This separation gives us better visibility into the functions of each layer.
➢ The network communications layer of the IoT stack itself involves a
significant amount of detail and incorporates a vast array of
technologies.
➢ Consider for a moment the heterogeneity of IoT sensors and the many
different ways that exist to connect them to a network.
➢ The network communications layer needs to consolidate these together,
offer gateway and backhaul technologies, and ultimately bring the data
back to a central location for analysis and processing.
➢ Many of the last-mile technologies used in IoT are chosen to meet
the specific requirements of the endpoints and are unlikely to ever be seen in
the IT domain.
➢ However, the network between the gateway and the data center is composed
mostly of traditional technologies that experienced IT professionals would
quickly recognize.

Fig: Expanded View of the Simplified IoT Architecture

A Simplified IoT Architecture:
➢ In the model presented, data management is aligned with each of
the three layers of the Core IoT Functional Stack.
➢ The three data management layers are the edge layer (data management
within the sensors themselves), the fog layer (data management in the
gateways and transit network), and the cloud layer (data management in the
cloud or central data center).
➢ The Core IoT Functional Stack can be expanded into sublayers containing
greater detail and specific network functions.
➢ For example, the communications layer is broken down into four separate
sublayers: the access network, gateways and backhaul, IP transport, and
operations and management sublayers.
➢ The applications layer of IoT networks is quite different from the application
layer of a typical enterprise network.
➢ IoT often involves a strong big data analytics component.
➢ IoT is not just about the control of IoT devices but, rather, the useful insights
gained from the data generated by those devices.
➢ Thus, the applications layer typically has both analytics and industry-specific
IoT control system components.

Core IoT Functional Stack
•Layer 1: Things: Sensors and Actuators Layer: Sensors and devices.
•Layer 2: Communications Network Layer: Connecting devices to the
•Layer 3: Applications and Analytics Layer: Analytics and industry-specific
control systems.
➢ IoT networks are built around the concept of things, or smart objects
performing functions and delivering new connected services.
➢ These objects are smart because they use a combination of contextual
information and configured goals to perform actions.
➢ These actions can be self-contained (that is, the smart object does not rely on
external systems for its actions); however, in most cases, the thing interacts with
an external system to report information that the smart object collects, to
exchange with other objects, or to interact with a management platform.
➢ In this case, the management platform can be used to process data collected from
the smart object and also guide the behavior of the smart object.
➢ From an architectural standpoint, several components have to work together for an
IoT network to be operational:

Layer 1: Things: Sensors and Actuators Layer, Layer 2: Communications Network Layer
Layer 3: Applications and Analytics Layer
1. Things layer: At this layer, the physical devices need to fit the constraints of the
environment in which they are deployed while still being able to provide the information
needed.
• Smart objects (sensors, actuators) with different characteristics:
• Battery-powered or power-connected
• Mobile or static
• Low or high reporting frequency
• Simple or rich data
• Report range
• Object density per cell
• Mobility and throughput requirements
2. Communication Network Layer: Enables communication between smart objects and
external environments:
• Access Network Sub-layer: Wireless technologies (802.11ah, 802.15.4g, LoRa)
and wired networks
• Gateways and Backhaul Sub-layer: Forwards data to central servers, acts as
routers
• Network Transport Sub-layer: Uses transport layer protocols (IP, UDP)
• IoT Network Management Sub-layer: Accesses and exchanges data with sensors
and applications (CoAP, MQTT)

6
1
Communications network layer: When smart objects are not self contained, they need to
communicate with an external system.
➢ This communication uses a wireless technology. This layer has four sublayers:
Access network sublayer:
➢ The last mile of the IoT network is the access network.
➢ This is made up of wireless technologies such as 802.11ah, 802.15.4g, and LoRa.
➢ The sensors connected to the access network may also be wired.
Gateways and backhaul network sublayer:
➢ A common communication system organizes multiple smart objects in a given
area around a common gateway.
➢ The gateway communicates directly with the smart objects.
➢ The role of the gateway is to forward the collected information through a longer-range
medium (called the backhaul) to a headend central station where the
information is processed.
➢ This information exchange is a application function, which is the reason this object is
called a gateway.
➢ On IP networks, this gateway also forwards packets from one IP network to another,
and it therefore acts as a router.
Network transport sublayer:
▪ For communication to be successful, network and transport layer protocols such
as IP and UDP must be implemented to support the variety of devices to connect
and media to use.

IoT network management sublayer:
▪ Additional protocols must be in place to allow the headend applications to
exchange data with the sensors.
▪ Examples include CoAP and MQTT.
3. Application and analytics layer:
▪ At the upper layer, an application needs to process the collected data, not
only to control the smart objects when necessary, but to make intelligent
decision based on the information collected and, in turn, instruct the things
or other systems to adapt to the analyzed conditions and change their
behaviors or parameters.
▪ Analyzes data, makes decisions, and instructs objects to change behavior.
▪ Access Network Technologies
▪ PAN (Bluetooth)
▪ HAN (Zigbee)
▪ NAN (802.11ah)
▪ FAN (Wireless HART)
▪ LAN (IEEE 802.11)
▪ MAN (Wi-Fi)
▪ WAN (Internet)

IoT Network Topologies and Layers
▪ Point-to-Point Topology: Communication between two nodes
▪ Point-to-MultiPoint Topology: One device communicates with multiple devices
▪ Topologies: Star, Mesh, and others, with Coordinator nodes (FFD) and Reduced
Function Devices (RFD)
▪ Communication Network Layer
▪ Gateways and Backhaul: Transfers data from sensors to center, using
technologies like Wi-Fi and WiMax- Network Transport Layer: Uses IP, UDP,
and TCP protocols for secure communication
▪ IoT Network Management Layer: Uses HTTP, MQTT, XMPP, and CoAP
protocols for data transfer and management
Applications and Analytics
▪ Analytics vs Control Applications: Analytics applications collect and analyze
data, while control applications control smart devices
▪ Data vs Network Analytics: Data analytics monitors sensor data, while network
analytics monitors network performance
▪ Smart Services: Intelligent services provided by objects, such as smart home
automation and industrial monitoring

IoT Data Management and Compute Stack
The massive scale of IoT networks drives new architectures to manage the vast
amount of data generated by IoT devices.
IoT Data Management- Data Collection: Sensors generate data, collected by
meter management systems, and analyzed in the cloud
Challenges
▪Data Volume: IoT devices generate enormous amounts of data.
▪Data Variety: Much of the data is unstructured and of little use on its own.
▪Latency: Milliseconds matter in many IoT applications.
▪Bandwidth: Limited bandwidth in last-mile IoT networks.
Cloud Computing in IoT- Centralized Architecture: Cloud computing model for
IoT data analysis- Data-Related Issues:
▪ Limited bandwidth
▪ High latency
▪ Expensive backhaul links
▪ High volume of data
▪ Real-time data management challenges

Fog Computing
▪ Fog Computing is an architecture that uses edge devices to perform
computing, storage, and communication and acts over the internet This
helps IoT to work efficiently.
▪ This involves four layers the bottom most layer has the end points(smart
objects-sensors(low power and low bandwidth)).the next layer is the edge
layer or fog layer, core IPV6 Network layer for communication to the data
center or cloud.
▪ Characteristics of fog computing
▪ Fog nodes provide contextual awareness.
▪ Fog nodes provide services and application on wide geographic
distribution.
▪ In gateway router 4000 fog nodes can be deployed near IoT
endpoints.
▪ Fog computing provides wireless access to all end points.
▪ This computing provides real time interactions and pre
processing of data.

Benefits:
▪Minimizes latency
▪Offloads network traffic
▪Keeps sensitive data local
Fog Nodes: Devices with computing, storage, and network connectivity.
Fig: Fog Computing

Fog Computing
Distributed data management and computing at the edge of the network.
Fig: The IoT Data Management and Compute Stack with Fog Computing

Edge Computing (Mist Computing)
▪ Edge computing enables connected devices to process the data where it
was generated called the “edge.”
▪ This can be done on the device itself (i.e. sensors), or very near to the
device, and provides an alternative way of sending data to a central cloud
for further processing.
▪ Features of Edge computing:
▪ Edge computing is called mist computing.
▪ Edge computing extends to the end device itself.
▪ Effective data processing.
▪ Reduces the consumption internet bandwidth.
▪ It provides security to the sensitive data
Computing and data management within IoT devices or sensors.
Benefits:
Real-time analysis and response
▪Reduced data transmission
▪Improved efficiency

The Hierarchy of Edge, Fog, and Cloud
▪ Edge or fog computing in no way replaces the cloud but they
complement each other, and many use cases actually require strong
cooperation between layers.
▪ Edge and fog computing layers simply act as a first line of defense
for filtering, analyzing, and otherwise managing data endpoints.
▪ This saves the cloud from being queried by each and every node for each
event.
▪ This model suggests a a hierarchical organization of network,
compute, and data storage resources.
▪ At each stage, data is collected, analyzed, and responded to
when necessary, according to the capabilities of the resources at
each layer.
▪ As data needs to be sent to the cloud, the latency becomes higher.
▪ The advantage of this hierarchy is that a response to events
from resources close to the end device is fast and can result in
immediate benefits, while still having deeper compute resources
available in the cloud when necessary.

▪ heterogeneity of IoT devices also means a heterogeneity of edge and fog
computing resources.
▪ While cloud resources are expected to be homogenous, it is fair to expect
that in many cases both edge and fog resources will use different
operating systems, have different CPU and data storage capabilities, and
have different energy consumption profiles.
▪ Edge and fog thus require an abstraction layer that allows
applications to communicate with one another.
▪ The abstraction layer exposes a common set of APIs for monitoring,
provisioning, and controlling the physical resources in a standardized
way.
▪ The abstraction layer also requires a mechanism to support virtualization,
with the ability to run multiple operating systems or service containers on
physical devices to support multitenancy and application consistency
across the IoT system.

▪Edge: Real-time analysis and response.
▪Fog: Distributed computing and data management.
▪Cloud: Historical analysis, big data analytics, and long-term storage.
Fig: Distributed Compute and Data Management Across an IoT System

Sensors in IoT
Sensors are devices that measure physical quantities and convert them into
digital representations. They play a crucial role in IoT systems, enabling
devices to perceive and respond to their environment.
Types of Sensors
1.Active or Passive: Active sensors produce energy output, while passive
sensors receive energy.
2.Invasive or Non-invasive: Invasive sensors are part of the environment,
while non-invasive sensors are external.
3.Contact or No-contact: Contact sensors require physical contact, while
no-contact sensors do not.
4. Absolute or Relative: Absolute sensors measure on an absolute scale,
while relative sensors measure differences.

Sensor Applications
▪ Precision Agriculture: Sensors measure soil characteristics, such as pH levels,
moisture, and nutrient levels.
▪ Smart Homes: Sensors detect temperature, humidity, motion, and more.
▪ Intelligent Vehicles: Sensors monitor speed, pressure, temperature, and other
factors.
▪ Connected Cities: Sensors track traffic, weather, and environmental
conditions.

Actuators in IoT
Actuators are devices that receive control signals and trigger physical effects,
such as motion or force. They complement sensors, enabling IoT systems to
interact with and impact the physical world.
Types of Actuators
1.Classification by Energy Type: Actuators can be categorized based on their
energy source, such as electric, pneumatic, hydraulic, or thermal.
2.Classification by Motion: Actuators can be classified based on the type of
motion they produce, such as linear, rotary, or multi-axis.
Fig: How Sensors and
Actuators Interact with
the Physical World

Actuator Applications
1. Precision Agriculture: Actuators can control valves to deliver optimized
amounts of water, pesticides, fertilizers, and herbicides based on sensor
readings.
2. Industrial Automation: Actuators can perform tasks such as assembly,
inspection, and material handling.
3. Robotics: Actuators enable robots to move and interact with their
environment.
Fig: Comparison of Sensor and Actuator Functionality with Humans

Fig: Actuator Classification by Energy Type

Smart Objects
Smart objects are the building blocks of IoT, transforming everyday objects
into intelligent, networked devices that can learn from and interact with their
environment.
Characteristics of Smart Objects
1. Processing Unit: A smart object has a processing unit for acquiring,
processing, and analyzing data.
2. Sensor(s) and/or Actuator(s): Smart objects interact with the physical
world through sensors and actuators.
3. Communication Device: Smart objects have a communication unit for
connecting with other devices and the outside world.
4. Power Source: Smart objects require a power source, often with limited
power consumption.

Fig: Characteristics of a Smart Object

Trends in Smart Objects
1. Decreasing Size: Smart objects are getting smaller, making them easier to
embed in everyday objects.
2. Decreasing Power Consumption: Smart objects are becoming more
power-efficient, with some lasting 10+ years on a single battery.
3. Increasing Processing Power: Processors are getting more powerful and
smaller, enabling more complex tasks.
4. Improving Communication Capabilities: Wireless speeds and ranges are
increasing, enabling more sophisticated applications.

Wireless Sensor Networks (WSNs)
WSNs are networks of wirelessly connected smart objects that can sense and
measure their environment.
They offer advantages such as:
1. Greater Deployment Flexibility: WSNs can be deployed in harsh
environments and hard-to-reach places.
2. Simpler Scaling: WSNs can scale to large numbers of nodes with ease.
3. Lower Implementation Costs: WSNs can reduce implementation costs
compared to wired networks.
Challenges in WSNs
1. Limited Processing Power: Smart objects in WSNs often have limited
processing power and memory.
2. Lossy Communication: WSNs can experience packet loss and interference.
3. Limited Power: Smart objects in WSNs often have limited power sources,
requiring efficient power management.

Applications of WSNs
▪ Smart Homes: WSNs can control temperature, lighting, and security
systems.
▪ Industrial Automation: WSNs can monitor and control industrial processes.
▪ Environmental Monitoring: WSNs can detect earthquakes, forest fires, and
other environmental phenomena.
Fig: Wireless Sensor Networks (WSNs)

Connecting Smart Objects
When connecting smart objects, several key criteria must be considered:
1. Range: Signal propagation and distance are crucial factors.
2. Frequency Bands: Licensed and unlicensed spectrum, including sub-
GHz frequencies, are used for IoT connectivity.
3. Power Consumption: Devices may be powered or battery-powered,
affecting connectivity options.
4. Topology: Star, mesh, and peer-to-peer topologies are common in IoT
networks.
5. Constrained Devices: Devices with limited resources impact networking
capabilities.
6. Constrained-Node Networks: Networks connecting smart objects may
be low-power and lossy.

IoT Access Technologies
Several technologies are used to connect smart objects:
1.IEEE 802.15.4: A wireless protocol for low-power, low-data-rate
applications.
2.IEEE 802.15.4g: An extension of 802.15.4 for smart utility networks.
3.IEEE 802.15.4e: An amendment to 802.15.4 for industrial and commercial
applications.
4.IEEE 1901.2a: A technology for narrowband power line communications.
5.IEEE 802.11ah: A Wi-Fi-based technology for low-power, low-bandwidth
applications.
6.LoRaWAN: A wireless technology for long-range, low-power
communications.
7.NB-IoT and LTE Variations: Cellular technologies for IoT applications.

Range
The distance over which a signal needs to be propagated, determining the
area of coverage for a selected wireless technology.
Range Categories:
▪ Short Range: Up to tens of meters (e.g., IEEE 802.15.1 Bluetooth,
IEEE 802.15.7 Visible Light Communications)
▪ Medium Range: Tens to hundreds of meters (e.g., IEEE 802.11 Wi-Fi,
IEEE 802.15.4, IEEE 802.3 Ethernet)
▪ Long Range: Greater than 1 mile (e.g., cellular, LPWA, outdoor IEEE
802.11 Wi-Fi)

Fig: Wireless Access Landscape

FUNDAMENTALS OF IoT Evolution of Internet of Things, Enabling Technologies, IoT Architectures,oneM 2 M, IoT World Forum

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