IoT- Introduction-19th march.pptxhhvvvvvvcc

IoT- Introduction
• IoT stands for Internet of Things.
• It refers to a network of interconnected devices embedded with sensors,
software, and other technologies that enable them to collect and exchange data
over the internet.
• These devices can range from everyday objects such as household appliances,
wearable devices, and industrial machines to vehicles and infrastructure
components like smart grids and smart cities.
• The key concept behind IoT is the ability of these devices to communicate with
each other and with centralized systems, often referred to as the "cloud” (Store,
analyse, monitor, decision)
• IoT application is seen in various domains, including home automation,
healthcare, agriculture, manufacturing, transportation, and more.

Genesis of IoT
• The person credited with creation of the term “IoT” is Kevin Ashton.
• 20th Century- Computers were brain without sensors- input data and
knowledge
• 21st Century- Brain with sensors-themselves.
Evolutionary Phases of IoT:
• Connectivity
• Networked Economy
• Immersive Experiences
• Internet Of Things

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.
. 15
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.
. 15

4
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.

5
Internet Phase: Second Phase Networked Economy (Digitize Business)
 E-Commerce and digital supply chains become the rage.
 E-commerce refers to the buying and selling of goods and services over the internet.
 Vendors, Suppliers and Consumers became closely interlinked.
 Online Shopping experienced incredible growth .
 The economy become more digitally intertwined as suppliers, vendors and
consumers all became more directly connected.
 Supply chain Visibility and planning -machine learning, and AI algorithms to predict
demand patterns

6
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.
 Social Media Interactions (text based communication/Real time chat/Social Networking)
 Video Platform Interactions: (Content creation and sharing/ Live streaming/ Conference-collaborative
viewing)
 Mobile Apps and Platforms (Public transit and digital payments/Digital ticket validation/Ride sharing )

7
Internet Phase: Forth(last) Phase Internet of Things (Digitize the World)
 We are in beginning of the IoT phase.
 60% 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.

Several key technological advancements and
concepts of IoT:
• Advancements in Sensor Technology: The development of smaller, cheaper, and more efficient sensors
played a crucial role in enabling everyday objects to be equipped with sensing capabilities. These sensors
can measure various parameters such as temperature, humidity, motion, and more.
• Wireless Connectivity: The proliferation of wireless communication technologies, such as Wi-Fi, Bluetooth,
Zigbee, and cellular networks, provided the means for devices to connect to the internet without the need
for physical cables. This allowed for greater flexibility and scalability in IoT deployments.
• IPv6: The adoption of Internet Protocol version 6 (IPv6) was necessary to accommodate the vast number of
devices that would eventually be connected to the internet. IPv6 provides a much larger address space
compared to its predecessor, IPv4, allowing for virtually limitless unique IP addresses.
• Cloud Computing: The rise of cloud computing platforms provided scalable and cost-effective solutions for
storing, processing, and analyzing the massive amounts of data generated by IoT devices. Cloud services also
offer the necessary infrastructure for remote device management and software updates.
• Data Analytics and Machine Learning: The ability to extract meaningful insights from IoT data is essential for
realizing the full potential of IoT applications. Advances in data analytics techniques, including machine
learning and artificial intelligence, enable organizations to derive actionable intelligence from the vast
amounts of sensor data collected by IoT devices.
• Standardization Efforts: Various organizations and consortia have worked to develop standards and
protocols for IoT communication and interoperability. Standards such as MQTT (Message Queuing Telemetry
Transport), CoAP (Constrained Application Protocol), and OPC UA (Open Platform Communications Unified
Architecture) help ensure compatibility and seamless integration between different IoT devices and systems.

IoT and Digitization
• IoT and digitization are terms that are often used interchangeably.
•
Digitization refers to the process of converting analog information into a digital format.
This involves encoding analog data, such as text, images, audio, or video, into binary
digits (0s and 1s) that computers can process and store. Digitization allows information to
be stored, transmitted, and manipulated electronically.
Interconnectivity: Digitization has facilitated seamless connectivity between IoT devices
and systems, allowing them to communicate and share data with each other over
networks.
Data Collection and Analysis: Digitization has enabled IoT devices to gather vast amounts
of data from various sources, including sensors, cameras, and other connected devices.
This data can then be analyzed in real-time or stored for later analysis.
Remote Monitoring and Control: Digitization enables remote monitoring and control of
IoT devices and systems, allowing users to access and manage them from anywhere with
an internet connection.
Predictive Maintenance: IoT sensors can collect data on the performance and condition of
equipment that can anticipate potential failures and schedule maintenance proactively,
reducing downtime and maintenance costs.

Benefits of Digitization
• Ease of Storage: Digital data can be stored more efficiently than analog
information, occupying less physical space and enabling easy retrieval and
backup.
• Ease of Transmission: Digital data can be transmitted over various
communication networks, including the internet, with minimal degradation or
loss of quality.
• Ease of Manipulation: Digital data can be easily manipulated and processed using
software applications, allowing for editing, analysis, and transformation.
• Durability: Digital data can be more durable than analog formats, as it is less
susceptible to degradation over time.
• Search ability: Digital data can be indexed and searched quickly, enabling rapid
retrieval of specific information.
• Interoperability: Digital data can be easily shared and integrated across different
systems and platforms, promoting interoperability and collaboration.

Example of digitization from traditional method
For example,
1) Home Automation
2) Digital Camera
3) Newspapers and advertisement services started to offer online
subscriptions and introduced digital advertising models to monetize
their digital content.
3) Digital Video Streaming-Recorded and Live Streaming
4) Digital Transportation Industry
5) In a shopping mall where Wi-Fi location tracking is deployed.

Impact of IoT
• Only 40% of the “Things” are inter-connected.
• Cisco Systems predicted that by 2020, this number will reach 50 billion.
• Helps Managing and monitoring smart objects using real-time
connectivity and enables easy data-driven decision making.
• This in turn results in the optimization of systems and processes and
delivers new services, save time, increase in performance and improve
the overall quality of life.

Connected Roadways
• Fantasizing about the self-driving car or autonomous vehicle which gets connected and interact with smart
transportation infrastructure.
• Smart connected roadways, also known as Intelligent Transportation Systems (ITS) or smart highways, utilize
advanced technologies to enhance safety, efficiency, and sustainability in transportation infrastructure.
Equipped with:
• Smart roads are equipped with sensors. These sensors collect data on traffic flow, vehicle speeds, road
surface conditions, weather, and other relevant parameters.
• Vehicle-to-Infrastructure (V2I) Communication: Smart roads enable communication between vehicles and
infrastructure elements such as wi-fi enabled access points/cellular network, traffic lights, traffic signals,
sign boards, road lane. This communication allows for real-time traffic management, optimization of traffic
flow, and enhanced safety features like collision avoidance warnings.
• Intelligent Traffic Management Systems (ITMS): Smart roads utilize intelligent traffic management systems
that analyze data from sensors and cameras to monitor traffic conditions in real-time. These systems can
predict traffic congestion, detect incidents, and provide automated responses such as adjusting signal
timings, diverting traffic.
• Dynamic Lane Management: Smart roads can dynamically adjust lane configurations and markings based
on traffic conditions and demand. This flexibility helps optimize lane usage, reduce congestion, and improve
traffic flow, especially during peak hours or in areas with variable traffic patterns.
• Environmental Monitoring and Mitigation: Smart roads may include environmental monitoring systems to
measure air quality, noise levels, and other environmental factors. This data can inform pollution mitigation
strategies which helps in urban planning and controlling impact on environment.

Challenges
Challenges Support by IOT Connected Roadways
Safety More crashes and fatalities were reported.
anticipate potential crashes(by considering speed of the other vehicles, debris, pits, weather
etc) and significantly reduce the number of lives lost each year.
Mobility Applications can enable system operators and drivers to make more informed decisions, which
can, in turn, reduce travel delays by optimizing the routing of the vehicles. –Dynamic
rerouting(through GPS communication)
Environment Public Transportation Association, each year transit systems can collectively reduce carbon
dioxide (CO2) emissions-by giving all travelers the real-time information they need and
managing the transportation system effectively by reducing traffic jams

Connected Factory
• connected smart factories represent the next evolution in manufacturing, offering significant improvements in efficiency,
flexibility, and competitiveness in today's rapidly changing industrial landscape.
Key characteristics of a connected smart factory include:
• Interconnectedness: Machines, equipment, and systems are interconnected through IoT devices and networks, enabling
seamless communication and data sharing.
• Data-driven decision-making: The factory collects vast amounts of data from various sources. This data is then analysed
using advanced analytics tools to derive insights and form decision-making processes.
• Automation and robotics: Connected smart factories leverage automation and robotics to streamline production
processes, reduce manual labor and improve consistency in manufacturing, reduction of hazards caused during
manufacturing or uplifting any machinery.
• Predictive maintenance: By continuously monitoring equipment and machinery performance, smart factories can predict
when servicing and maintenance is required for the machines and optimizing maintenance schedules.
• Flexibility and agility: Connected smart factories are designed to be adaptable to changing market demands and
production requirements. They can quickly reconfigure production lines and processes to accommodate new products or
variations.-(This real-time monitoring enables manufacturers to quickly identify bottlenecks, inefficiencies, or deviations
from production targets, allowing for prompt adjustments and optimization of production lines.)
• Preventive Quality control and line maintenance: Real-time monitoring and analytics enable early detection of defects or
deviations from quality standards, allowing for immediate corrective actions to maintain product quality

Smart Building
• Buildings have become increasingly complex intersections of structural, mechanical, electrical,
and IT components.
• The function of a building is to provide a work environment that keeps the person at home or
workers at office comfortable, efficient and safe.
• Home or Work areas need to be well lit and kept at a comfortable temperature and lighting
system.
• Detect occupancy - These tend to be motion sensors-Motion detection occupancy sensors work
great if everyone is moving around in a room and can automatically shut the lights off when
everyone has left-Conserves energy.
• Occupancy can also be integrated with HVAC system, where detection of person inside a room
automatically regulates air flow and automatic moderate temperature adjustment.
• Smart Locking system for safety of the users.
• Fire alarm sensor to sense smoke and fire at the time of disaster.
• Smart refrigerator-gives the status of freshness of the food items inside it, remind to order or
purchase certain food items etc.(recognise food items available and list the recipes on hand

Smart Creatures
• Smart electronic backpack on roaches
• To help with finding a person trapped in the rubble of a collapsed
building.
• The electronic backpack is equipped with directional microphones
that can detect certain sounds and the direction from which they are
coming.

Smart Creatures
Smart sensors in cattles:
• Identification Tags: Electronic identification (EID) tags or RFID tags are commonly used
to uniquely identify individual cattle within a herd.
• Health Monitoring Sensors: Health monitoring sensors measure vital signs such as body
temperature, heart rate, and respiratory rate. These sensors can help detect signs of
illness or stress early, enabling prompt treatment and preventing the spread of diseases
within the herd.
• Milk Yield Monitors: In dairy farming, sensors can be used to monitor milk production
and milk quality parameters such as fat content and protein content. This information
helps dairy farmers to optimise feeding and milk production in cattles.
• GPS Tracking: GPS tracking devices are used to monitor the location and movement of
cattle, particularly in extensive grazing systems. Farmers can use GPS data to track
grazing patterns, monitor herd movements, and prevent theft or predation.
• Feed Intake Sensors: These sensors measure the amount of feed consumed by
individual cattle or groups of cattle. Monitoring feed intake can help optimize feeding
strategies, detect changes in appetite or feeding behavior, and identify health problems
such as digestive disorders.

IT and OT
Information Technology
• IT data centric and Utility with just computing.
• IT typically deals with digital data management, networking, and computing systems, IT
refers to the use of computers, storage, networking, and other computing devices to
manage and process data.
• IT systems are typically used for administrative, communication purpose only.
• Examples of IT systems include enterprise resource planning (ERP) software, email
servers, and office productivity tools like word processors and spread sheets.
Operational Technology
• OT Monitoring and controlling the system computing.
• while OT focuses on the hardware and software used to monitor and control physical
devices.
• OT, on the other hand, focuses on the integration of hardware and ample software
systems that detect changes through direct monitoring or through industrial equipment
and control those physical devices.

Convergence of IT and OT
Convergence refers to the coming together or integration of different elements,
entities, or technologies into a unified whole or common point. It can occur in
various contexts, including:
• Technological Convergence: This is when different technologies merge or evolve
to perform similar functions or operate on similar platforms. For example, the
convergence of telecommunications, computing, and media technologies in the
form of smartphones.
• Media Convergence: This refers to the merging of traditional media forms (such
as newspapers, television, and radio) with digital technologies and platforms (like
the internet and social media). It involves the integration of content across
multiple media channels.
• Industrial Convergence: Industries that were once distinct may converge due to
technological advancements or changing market dynamics. For instance, the
automotive and technology industries are converging with the development of
autonomous vehicles and electric cars.

Objectives of convergence of IT and OT
• Enhanced Visibility and Insights: Integrating IT and OT systems enables
organizations to gather and analyse data from both digital and physical
sources, providing deeper insights into operations, performance, and
potential areas for improvement.
• Real-Time Decision Making: By accessing real-time data from OT systems
and integrating it with IT systems, system can make faster and more
informed decisions, enabling proactive responses.
• Innovation and New Opportunities: The convergence of IT and OT opens
up new possibilities for innovation, such as the development of predictive
maintenance solutions, smart manufacturing processes, and connected
supply chains.

IoT Challenges
While an IoT-enables impressive picture, it does not come without significant challenges.
1) Security
• With more “things” becoming connected with other “things” and people, security is an increasingly complex
issue for IoT.
• The threat surface is now greatly expanded, and if a device gets hacked, its connectivity is a major concern.
• A compromised device can serve as a launching point to attack other devices and systems.
2) Privacy
• As sensors become more prolific in our everyday lives, much of the data they gather will be specific to
individuals and their activities.
• This data can range from health information to shopping patterns and payment transactions
• For businesses, this data has monetary value.
3) Scale
• Devices are getting connected in a larger number and various sector-banking/health science/industry
• This means the scale of the network utility has increased.
• Challenge is on managing the increasing network usage and security issues within the network.

4) Big Data and Analytics
• IoT and its large number of sensors is going to trigger a massive amount of data
that must be handled.
• This data will provide critical information and insights with various parameter.
• The challenge, however, is evaluating massive amounts of data arriving from
different sources, in various forms and doing so in a timely and real time manner.
5) Interoperability
• various protocols and software architectures are evolving in market share for
standardization within IoT.
• Some of these protocols and architectures are based on proprietary elements,
and others are open.
• Proprietary elements are new challenges to the IoT technology in terms of
(privacy and security issues, compatibility ,rules and regulatory risk, cost, limited
customisation, etc)

IoT Network Architecture
• IoT Network architecture refers to the design and structure of a IoT
network.
• It encompasses various components, protocols, and technologies
that define how devices communicate and exchange data within the
network.
• Network architecture plays a crucial role in ensuring the efficient,
secure, and reliable operation of a network.
• IoT is different technology than existing IT Technology and thus,
requires new IoT architecture models.

IoT Architectural Drivers
• Scale- The massive scale of IoT endpoints - The IPv4 address space
has reached exhaustion and is unable to meet IoT’s scalability
requirements (IPv6 and NAT technology)
• Security- IoT devices, especially those on wireless sensor networks
(WSNs), are often physically exposed to the threat world
(modification to design of an existing network with a primary focus on
implementing robust security measures to protect against various
cyber threats and vulnerabilities)
• Constrained Devices and Networks – Due to devices constrained by
power, CPU, memory and speed and bandwidth network are always
lossy and supports minimal data rates- wireless technologies are
needed upgrade in network and transport layer to support
constrained IoT devices over long distances.

• Data Analytics- The sensors generate a massive amount of data on a 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.(Analytics refers to the systematic analysis of
data or statistics to uncover meaningful patterns-It involves applying
various techniques, methods, and tools)
• The need for data to be processed in real time- Whereas traditional IT
networks perform scheduled batch processing of data, IoT data needs to be
analyzed and responded to in real-time- Analytics software and processing
needs to be positioned closer to the edge and should support real time
processing.
• Support for legacy devices-An IoT network often comprises a collection of
modern, IP-capable endpoints as well as legacy, non-IP devices-
Integrating IoT with legacy systems can be challenging due to differences in
technology, protocols, and data formats (upgradation in data
normalisation, gateways, transmission network, middleware platform,etc)

The IoT World Forum (IoTWF) Standardized
Architecture
• the IoTWF architectural committee published a seven-layer IoT
architectural reference model.
• While various IoT reference models exist, the one put forth by the IoT
World Forum offers a clean and simplified perspective on IoT.

• Perception/ Physical Layer: The Perception Layer is the lowest layer of the
IoT reference model and represents the physical world where sensors,
actuators, and other IoT devices collect data from the environment. This
layer is responsible for sensing and capturing real-world data such as
temperature, humidity, motion, and location.
• Connectivity Layer: The Connectivity Layer is responsible for transporting
data collected by IoT devices to the next layer of the IoT architecture,
typically through wired or wireless communication networks. This layer
concentrate on protocols, standards, and technologies for connecting IoT
devices to the internet and other network infrastructure.
• Edge computing (Edge Server): in IoT refers to the practice of processing
data closer to the source of generation, typically at or near the edge of the
physical network, rather than relying solely on centralized cloud computing
resources. In edge computing, data is processed locally on IoT devices,
gateways, or edge servers, before being transmitted to the cloud or data
center for further analysis or storage.

Purpose of Edge Computing
• Reduced Latency: By processing data locally at the edge of the network, edge computing
reduces the latency associated with transmitting data to centralized cloud servers for
processing. This is particularly important for applications that require real-time or low-
latency processing.
• Bandwidth Optimization: Edge computing helps optimize network bandwidth by
reducing the amount of data that needs to be transmitted to the cloud. By processing
data locally and transmitting only relevant or aggregated data to the cloud, edge
computing minimizes network congestion.
• Improved Privacy and Security: Edge computing enhances data privacy and security by
processing sensitive data locally on IoT devices or edge servers, rather than transmitting
it over potentially insecure network connections to centralized cloud servers.
• Resilience and Reliability: Edge computing improves the resilience and reliability of IoT
systems by enabling local processing and decision-making capabilities, even in the
absence of network connectivity or during network outages. This ensures that critical
functions can continue to operate autonomously at the edge, without relying on
continuous access to cloud services

• Data Accumulation (Storage): The cloud plays a significant role in IoT (Internet of
Things) deployments by providing a scalable, flexible, and centralized platform
for storing, processing, and analyzing data generated by IoT devices.
Purpose of Cloud:
• Data Storage: The cloud serves as a reliable, scalable and centralized repository
for storing large volumes of data generated by IoT devices.
• Data Processing: The cloud provides powerful computing resources for
processing and analyzing large volume of IoT data in real-time by using big data
analytics platform on the stored data.
• Security: Cloud providers offer robust security measures, data encryption,
protect IoT data and applications from unauthorized access, data breaches, and
cyber threats
• Device Management: Cloud-based device management platforms enable
organizations to remotely monitor, manage, control and update the gathered
data at scale

• Data Aggregation: Data aggregation simplifies and condenses the
information into more manageable and meaningful forms. Data
aggregation summarises data points for the purpose of reporting and
visualisation. (Sampling, grouping, counting, averaging etc)
• Application : The application layer in IoT serves as the interface
between IoT devices and end-users. Proactive monitoring, controlling
and timely response to critical events is achieved here through
actuators or application software.
• Collaboration: Data sharing among various entities like stake holders,
business sector etc for constant upgradation of iot services,
analyzation and management of data gathered and operation
performed.

Simplified IOT Architecture
• The IoT technology core stack is a spectrum of technologies, standards and applications designed
to connect devices to the Internet to collect data from them for different purposes.
• Data management and compute stack Includes data framework and virtual layer elements.

Simplified and IOTWF Architecture
Standardization and Frameworks
• Simplified IoT Architecture: It may not adhere strictly to any specific
IoT standard or framework but rather provides a generic template
that can be adapted and customized according to specific needs.
• IoTwf IoT Architecture: The IoTWF architecture is likely to
incorporate standards, best practices, and guidelines established by
the Internet of Things World Forum. It may provide a structured
framework for designing, implementing, and managing IoT
solutions, promoting interoperability and scalability across different
domains and industries.

Interoperability and Ecosystem Integration
• Simplified IoT Architecture: While interoperability is important, the
simplified architecture may not delve deeply into standards and
protocols for seamless integration between diverse devices,
platforms, and ecosystems.
• IoTwf IoT Architecture: The IoTwf architecture may place greater
emphasis on interoperability, emphasizing the need for standardized
protocols, interfaces, and data models to facilitate seamless
communication and collaboration within the IoT ecosystem.

Complexity and Scope:
• Simplified IoT Architecture: The simplified IoT architecture provides a
high-level overview of the essential components involved in an IoT
system, focusing on the basic functionalities and interactions
between devices, connectivity, cloud platforms, analytics, and user
interfaces.
• IoTwf IoT Architecture: The IoTwf IoT architecture, developed by the
Internet of Things World Forum, is likely to be more comprehensive
and detailed. It may include additional components, layers, and
standards specific to the IoTwf framework,

M2M IoT Architecture
• The European Telecommunications Standards Institute (ETSI) created the M2M
Technical Committee in 2008. The goal of this committee was to create a
common architecture that would help accelerate M2M applications and
devices.
• In 2012 ETSI and 13 other inventive bodies launched oneM2M as a global
initiative designed to promote efficient M2M communication systems and IoT.
• The goal of oneM2M is to create a common services layer, which can be readily
embedded in field devices to allow communication with extensive application
like smart metering applications, smart grid, smart city automation, e-health, and
connected vehicles.
• One of the stated goals of oneM2M is to “develop technical specifications
which address the need for a common M2M Service Layer that can be readily
embedded within various hardware and software nodes,

• The oneM2M architecture divides IoT functions into three major domains: the
application layer, the services layer, and the network layer.
• Applications layer: The oneM2M architecture gives major attention to connectivity
between devices and their applications.
• This domain layer includes the standard optimised application-layer protocols, data
models and attempts to standardize API definitions for interaction with various
system.
• Service Layer: they are like middlewear components which facilitates communication
and data exchange. One of the stated goals of oneM2M is to “develop technical
specifications which address the need for a common M2M Service Layer that can be
readily embedded within various hardware and software nodes.
• Network layer: This is the communication domain for the IoT devices and end points. It
includes the devices themselves and the communications network protocols, gateways
and frameworks that link them. concerned on improvising connectivity technologies
Bluetooth, Zigbee, cellular networks and wired connections such as Ethernet.

• The IoT technology stack is nothing else than a range of
technologies, standards and tools, which lead from the simple
connection of objects to the applications that use these connected
things, the data they gather and communicate and the different
steps needed to power them.

Layer 1: Physical Layer
• Most IoT networks start from the object, or “thing,” that needs to be
connected.
• From an architectural standpoint, the variety of smart object types,
shapes, and needs drive the variety of IoT protocols and
architectures.

IoT- Introduction-19th march.pptxhhvvvvvvcc

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