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I) Fundamentals of IoT:
IoT means connecting everyday physical objects (like sensors, machines, vehicles, appliances) to
the internet.
These devices can collect data, share it, and even act on it — without needing much human
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control.
IoT = connecting devices through the internet so they can share, collect, and transfer data.
IoT makes ordinary things “smart” by adding digital intelligence. For example, a smart fridge
can remind you to buy milk.
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IoT can connect people even in faraway or remote areas.

IoT devices often work with low power but still stay accurate. Example: sensors in agriculture
that run on tiny batteries but give correct readings.
Applications of IoT:
Smart Homes
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●​ IoT enables home automation with devices like smart lights, thermostats, and voice
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assistants (Alexa, Google Home).

●​ Example: Lights turn off automatically when no one is in the room.
Healthcare
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●​ Wearable devices (smartwatches, fitness trackers) monitor heart rate, oxygen level, and
steps.
●​ Remote patient monitoring improves medical care.
Smart Agriculture
●​ Sensors measure soil moisture, humidity, and temperature.
●​ Automated irrigation systems help farmers save water and increase crop yield.
Transportation & Smart Vehicles
●​ Connected cars provide real-time navigation, accident alerts, and traffic updates.
●​ Fleet management systems track vehicles and optimize routes.
Industrial IoT (IIoT)
●​ Smart factories use IoT for predictive maintenance of machines, automation, and
reducing downtime.
●​ Improves efficiency and reduces operational costs.
Characteristics of IoT:
1. Connectivity
●​ Devices must be connected (via internet, Bluetooth, Wi-Fi, etc.) so they can share
information.
●​ Example: Your smartwatch connects to your phone.
2. Things

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●​ “Things” = any object that can be connected.
●​ Example: sensors, fridge, AC, car, cows with tracking tags, etc.

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3. Data
●​ Data is the heart of IoT.

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●​ Devices collect data (like temperature, heart rate, GPS location).
●​ Without data, IoT is useless.
4. Communication
●​ Devices not only collect data, they must talk to each other.
●​ Example: Your fitness band sends steps data to your mobile app.
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●​ This can happen over short distances (Bluetooth, Wi-Fi) or long distances (LoRa,
NB-IoT).
5. Intelligence
●​ Devices + Data → Smart decisions.
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●​ Example: A smart AC senses room temperature and decides whether to turn ON or OFF.
●​ Sometimes AI/Big Data helps in making these decisions smarter.
6. Action
●​ After intelligence → comes action.
●​ Example:
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○​ Smart bulb automatically turns ON at night.

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○​ Smart factory machine slows down if it detects overheating.

7. Environment
●​ IoT doesn’t work alone; it fits into a bigger ecosystem of technologies and communities.
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●​ Example: Smart cities use IoT + Cloud + AI + Government policies + people → to make
life better.:
Physical Design of IoT
●​ Turns the IoT plan into a working system with devices and network.
●​ Focuses on nodes (devices), connections, and data management.
●​ Devices can sense, monitor, actuate, transmit data using wired or wireless connections.
Node Devices in IoT
Different devices perform different roles:
 ●​ Connectivity → USB, Ethernet (connect devices & server).
●​ Processor → CPU (process data, improve decisions).
●​ Audio/Video Interfaces → HDMI, RCA (record media).
●​ Input/Output → UART, SPI, CAN (talk to sensors/actuators).
●​ Storage → SD, MMC (store data).
●​ Control → DDR, GPU (control system activity).
IoT Protocols
Protocols = rules for communication between devices and servers.​
They work across network layers:
1.​ Application Layer → Defines how data is sent.

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○​ Examples: HTTP, WebSocket, MQTT, AMQP
○​ HTTP = share web data,

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○​ WebSocket = two-way communication,
○​ MQTT = lightweight for sensors.

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2.​ Transport Layer → Ensures reliable delivery.
○​ TCP = stable data transfer.
3.​ Network Layer → Routes data between devices.
○​ IPv4, IPv6.
4.​ Link Layer → Handles physical connection.
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○​ Ethernet = wired LAN,
○​ Wi-Fi = wireless LAN.
Logical Design of IoT:
It is the actual design of the IoT system. It illustrates the assembling and configuration of the
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components i.e. computers, sensors, and actuators. The logical designs of IoT is composed of:
1. IoT Functional Blocks (Building Blocks)
These are the main parts that make an IoT system work:
●​ Device → Sensors, actuators, appliances (collect data, act, monitor).
●​ Communication → Makes devices talk to each other (wired or wireless).
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●​ Services → Manage device discovery, monitoring, control, and data publishing.

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●​ Management → Track devices, control them, enforce rules, ensure data is safe.
●​ Security → Protects system from hacking, ensures authentication & data safety.
●​ Application → User interface to see status, control devices, and analyze data.
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Think of it like: Devices collect data → Communicate → Managed securely → Shown in an app.
2. IoT Communication Models (How devices talk)
●​ Request-Response → Like asking & answering. Client asks → Server replies (HTTP).​
Ex: Phone app requests sensor data → server responds.
●​ Publisher-Subscriber → Publishers send data → Broker → Consumers receive it.​
Ex: Weather sensor publishes data → app subscribes to updates.
●​ Push-Pull → Publisher pushes data to a queue → Consumer pulls from it later.​
Ex: Messages stored in queue and processed later.
 ●​ Exclusive Pair → Direct two-way communication (full-duplex).​
Ex: WebSocket for live chat or live IoT updates.
3. IoT Communication APIs (Rules for Communication)
REST API (Request-Response model)
●​ Works like web browsing.
●​ Advantages: Simple, flexible, scalable, stateless, caching improves speed.
●​ Best for: Apps where real-time is not critical.
WebSocket API (Real-time two-way)
●​ Once a connection is made, client & server can continuously exchange messages.
●​ Advantages: Efficient, scalable, low overhead, real-time.

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●​ Best for: Real-time IoT apps (smart traffic, gaming, chat, live monitoring).​

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II)IoT Enabling Technologies

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III) IoT Architecture
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The architecture of IoT defines how devices, networks, data, and applications interact to deliver
smart services. Several standard models have been proposed, the most widely used being the IoT
World Forum (IoTWF) Reference Architecture, which defines a 7-layer structure.
Layer 1: Perception Layer (Sensing Layer)
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●​ Physical layer consisting of IoT devices, sensors, RFID tags, cameras, actuators, etc.
●​ Function: Collect raw data from the environment.
●​ Example: A temperature sensor in a smart thermostat.
Layer 2: Network Layer
●​ Responsible for transmitting data collected by sensors to other devices or systems.
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●​ Includes communication technologies like Wi-Fi, Zigbee, Bluetooth, LoRaWAN, 4G/5G.

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●​ Example: Data sent from a smart home device to a cloud server using Wi-Fi.
Layer 3: Edge Layer (Edge Computing)
●​ Performs data preprocessing close to the device to reduce latency and bandwidth usage.
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●​ Example: A gateway that filters redundant sensor data before sending it to the cloud.
Layer 4: Data Processing Layer (Middleware)
●​ Stores, manages, and analyzes the data collected.
●​ Includes databases, cloud storage, and middleware platforms.
●​ Example: AWS IoT or Azure IoT Hub storing real-time device data.
Layer 5: Application Layer
●​ Provides services to the end-users through applications.
●​ Example: A mobile app showing smart home energy consumption.
Layer 6: Business Layer
 ●​ Defines business models, goals, and strategies enabled by IoT.
●​ Example: Predictive maintenance reducing cost in manufacturing.
Layer 7: Security Layer (cross-cutting)
●​ Ensures authentication, encryption, data privacy, and integrity across all layers.
●​ Example: Using SSL/TLS encryption for IoT device communication.

1. Information Technology (IT)​

IT primarily deals with the digital infrastructure, including data storage, networking, analytics,
software applications, and cybersecurity. It ensures that the information gathered from devices is
properly transmitted, processed, and secured.

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●​ Role in IoT:​
IT professionals manage the back-end systems that support IoT applications. This

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includes cloud platforms, databases, machine learning algorithms, and mobile/web apps
that allow users to monitor and control IoT devices remotely.

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●​ Example:​
A cloud engineer working with Microsoft Azure IoT Hub or AWS IoT Core ensures that
data collected from thousands of smart home devices (like thermostats, cameras, or
wearables) is stored securely in the cloud, analyzed for patterns, and made accessible to
users via mobile apps.
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2. Operational Technology (OT)​
OT deals with the physical components of IoT systems, such as sensors, actuators, controllers,
and industrial machines. It ensures the devices in the field operate correctly and provide accurate
real-time data.
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●​ Role in IoT:​
OT engineers focus on device deployment, maintenance, real-time control, and safety.
They make sure the physical systems (factories, vehicles, smart cities) run efficiently and
reliably.
●​ Example:​
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An industrial engineer in a smart factory manages IoT-enabled machines equipped with

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sensors that measure temperature, vibration, and pressure. The engineer ensures these
machines send correct data to IT systems, enabling predictive maintenance to prevent
breakdowns.
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Components of IoT architecture

1. Sensing, embedded components: This layer provides accurate and credible data. It collects
information from the surroundings.
Sensors sense or detect even the slightest changes in the environment. Whereas, actuators
respond or act on the signals they receive. For example, temperature control in smart
thermostats.
2. Connectivity: Networking, communication and connectivity are the fundamentals of any Iot
ecosystem. Without device communication and connectivity, there is in fact no IoT. IoT
protocols transfer data from one place to another. The most common wireless protocols are WiFi,
Zigbee, LoRa and cellular etc.
Gateways are a mode through which the data passes to reach the cloud or servers. Gateways
provide security by limiting unauthorized access.
3. IoT cloud: Cloud stores all the incoming data. Here data processing takes place with the help
of data analysis and actions are performed on the data to generate a response in the system. Edge
computing is done when there is large amounts of incoming data from the user.
4. Data management: This is a proper mechanism that stores the data and remembers information
for future responses.
Regardless of any IoT project, IoT uses some common components:

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1. Devices
2. Connectivity

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3. Platform
4. Data analytics

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5. Applications
IoT Reference Model:
The Reference Architecture of IoT (Internet of Things) is a conceptual framework that provides a
standardized way to understand and design IoT systems. It describes the major functional
components, their relationships, and how data flows across the system. Think of it as a blueprint
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for building IoT solutions. Let’s go step by step.
1. Perception Layer (Sensing Layer)
●​ Function: Collects data from the physical world.
●​ Components: Sensors, actuators, RFID tags, cameras, GPS, temperature sensors.
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●​ Role: Detects events, conditions, or measurements and converts them into digital signals.
●​ Example: A temperature sensor in a smart home or a vibration sensor in an industrial
machine.
2. Network Layer (Transmission Layer)
●​ Function: Transmits data from devices to other devices or centralized systems.
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●​ Components:
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○​ Wired networks: Ethernet, Fiber

○​ Wireless networks: Wi-Fi, Zigbee, LoRaWAN, NB-IoT, 5G
○​ Protocols: MQTT, CoAP, HTTP/HTTPS
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●​ Role: Ensures reliable and secure communication between IoT devices and platforms.
●​ Example: A smart thermostat sending temperature data to the cloud via Wi-Fi.
3. Edge Layer (Edge Computing / Fog Layer)
●​ Function: Performs preliminary processing close to the data source.
●​ Components: Edge gateways, microcontrollers, edge servers.
●​ Role:
○​ Reduces latency
○​ Filters or aggregates data
 ○​ Performs real-time decision-making
●​ Example: A smart camera detecting motion locally before sending an alert to the cloud.
4. Processing Layer (Data Management & Analytics Layer)
●​ Function: Stores, analyzes, and interprets data.
●​ Components: Cloud platforms, big data analytics, databases, AI/ML algorithms.
●​ Role:
○​ Provides actionable insights
○​ Detects patterns and anomalies
○​ Supports decision-making
●​ Example: Predictive maintenance in factories using analytics on IoT data.

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5. Application Layer
●​ Function: Interfaces with end-users and provides services.

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●​ Components: Mobile apps, web dashboards, APIs.
●​ Role: Delivers IoT value through user interaction and visualization.

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●​ Example: Smart home apps controlling lights, thermostat, and security systems.
Simplified IoT Model:
Stage 1: Perception Layer
●​ Description: Contains IoT devices like sensors, actuators, and machines that sense,
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calculate, and connect. Sensors gather data from the environment.
●​ Role: Client-side data collection; acts as the “eyes and ears” of the system.
●​ Data flow: Information gathered here is sent to the aggregation layer or IoT gateway.
●​ Equivalent in standard architecture: Perception Layer + Edge Layer (IoT Gateway).
●​ Example: A smart thermostat sensing temperature, a motion sensor, or an industrial
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machine sensor.
Stage 2: Transport Layer (Connectivity Layer)
●​ Description: Responsible for transmitting data from devices to servers/cloud and sending
responses back.
●​ Technologies: Wi-Fi, Ethernet, Zigbee, Bluetooth, LoRa, Cellular (3G/4G/5G).
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●​ Role: Ensures reliable and secure communication.

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●​ Equivalent in standard architecture: Network Layer.

●​ Example: Sending temperature readings from a smart thermostat to the cloud, or
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receiving an on/off command.

Stage 3: Event Processing Layer
●​ Description: This layer sits in the cloud and contains algorithms for data processing,
analysis, and aggregation. It handles information from multiple devices.
●​ Role: Converts raw IoT data into actionable insights, detects patterns, triggers events, and
performs computations.
●​ Equivalent in standard architecture: Processing Layer (Data Management & Analytics
Layer).
 ●​ Example: Predictive maintenance algorithms analyzing sensor data to forecast machine
failure.
Stage 4: API Management Layer (Application Layer)
●​ Description: Interfaces between third-party apps, users, and IoT infrastructure. Includes
device management, identity, and access control.
●​ Role: Provides a secure way for clients, operators, or engineers to access data or control
devices.
●​ Equivalent in standard architecture: Application Layer + Security Layer.
●​ Example: A mobile app controlling smart home devices, dashboards for industrial
monitoring, or APIs for third-party services.

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The Core IoT Functional Stack: Layers 1–3
The Core IoT Stack consists of three main layers:

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1.​ Device Layer (Sensing and Actuation)
○​ Sensors capture environmental data.

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○​ Actuators take actions based on commands.
○​ Example: Soil moisture sensor in agriculture triggering irrigation.
2.​ Network Layer (Communication and Connectivity)
○​ Connects devices to gateways and the cloud.
○​ Supports multiple communication protocols.
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○​ Example: Smart car using 5G to transmit location data.
3.​ Application Layer (Service Delivery)
○​ Provides meaningful services to end users.
○​ Example: Smart health app showing patient heart rate in real-time.
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IV) IoT Data Analytics

IoT analytics means taking the huge data collected from IoT devices (like sensors, machines,
wearables) and turning it into useful insights.
It is divided into 4 categories:
1.​ Descriptive Analytics – “What happened?”​
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Looks at past data and shows trends, patterns, or reports.​

Example: A smart energy meter shows your daily and monthly power usage.
2.​ Diagnostic Analytics – “Why did it happen?”​
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Finds reasons behind problems by analyzing data deeply.​

Eg: If a motor overheated, it checks vibration and temperature data to find the cause.
3.​ Predictive Analytics – “What will happen?”​
Uses past data + machine learning to predict future events.​
Eg: Predicting when a machine in a factory is likely to fail.
4.​ Prescriptive Analytics – “What should we do?”​
Suggests actions or solutions to improve performance.​
Eg: A smart irrigation system recommends the best watering time for crops.
5 Key Business Benefits of IoT Analytics (Simple)
1.​ Better efficiency – Real-time monitoring reduces downtime and improves operations.​
Eg: Predictive maintenance in factories.
2.​ Lower costs – Finds wastage and saves resources like energy.​
Eg: Smart meters help reduce electricity bills.
3.​ Happier customers – Personalizes services and improves comfort.​
Eg: Smart homes adjust lights and AC to your habits.
4.​ Smarter decisions – Predicts problems early and helps plan ahead.​
Eg: Logistics companies predict vehicle issues to avoid delays.
5.​ New ways to earn money – Creates new services and business models.​
Eg: Companies selling machines as a service, charging only for usage.

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V) IoT Data Management and Compute Stack

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The IoT Data Management and Compute Stack is the technological framework that handles the
entire lifecycle of data generated by IoT devices. It's not a single product but a layered

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architecture of hardware and software that works together to collect, process, store, and analyze
data. The primary purpose of this stack is to minimize latency, conserve network bandwidth, and
increase local efficiency by intelligently managing where and when data is processed. This is
essential for applications that require real-time decisions, such as autonomous vehicles or
industrial automation.This stack is fundamentally a hierarchy of computing locations, with each
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level handling different types of data processing and management tasks. The core components of
this hierarchy are Edge, Fog, and Cloud computing.
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IoT Levels and Deployment Templates

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M2M architecture in IoT

Machine-to-Machine (M2M) refers to direct communication between devices without human
intervention.
In IoT, M2M architecture forms the foundation that allows devices (machines, sensors,
actuators) to exchange information and perform actions automatically. It enables automation,
remote monitoring, and intelligent decision-making.
That's the essence of it, delivering such devices the ability to communicate with each other,
whether it's through wires or wireless transmissions, to be able to share and take action without
having many human interventions.
It has established a protocol of using a specific language so various devices, ranging from a robot
to a printer, to an HVAC system, can exchange data safely and quickly.
There are three layers in M2M architecture:
Application layer
This layer focuses on connectivity between IoT devices and their applications, including
protocols and standardized API definitions for business intelligence systems.
Common services layer

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It provides a horizontal framework across vertical industry applications, encompassing the
physical network, management protocols, and hardware necessary for IoT applications.

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Network services layer
This layer is the communication domain for IoT devices and endpoints, incorporating different

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networking standards like IEEE for efficient communication.
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