Internet Of Things(IOT)

Q.What is IoT?

Internet of Things (IoT) is a network of physical objects (things) such as sensors, devices, vehicles, appliances etc. that are connected to the internet to collect, exchange, and process data without much human intervention.

Q.What is Internet ?

A worldwide network that connects millions of devices for communication and data sharing.

Q.What is Things ?

Physical objects (devices, sensors, appliances) connected to the internet to collect and exchange data

📌Characteristics of IoT

• Connectivity

• Sensing

• Communication

• Automation

• Scalability

• Interoperability

• Security

Connectivity

Devices must be connected via internet or network.

Sensing

Devices can sense environment data (temperature, motion, etc.).

Communication

Devices exchange data using protocols

Automation

IoT works with minimum human effort.

Scalability

Easily add new devices without performance loss

Interoperability

Different devices/brands should work together.

Security

Safe data transfer and device protection.

📌Applications of IoT

• Smart Home

• Healthcare

• Smart Cities

• Agriculture

• Industrial IoT (IIoT)

• Transportation

Smart Home

Automates home devices for comfort & energy saving.
👉 Example: Smart bulbs, Alexa, Nest thermostat.

Healthcare

Monitors patient health remotely.
👉 Example: Smart watches tracking heartbeat, glucose monitor.

Smart Cities

Manages traffic, waste, and energy efficiently.
👉 Example: Smart traffic lights, smart parking

Agriculture

Improves farming with sensors & automation.
👉 Example: Soil moisture sensor, smart irrigation.

Industrial IoT (IIoT)

Enhances manufacturing & safety.
👉 Example: Predictive maintenance in factories.

Transportation

Increases safety & efficiency in travel.
👉 Example: Connected cars, GPS tracking, Uber

📌IoT Framework

• Perception Layer

• Network Layer

• Edge Layer

• Application Layer

• Business Layer

Perception Layer

This is the physical layer that uses sensors, actuators, RFID, and cameras to collect real-world data (like temperature, motion, light).
👉 Example: Temperature sensor in smart home.

Network Layer

Responsible for transmitting the sensed data securely and reliably to other devices or cloud platforms using communication technologies.
👉 Example: Wi-Fi, Bluetooth, 5G.

Edge Layer

Performs preliminary processing and filtering of data close to the source device to reduce latency and network load.
👉 Example: Raspberry Pi or IoT gateway.

Application Layer

Delivers user-oriented services and applications to different industries such as healthcare, smart cities, or agriculture.
👉 Example: Smart home app controlling lights.

Business Layer

Defines the business logic, policies, and goals, making decisions based on IoT-generated data to create value and improve strategies.
👉 Example: A company using IoT analytics to reduce costs

Q.What is iot architecture ?

IoT Architecture is a structured design that defines how IoT devices, networks, storage, and applications interact to collect, process, and deliver data.
It provides different layers (like perception, network, middleware, application, business) to ensure smooth communication and services

📌Cisco IoT Architecture

• Perception Layer (Sensing)

• Network Layer

• Edge Layer

• Processing Layer

• Application Layer

• Application Layer

• Business Layer

Perception Layer

Sensors, RFID, actuators collect real-world data.

Network Layer

Data transfer using Wi-Fi, ZigBee, Bluetooth, 5G, etc

Edge Layer

Local computing at gateways or edge devices.

Processing Layer

Data storage, filtering, and management.

Application Layer

User services (smart home, healthcare, etc.).

Business Layer

Defines business goals, rules, and analytics.

Security Layer

Provides end-to-end security, authentication, and privacy.

📌Oracal iot Architecture

• Gether

• Inreach

• Stream

• Manage

• Acuire

• Oragenize analize

Gether

Devices (things) collect raw data from sensors, edge devices, or external system.

Inreach

Gatewaye proccess and refind data before sending it.

Stream

Data flows through network to server to cloud.

Manage

Devices are identified authenticated and given access.

Acquire

Data is stored in big data centers .

Organize and Analize

Business intelligence tools Analize data for decision making.

📌Physical Design of IoT

📌 Definition:
The physical design of IoT refers to the actual hardware components and devices that make up an IoT system. It focuses on the things (objects) in IoT and the way they are connected to sense, process, and communicate data.

It mainly consists of devices, sensors, actuators, protocols, and communication systems.

📌Components of Physical Design in IoT

1. Things (Devices / Objects)

2. Sensors

3. Actuators

4. Connectivity / Communication

6. IoT Gateway

5. Protocols

1. Things (Devices / Objects)

• "Things" are the core physical objects connected to the Internet.

• These can be sensors, actuators, appliances, machines, or vehicles.

• Example: Smart fridge, fitness band, CCTV camera.

2. Sensors

• Devices that sense or measure physical parameters like temperature, light, motion, humidity, pressure, etc.

• Convert physical values into electrical/digital signals.

• Example: Temperature sensor in AC, motion sensor in smart door.

3. Actuators

• Devices that perform actions based on signals received.

• Convert electrical signals into physical action (movement, heat, sound, etc.).

• Example: Motor turning ON in smart fan, valve controlling water supply.

4. Connectivity / Communication

• IoT devices need communication technologies to transfer data.

• Wired: Ethernet, USB.

• Wireless: Wi-Fi, Bluetooth, Zigbee, RFID, NFC, Cellular (4G/5G), LoRaWAN.

6. IoT Gateway

• Acts as a bridge between IoT devices and the cloud/internet.

• Collects data from sensors, processes it, and sends it to servers.

• Example: Smart home hub (Amazon Echo, Google Nest Hub).

5. Protocols

• Protocols define how IoT devices communicate and exchange data.

• Application Layer Protocols: MQTT, CoAP, HTTP/HTTPS.

• Network & Communication Protocols: IPv6, 6LoWPAN, Zigbee.

📌Generic Block Diagram of IoT Device

1. Connectivity

   • Provides wired/wireless communication.

   • Examples: Wi-Fi, Bluetooth, Zigbee, NFC, Cellular (4G/5G).

2. Processor (Microcontroller / Microprocessor / SoC)

   • Brain of IoT device.

   • Handles data processing, computation, and control operations.

   • Examples: ARM Cortex, Arduino, Raspberry Pi, ESP8266.

3. Memory

   • Used to store program code and temporary data.

   • RAM: Temporary working memory.

   • ROM/Flash: Permanent storage for firmware.

4. Graphics (Display Interface)

   • If IoT device needs user interaction, graphics interface drives LCD/LED/OLED displays.

   • Example: Smartwatch display, IoT thermostat screen.

5. Audio/Video Interface

   • For capturing and output of media.

   • Examples: Microphones, speakers, cameras, video streaming interface (CCTV, smart doorbell).

6. Storage

   • Stores large amounts of collected data.

   • Local storage: Flash memory, SD card.

   • Cloud storage: Remote servers.

7. I/O Interfaces (Input/Output Ports)

   • Enable device to connect with external sensors, actuators, and peripherals.

   • Examples: GPIO pins, USB, HDMI, SPI, I2C, UART.

📌Logical Design of IoT

The logical design of IoT refers to the abstract architecture, models, and functions of IoT systems. It explains how IoT devices, applications, and services interact logically, regardless of the underlying hardware.

It focuses on data flow, communication models, functional blocks, and protocols.

📌M2M (Machine-to-Machine Communication)

📌 Definition:
M2M (Machine-to-Machine) is a type of communication where two or more devices exchange information directly with each other without human involvement.

It allows machines (sensors, devices, embedded systems) to collect data, transmit it over a network, and act on the information automatically.

📌Key Features of M2M

• Automatic Communication: Machines communicate without human help.

• Uses Sensors & Actuators: To monitor and control physical conditions.

• Networks Involved: Cellular (2G/3G/4G/5G), Wi-Fi, Zigbee, Bluetooth, Satellite.

• Data Flow: Device → Network → Server → Another Device.

• Goal: Improve efficiency, real-time monitoring, automation.

📌Examples of M2M

• Smart Meters: Electricity meters sending usage data to utility company.

• Fleet Management: GPS devices in trucks sending location data to control center.

• ATM Machines: ATMs communicating with banks for transaction authorization.

• Smart Vending Machines: Automatically alert company when stock is low.

📌Advantages of M2M

• Reduces human intervention.

• Real-time monitoring and control.

• Improves efficiency and automation.

• Cost savings in operations.

📌SDN (Software-Defined Networking)

📌 Definition:
SDN is a modern network architecture that separates the control plane (decision-making) from the data plane (packet forwarding).

Instead of configuring each router/switch manually, SDN uses a centralized controller (software-based) to manage the entire network.

📌Architecture of SDN

1. Application Layer

   • Includes network apps (firewalls, load balancers, monitoring tools).

   • Provides requirements to the SDN controller (e.g., “route video traffic faster”).

2. Control Layer (SDN Controller)

   • The brain of SDN, centralized software that manages policies and routing.

   • Translates app requirements into instructions for devices.

3. Infrastructure Layer (Data Plane)

   • Physical devices (switches, routers) that forward packets based on controller instructions.

   • These devices don’t make decisions on their own.

📌How SDN Works (Flow):

1. Application requests a service (e.g., allocate bandwidth).

2. SDN Controller processes the request and decides routes.

3. Controller sends instructions to network devices.

4. Devices forward packets accordingly.

📌Key Features of SDN

• Centralized Control: Single controller manages the whole network.

• Programmability: Network can be programmed using software.

• Flexibility: Easy to change policies (security, routing, bandwidth).

• Dynamic Scaling: Adapts quickly to new traffic demands.

📌Advantages of SDN

• Simplified network management.

• Faster deployment of new applications/services.

• Better security (centralized monitoring).

• Reduced operational cost.

• High flexibility and automation.

📌Disadvantages of SDN

• Initial setup cost is high.

• Controller failure may cause network failure (single point of failure).

• Requires skilled professionals.

• Compatibility issues with old hardware.

📌Applications of SDN

• Data Centers: Cloud providers (Google, Amazon, Microsoft) use SDN for flexible traffic management.

• Enterprise Networks: Easy network configuration and security enforcement.

• WAN Optimization: Better bandwidth usage and traffic routing.

• 5G & IoT Networks: Flexible and scalable communication control.

📌NFV (Network Function Virtualization)

📌 Definition:
NFV is a network architecture concept that uses virtualization technology to run network functions (firewall, load balancer, router, VPN, etc.) as software applications instead of using dedicated hardware devices.

👉 Matlab jo kaam pehle ek hardware box karta tha (jaise router ya firewall), ab wohi kaam ek software (VM/Container) cloud server pe kar sakta hai.

📌Architecture of NFV

1. VNFs (Virtual Network Functions)

   • Ye woh software applications hain jo ek specific network function perform karte hain.

   • Examples: Firewall, Load Balancer, NAT, DNS, VPN, IDS (Intrusion Detection System).

2. NFVI (Network Function Virtualization Infrastructure)

   • Ye woh hardware + virtualization layer hai jisme VNFs run karte hain.

   • Components: Servers, Storage, Network devices, Hypervisor (VMware, KVM, Xen).

3. MANO (Management and Orchestration)

   • Ye pura management system hai jo VNFs ko install, configure, scale aur monitor karta hai.

   • Subparts:

     • Orchestrator → resources allocate karta hai.

     • VNF Manager → VNFs ko manage karta hai.

     • Virtualized Infrastructure Manager (VIM) → physical resources ko control karta hai.

📌Working of NFV (Step by Step)

1. Network service request hota hai (e.g., VPN service).

2. NFV Orchestrator required VNFs select karta hai.

3. VNFs server pe deploy hote hain (VMs/containers ke form me).

4. NFVI unke liye resources (CPU, RAM, Storage, Network) allocate karta hai.

5. MANO ensure karta hai ki VNFs sahi se run ho rahe hain aur scale ho sakte hain.

📌Features of NFV

• Hardware independent (runs on commodity servers).

• Virtualization-based (VMs or containers).

• Scalable (easily add/remove functions).

• Cost-effective (no need for dedicated devices).

• Dynamic provisioning (functions can be deployed on-demand).

📌Advantages of NFV

• Cost Saving: No need to buy multiple hardware devices.

• Flexibility: Easily deploy new services.

• Scalability: Functions can be scaled up or down as per demand.

• Faster Deployment: Services can be launched in minutes.

• Simplified Management: Centralized orchestration.

📌Disadvantages of NFV

• Performance may be lower than specialized hardware.

• Security issues (multi-tenancy in cloud).

• Complexity in orchestration.

• Reliability issues if virtual infrastructure fails.

📌Applications of NFV

• Telecom Operators: Virtual routers, firewalls, EPC (Evolved Packet Core).

• Enterprise Networks: VPN services, security appliances.

• Data Centers & Cloud: Load balancing, IDS/IPS.

• 5G & IoT: NFV plays a key role in enabling flexible mobile networks.

📌Data Storage in IoT

📌 Definition:
Data storage in IoT refers to the process of collecting, storing, and managing huge volumes of data generated by IoT devices (sensors, actuators, gateways, smart devices) in a way that it can be retrieved, processed, and analyzed efficiently.

Since IoT devices generate massive, real-time, and continuous streams of data, efficient storage systems are essential.

📌Types of Data in IoT

1. Device Data → Collected from sensors (temperature, motion, pressure).

2. Metadata → Information about device status, location, time.

3. User Data → Behavior, preferences, interactions.

4. Application Data → Processed results, analytics, reports.

📌Challenges in IoT Data Storage

• Huge Volume → Billions of devices generate petabytes of data.

• High Velocity → Real-time continuous streams.

• Variety → Structured (tables), semi-structured (JSON/XML), unstructured (video, images).

• Security & Privacy → Sensitive user/device information must be protected.

• Scalability → Storage system must grow with the number of devices

IoT Data Storage Models

1. Device Level Storage

• Data is stored locally in IoT devices.

• Used for small data and temporary storage.

• Example: Smart watch storing steps data before syncing with phone.
  ✅ Fast access, ❌ Limited capacity.

2. Edge/Fog Storage

• Data stored at edge devices or gateways (closer to source).

• Reduces latency by processing data before sending to cloud.

• Example: CCTV system storing video locally in DVR before sending to cloud.
  ✅ Low latency, ❌ Limited long-term storage.

3. Cloud Storage

• IoT devices send data to cloud platforms (AWS IoT, Google Cloud IoT, Azure IoT).

• Cloud offers huge storage, scalability, backup, analytics.

• Example: Smart home devices sending data to Amazon AWS for AI-based processing.
  ✅ Scalable, reliable, ❌ High bandwidth needed.

📌Technologies Used in IoT Data Storage

• Databases:

  • SQL (MySQL, PostgreSQL) → Structured data.

  • NoSQL (MongoDB, Cassandra) → Unstructured & semi-structured data.

• Cloud Storage: AWS S3, Google Cloud Storage, Azure Blob Storage.

• Big Data Platforms: Hadoop, Spark, HDFS.

• Time-Series Databases: InfluxDB, OpenTSDB (for sensor data).

📌Characteristics of IoT Data Storage

1. Scalable → Can handle billions of records.

2. Secure → Encrypted and access-controlled.

3. Low Latency → Fast read/write.

4. Cost-Effective → Cloud storage with pay-per-use.

5. Reliable → Backup and recovery enabled.

📌Example (Smart Home System Data Storage)

• Sensors (temperature, light) → Store temporary data in device.

• Gateway (router) → Stores and filters important data.

• Cloud (AWS IoT Core) → Stores long-term data for analytics.

• Database (MongoDB) → Saves user preferences and logs.

📌Advantages of Efficient IoT Data Storage

• Real-time decision-making.

• Predictive analytics possible.

• Data backup and recovery.

• Reduces latency and improves IoT application performance.

📌IoT Cloud-Based Services

📌 Definition:
IoT Cloud-Based Services are platforms and tools used to collect, store, process, and analyze data generated by IoT devices on cloud servers via the Internet.

They provide scalability, real-time processing, data analytics, and remote access for IoT applications.

📌Key Functions of IoT Cloud-Based Services

1. Data Storage: Sensor data is stored on cloud servers.

2. Data Processing: Cloud servers analyze data in real-time.

3. Application Hosting: IoT apps (like dashboards, monitoring apps) run on the cloud.

4. Security: Provides encryption, authentication, and access control.

5. Scalability: Can easily handle an increasing number of IoT devices.

6. Remote Access: Users can monitor/control devices from anywhere.

📌Examples of IoT Cloud Platforms

• Amazon AWS IoT Core

• Microsoft Azure IoT Hub

• Google Cloud IoT

• IBM Watson IoT

• Oracle IoT Cloud

📌Advantages of IoT Cloud-Based Services

• Large scale data storage

• Cost-efficient (no need for local infrastructure)

• Real-time analytics and AI integration

• Secure and reliable

• Easy integration with mobile & web apps

📌Disadvantages

• Dependence on Internet (without Internet devices can’t send data)

• Data privacy and security concerns

• Vendor lock-in (hard to switch cloud providers)

📌Use Cases

• Smart Homes: Devices like Alexa, Google Nest store and process data on the cloud.

• Healthcare: Patient monitoring devices send health data to cloud servers.

• Smart Cities: Traffic sensors and pollution monitoring devices store/analyze data in the cloud.

• Industrial IoT: Machines send performance data to the cloud for predictive maintenance.