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Computer Science

Internet of Things

The Internet of Things (IoT) is a network of physical objects embedded with sensors, software, and network connectivity that allows them to collect and exchange data over the internet without human help.

15 Chapters

109 Lessons

beginner

Course Overview

The Internet of Things (IoT) comprises a whole ecosystem of tangible objects that connect to the internet. It is about a number of household appliances, wearable objects and even devices such as machinery used by industries or smart city components.

This system uses the installation of special sensors, software, and communication technologies to collect data, perform operations with other systems, and generate an automated reaction right away. Thus, a smart thermostat may collect data about house temperature and regulate heating of a building automatically; a sensor may warn about malfunction of the industrial machinery and the need for its timely repair.

In essence, the technology of IoT unites tangible and digital realms of our world, making it more efficient and intelligent.

Course Key Information

Course Duration

Self Paced

Difficulty Level

Beginner

Eligibility

Open to all learners.

What You Will Learn

Responsive HTML5 & Tailwind CSS UI

Modern JavaScript (ES6+), Async/Await & Promises

React.js Components, State, Hooks & Router

Node.js & Express REST API Server Architecture

MongoDB Schema Design & Mongoose ORM

Git/GitHub Workflows & Vercel Deployment

Technologies Covered

HTML5CSS3JavaScriptReactNode.jsExpressMongoDBTailwind CSSGit

Tools & Platforms Used:

VS CodePostmanGitHubMongoDB CompassVercelRender

Lesson Plans & Curriculum

All chapters and lessons are publicly accessible.

15 Chapters

Chapter 1 — Foundations of Internet of Things - IOT

7 Lessons • <p>Foundations of Internet of Things - IOT</p>

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Lesson 1.1: What is IoT? Definition, Core Concepts, and Vision

Lesson 1.2: Evolution of IoT: From M2M to Ubiquitous Smart Networks

Lesson 1.3: Characteristics of IoT Systems (Heterogeneity, Dynamic Changes, Scale)

Lesson 1.4: Real-World Applications Overview (Smart Home, Industry 4.0, Smart Cities)

Lesson 1.5: IoT Enablers & Key Technologies

Lesson 1.6: Challenges in IoT Adoption: Security, Interoperability, Scalability

Lesson 1.8: Future Trends and Emerging Standards in IoT

Chapter 2 — IoT Architectural Frameworks & Components

7 Lessons • <p>IoT Architectural Frameworks & Components</p>

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Lesson 2.1: Fundamental Layers of IoT Architecture (3-Layer vs. 5-Layer Models)

Lesson 2.2: Perception/Sensing Layer Functions and Devices

Lesson 2.3: Network and Transport Layer Responsibilities

Lesson 2.4: Middleware and Application Layer Operations

Lesson 2.5: Hardware vs. Software Components in IoT Deployment

Lesson 2.6: IoT Gateways: Edge Routing and Protocol Translation

Lesson 2.7: Edge vs. Fog vs. Cloud Computing Architectures

Chapter 3 — Sensor Technology & Working Principles

8 Lessons • <p>Sensor Technology & Working Principles</p>

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Lesson 3.1: Classification of Sensors (Analog vs. Digital, Active vs. Passive)

Lesson 3.2: Temperature and Humidity Sensors (DHT11/DHT22, LM35)

Lesson 3.3: Optical, Light, and Proximity Sensors (LDR, Ultrasonic HC-SR04, PIR)

Lesson 3.4: Motion and Inertial Sensors (Accelerometers, Gyroscopes - MPU6050)

Lesson 3.5: Environmental & Gas Sensors (MQ Series, Pressure Sensors)

Lesson 3.6: Sensor Characteristics: Accuracy, Precision, Resolution, Sensitivity, Calibration

Lesson 3.7: Signal Conditioning and Analog-to-Digital Conversion (ADC)

Lesson 3.8: Interfacing Protocols for Sensors (I2C, SPI, UART Basics)

Chapter 4 — Actuator Systems & Hardware Integration

8 Lessons • <p>Actuator Systems & Hardware Integration</p>

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Lesson 4.1: Fundamentals of Actuators and Energy Conversion Principles

Lesson 4.2: Relay Modules: High-Voltage AC/DC Load Control

Lesson 4.3: Electric Motors in IoT: DC Motors and Driver ICs (L298N)

Lesson 4.4: Precision Motion: Servo Motors and Stepper Motors

Lesson 4.5: Hydraulic and Pneumatic Actuators (Industrial IoT Context)

Lesson 4.6: Visual and Auditory Output Devices (OLED, LCD, Buzzers, LEDs)

Lesson 4.7: Closed-Loop Control Systems & Closed Loop Actuation

Lesson 4.8: Sensor-Actuator Feedback Loops & Integrated System Logic

Chapter 5 — IoT Networking Fundamentals

7 Lessons • <p>IoT Networking Fundamentals</p>

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Lesson 5.1: Network Topologies in IoT (Star, Mesh, Hybrid)

Lesson 5.2: Transmission Media: Wired vs. Wireless IoT Connectivity

Lesson 5.3: Short-Range Wireless Technologies (Bluetooth Low Energy - BLE, NFC, RFID)

Lesson 5.4: Medium-Range Wireless Technologies (Wi-Fi 802.11 b/g/n/ac/ax)

Lesson 5.5: Long-Range Low-Power Networks (LPWAN: LoRaWAN, Sigfox, NB-IoT)

Lesson 5.6: Cellular IoT Networks (4G LTE-M, 5G in IoT Systems)

Lesson 5.7: Addressing and Naming in IoT (IPv4 vs. IPv6, 6LoWPAN)

Chapter 6 — IoT Application Layer Communication Protocols

8 Lessons • <p>IoT Application Layer Communication Protocols</p>

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Lesson 6.1: Protocol Requirements for Resource-Constrained Devices

Lesson 6.2: Publish-Subscribe Model Architecture

Lesson 6.3: Deep Dive into MQTT (Topics, Quality of Service QoS, Brokers)

Lesson 6.4: Request-Response Model Architecture

Lesson 6.5: HTTP and RESTful APIs in IoT Web Services

Lesson 6.6: CoAP (Constrained Application Protocol) and UDP-Based Transfer

Lesson 6.7: Comparative Analysis: MQTT vs. HTTP vs. CoAP

Lesson 6.8: Data Format Standards in Protocols (JSON, XML, Protocol Buffers)

Chapter 7 — Wireless Sensor Networks (WSN) & Applications

7 Lessons • <p>Wireless Sensor Networks (WSN) & Applications</p>

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Lesson 7.1: Architecture and Components of a WSN Node

Lesson 7.2: Energy Efficiency and Power Management in WSNs

Lesson 7.3: Routing Protocols in WSNs (AODV, LEACH, Directed Diffusion)

Lesson 7.4: Node Localization and Time Synchronization

Lesson 7.5: WSN Topology Control and Coverage Problems

Lesson 7.6: WSN Applications in Smart Environment Monitoring

Lesson 7.7: WSN Applications in Structural Health and Industrial Tracking

Chapter 8 — Arduino Platform & IDE Basics

7 Lessons • <p>Arduino Platform & IDE Basics</p>

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Lesson 8.1: Overview of the Arduino Ecosystem and Hardware Boards (Uno, Nano, Mega)

Lesson 8.2: Microcontroller Fundamentals (ATmega328P Architecture, Pinouts)

Lesson 8.3: Installing and Configuring the Arduino IDE / Arduino CLI

Lesson 8.4: Structure of an Arduino Program (setup() and loop())

Lesson 8.5: Digital I/O Operations (pinMode, digitalWrite, digitalRead)

Lesson 8.6: Analog Inputs (analogRead) and Pulse Width Modulation (analogWrite)

Lesson 8.7: Using Serial Monitor for Debugging and Communication

Chapter 9 — Sensor & Actuator Interfacing with Arduino

7 Lessons • <p>Sensor & Actuator Interfacing with Arduino</p>

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Lesson 9.1: Interfacing Digital Sensors (PIR, Ultrasonic Sensor Integration)

Lesson 9.2: Interfacing Analog Sensors (LDR, LM35 Temperature Sensor)

Lesson 9.3: Working with Libraries in Arduino (Installing external libraries)

Lesson 9.4: Controlling Motors using Transistors and Relay Drivers

Lesson 9.5: Displaying Data on 16x2 LCD and I2C OLED Displays

Lesson 9.6: Handling Interrupts in Arduino for Real-Time Event Processing

Lesson 9.7: Power Optimization Techniques for Arduino Systems

Chapter 10 — Embedded System Prototyping & Mini-Project

7 Lessons • <p>Embedded System Prototyping & Mini-Project</p>

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Lesson 10.1: Circuit Design Principles, Breadboarding, and Schematic Analysis

Lesson 10.2: Project Concept: Designing an Automated Environmental Monitoring System

Lesson 10.3: Integrating Temperature, Humidity, and Light Sensors

Lesson 10.4: Programming Alarm and Control Thresholds with Actuators

Lesson 10.5: System Testing, Debugging Common Hardware/Software Errors

Lesson 10.6: Adding Serial/Bluetooth Data Communication

Lesson 10.7: Mini-Project Documentation, Code Refactoring, and Demonstration

Chapter 11 — Raspberry Pi Architecture & Setup

7 Lessons • <p>Raspberry Pi Architecture & Setup</p>

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Lesson 11.1: Introduction to Raspberry Pi Hardware (SoC, RAM, GPIOs, Interfaces)

Lesson 11.2: Single-Board Computer (SBC) vs. Microcontroller (Arduino vs. Raspberry Pi)

Lesson 11.3: Flashing and Installing Raspberry Pi OS

Lesson 11.4: Linux Command Line Interface (CLI) Essentials for IoT

Lesson 11.5: Remote Access: SSH Setup, VNC, and Headless Configuration

Lesson 11.6: Python Environment Setup on Raspberry Pi

Lesson 11.7: Overview of Raspberry Pi GPIO Header and Pinout Configuration

Chapter 12 — Raspberry Pi IoT Implementation & Data Handling

7 Lessons • <p>Raspberry Pi IoT Implementation & Data Handling</p>

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Lesson 12.1: Controlling GPIO Pins using Python (RPi.GPIO / gpiozero Libraries)

Lesson 12.2: Interfacing Digital Sensors with Raspberry Pi

Lesson 12.3: Reading Analog Inputs using External ADCs (ADS1115 / MCP3008)

Lesson 12.4: Data Logging: Reading Sensors and Saving Data locally (CSV, SQLite)

Lesson 12.5: Local Database Setup on Raspberry Pi (SQLite / MySQL)

Lesson 12.6: Building a Local Web Server on Raspberry Pi (Flask / FastAPI)

Lesson 12.7: Deploying Edge Analytics Scripts on Raspberry Pi

Chapter 13 — Cloud Integration & Data Visualization

8 Lessons • <p>Cloud Integration & Data Visualization</p>

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Lesson 13.1: Cloud Computing Architecture for IoT Data Management

Lesson 13.2: Overview of IoT Cloud Platforms (ThingSpeak, Adafruit IO, AWS IoT, Firebase)

Lesson 13.3: Connecting Raspberry Pi to Cloud Platforms via REST/MQTT APIs

Lesson 13.4: Real-Time Data Streaming to the Cloud

Lesson 13.5: Building Interactive Dashboards for IoT Data Visualization

Lesson 13.6: Implementing Real-Time Alerts and Push Notifications (Email/SMS Telegram Bots)

Lesson 13.7: Basic Predictive Analytics and Trend Analysis on Telemetry Data

Lesson 13.8: Data Security and Encryption Principles in Cloud Data Transfer

Chapter 14 — Practical Domain-Specific IoT Applications

7 Lessons • <p>Practical Domain-Specific IoT Applications</p>

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Lesson 14.1: Smart Agriculture: Soil Moisture Monitoring, Automated Irrigation, and Climate Control

Lesson 14.2: Precision Farming: Crop Health Tracking and Drone Integration

Lesson 14.3: Healthcare IoT (IoMT): Wearable Sensors and Remote Patient Monitoring

Lesson 14.4: Smart Healthcare: ECG, Pulse Oximeter Interfacing and Emergency Alert Systems

Lesson 14.5: Activity & Fitness Monitoring: Accelerometer-based Step Tracking and Gesture Recognition

Lesson 14.6: Asset and Human Activity Recognition (HAR) using Machine Learning Algorithms

Lesson 14.7: Smart Cities & Home Automation Case Studies

Chapter 15 — Comparative Analysis, Seminars & Future Horizons

7 Lessons • <p>Comparative Analysis, Seminars & Future Horizons</p>

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Lesson 15.1: Architectural Trade-offs: Microcontrollers vs. Single Board Computers

Lesson 15.2: Network Selection Comparison: Range, Bandwidth, and Power Constraints

Lesson 15.3: Technical Comparison of Agriculture, Healthcare, and Activity Monitoring Systems

Lesson 15.4: Seminar Topic Preparation: Security and Privacy Vulnerabilities in IoT

Lesson 15.5: Student Seminar Session 1: Next-Generation IoT Communication and 6G

Lesson 15.6: Student Seminar Session 2: AI at the Edge (TinyML) and Intelligent Devices

Lesson 15.7: Group Project Review, Technical Discussions, and Course Synthesis

Final ChapterProject & Certification

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What's Included in this Course:

15 Course Chapters
109 Lessons
Interactive Lesson Exercises & Notes
Official Verified Digital Certificate
Lifetime Access to All Course Materials

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