Why this course?

Description

The IoT (Internet of Things) Masterclass is an immersive educational program designed to equip 
individuals with the knowledge and skills needed to excel in the rapidly evolving field of IoT. This 
comprehensive course covers fundamental concepts, practical applications, and hands-on experiences, making it an ideal choice for beginners and experienced professionals alike.

The IoT master class is a curated learning experience designed for technology enthusiasts, 
developers, and professionals eager to delve into the realm of the Internet of Things. This program goes beyond theory, providing a hands-on approach to understanding the intricacies of IoT architecture, protocols, security, data management, and real-world applications.
 

Key components of IoT systems:
Devices/Things:

Sensors: These devices collect data from the physical environment. Examples include temperature 
sensors, humidity sensors, motion sensors, and more.

Actuators: Devices that perform actions based on data received from sensors. For example, 
Actuators could control the opening or closing of a valve, the movement of a motor, or the adjustment of a thermostat.

Connectivity:
Communication Protocols: Define the rules for data transmission between devices. Common protocols include MQTT, CoAP, HTTP, and others. Wireless Technologies: Enable communication between devices without the need for physical cables.

Examples include Wi-Fi, Bluetooth, Zombie, Lora, and cellular networks.
Data Processing:

Edge Computing: Processing data locally on the device, reducing the need to send all data to a 
centralized server. This is particularly useful for real-time processing and reducing bandwidth 
usage.

Cloud Computing:
Involves sending data to remote servers for storage, analysis, and processing. Cloud platforms 
provide scalability and accessibility. 

Data Storage:
Databases: Store and manage the large volumes of data generated by IoT devices. Examples include relational databases, NoSQL databases, and time-series databases.
Data Warehousing: Aggregates and analyses data from various sources for business intelligence and reporting.

Analytics and Insights:
Data Analytics Tools: Extract meaningful insights from raw data. This can involve descriptive analytics, predictive analytics, and prescriptive analytics.

Machine Learning and AI: Employ advanced techniques to recognize patterns, make predictions, and automate decision-making based on historical data.
 

Use Cases IoT:
1. Predictive Maintenance in Industrial Settings: Implementing IoT for predictive 
maintenance of industrial equipment to reduce downtime and increase operational efficiency
 2. Asset Tracking in Logistics:
Using IoT to track the movement and condition of assets in the supply chain, improving 
visibility and traceability. 
3. Smart Grids for Energy Distribution:
Implementing IoT in the energy sector to create intelligent and responsive power distribution
systems. 
4. Autonomous Vehicles and Intelligent Transportation Systems:
Integrating IoT into transportation systems for connected and autonomous vehicles. 
5. Smart Clothing and Wearables in Fashion:
Integrating IoT into clothing for smart features such as temperature regulation, fitness tracking, 
and augmented reality experiences.

MODULES OF IoT:
Module 1: Introduction to IoT & the Protocols
Modules 2: Fundamentals of Arduino, Programming & Interfacing
Module 3: Working with Digital sensors – Speed Sensor, DHT11, and Contactless Temperature 
Sensor.
Module 4: Interfacing Analogy Sensors using MCP3008 – LDR, Gas, Memes.
Module 5: Data Monitoring using Thing Speak & Adriano
Modules 6: Integrating Arduino with AWS Cloud
Module 7: Real-time application using Blank App
Module 8: Webpage Monitoring using Arduino & HTML
Module 9: Data logging to Microsoft Azure cloud using Arduino
Modules10: Interfacing Arduino with Arduino Cloud
Modules11: Home Automation using MQTT Protocol
Modules12: Automatic mail Alert using SMTP Protocol
Modules13: Recording sensor data to Google sheet using IFTTT with Arduino
Modules14: Monitoring sensor data using UBIDOTS with Arduino
Modules15: Home automation using Google Assistant
Modules16: Device Communication using UDP & TCP Protocol
Modules17: Raspberry Pi Overview & Python Programming
Modules18: Working with Digital Sensors – Spo2 & Pressure Sensor
Modules19: Interfacing Analogy sensors using MCP3008 – Flame Sensor, Level Sensor & Moisture
Sensor.
Modules20: API integration with Thing Speak using Raspberry Pi
Modules21: Data transmission from Raspberry Pi to AWS Cloud
Modules22: Real-time Application using Blank App
Modules23: Robot Control through Webpage using PHP
Modules24: Logging sensor data to Microsoft Azure
Modules25: Home Automation using MQTT & Mail alert using SMTP
Modules26: Creating a webpage using Flask with Raspberry Pi
Modules27: Logging Sensor Data to Google sheet using Raspberry Pi
Modules28: Working with Sensor data & UBIDOT with Raspberry Pi
Modules29: Integrating Alexi with Raspberry Pi
Modules30: Working with Augment Reality & IoT using Raspberry Pi