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Internet of Things

Lesson-1-> Introduction to IOT
1.1 What is IOT ?
1.2 Why do we need IOT?
1.3 How IOT works?
1.4 Features & Application of IOT
Lesson-2-> Introduction to Node MCU & Arduino IDE
2.1 What is Node MCU?
2.2 Hardware description of Node MCU
2.3 What is Arduino IDE?
2.4 How to download Arduino IDE software?
2.5 How to use Arduino IDE for Node MCU programming?
2.6 Introduction to different syntax for writing any code in Arduino IDE.
Lesson-3->Introduction to ThingSpeak
3.1 Introduction to Data Analytics.
3.2 Introduction to ThingSpeak
3.3 How to login in ThingSpeak
3.4 How it works ?
Activity-1-> IOT Enabled Light System
1.1 Introduction
1.2 What is server?
1.3 Circuit connection
1.4 Code to control Bulb by server
Activity-2-> IOT enabled Temperature Monitoring System
2.1 Introduction
2.2 How to setup Thingspeak?
2.3 Code
Activity-3-> IOT based Weather Reporting system
3.1 Introduction
3.2 Code
Activity-4-> IOT based Plant Monitoring system
4.1 Introduction to project
4.2 Coding
Activity-5 –> IoT Based Air Pollution Monitoring
5.1 Introduction to project
5.2 Code
Activity-6 –> IOT based Home Security System
6.1 Introduction to project
6.2 How to setup Telegram Bot?
6.3 Coding
Activity-7-> Home Automation using Google Assistant
7.1 What is Google Assistance?
7.2 Introduction to Activity
7.3 Installing Blynk App
7.4 How to Download Arduino IDE and Configuring Blynk Libraries?
7.5 How to upload code to NodeMCU?
7.6 Connect Google Assistant to NodeMCU using IFTTT
7.7 Coding to control Relay using Google Assistant
Activity-8 –> Home Automation using Alexa
8.1 Introduction to project
8.2 Code
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3.1 Introduction to Data Analytics.

Data Analytics is a process of examining data or datasets and then give a conclusion about the information they have. The goal of data analysis is to discover useful information, conclusions, and supporting decision-making. Data analytics allow us to make informed decisions and to stop guessing. 

Process of data analytics :

Data analytics in IoT

IoT data analytics is analytics that assesses the data collected from IoT devices. This variant of analytics is particularly well-suited to analyze IoT data because the devices typically generate a lot of information, in a relatively short time. Statistics show that IoT devices produce 2.5 quintillion bytes of data on a daily basis. There is a huge volume of data sets that IoT applications make use of. There may also be a significant difference in the data formats and types. Data analytics will allow the business executive to analyze all of these varying sets of data using automated tools and software.