Exploring Aws Iot

Device to AWS Cloud integration: Programming Embedded Devices and managing data in AWS IoT

What you'll learn
Program the ESP8266, ESP32, or Raspberry Pi 3 to send data to AWS IoT Core
Connect to AWS free Tier and use relevant AWS services
Understand MQTT, JSON, IoT, and the AWS cloud
Become familair with device to cloud communication
Place IoT data into Dynamo DB by creating a table and data fields
Gain competency designing graphs and using analytics on IoT data
Code with basic programming structures in JavaScript, Python, and C
Get experience with many AWS services vital to IoT like Lambda and S3
Learn to Create Security certificates and policy's in AWS IoT
Requirements
Comfortable using a PC, Mac, or a Linux computer
Some knowledge of the Internet of Things ( IoT)
Desire to understand device to cloud communication
Experience with a basic IDE like Arduino
Amazon AWS familiarity is helpful
Description
This course explores the various features of device to cloud communication using Amazon AWS IoT Core on a AWS  free tier account.   Before the course starts we need an AWS free tier account, a local installation of the AWS CLI tool, and installation of the MQTT.fx testing tool (all free).  After this is set up we will program inexpensive, WiFi enabled embedded devices such as the ESP8266, ESP32, and Raspberry Pi to communicate with AWS IoT Core with MQTT.    We will take advantage of free "Internet of Things" (IoT)  development environments, like Mongoose OS in JavaScript, Arduino in C, Zernyth in Python, AWS FreeRTOS in C,  and the AWS IoT SDK in both JavaScript and Python for the Raspberry Pi to program our inexpensive WiFi devices.  You will need at least one or more of the following devices to transmit data to AWS IoT.  Alternately, you can send JSON test payloads from IoT Core directly, imitating a IoT device.  The course continues on with programming our embedded devices to send data from the device to the AWS cloud.  To transmit our data we will use the built in MQTT broker on our devices firmware, sending JSON encoded sensor data, to the AWS IoT console.   Device                                     Development Environment                Programming LanguageESP8266 12-E                           Mongoose OS, MicroPython                  JavaScript, ArduinoESP32                                       Arduino, Zerynth, FreeRTOS                   JavaScript, Python, Arduino, CRaspberry Pi 3 Model B           AWS IoT SDK                                          JavaScript, PythonFrom within the IoT console we will create AWS IoT “Rules” and “Actions” to explore many of the built in AWS IoT enabled services that are integrated in the AWS IoT Core console on the AWS cloud. Creating rules-based actions to AWS services we will send, store, file, manipulate, graph and analyze our sensor data through a variety of important AWS applications.   Some of these integrated applications, using these rule-based actions, are Dynamo Database, S3, SNS, Lambda, Data Pipeline, Glue,  QuickSight, AWS IoT Analytics, and SageMaker.IoT is largely the fusion of devices and the web, specifically the cloud; all sending and recording data, ubiquitously and continually, everywhere. Understanding and being able to  prototype and implement an end-to-end, device to cloud path communication is a much in demand career skill. Having the skills to build a prototyping IoT solution in the cloud is already an important and highly demanded skill set for those wanting to call themselves IoT developers, and this is more true as time goes on and IoT exponentially expands as cheap connected devices become wide-spread.   Remember! 30 days money-back guarantee with no questions asked. I want you to be happy with the value I believe this course provides. 

Overview

Section 1: Welcome to the course

Lecture 1 Welcome to the Course

Lecture 2 IoT Devices used for the Course

Lecture 3 Development Board recommendations for 2022

Lecture 4 Software and Languages used for the Course

Lecture 5 The MQTT protocol for IoT and the Publish/Subscribe model

Section 2: Setting up Free tier AWS, AWS CLI, Policys, Security Credentials, and Testing

Lecture 6 AWS Free Tier and Configuring the AWS CLI

Lecture 7 AWS IoT Actions and Core related services

Lecture 8 Introducing IAM for IoT policys and Roles

Lecture 9 Creating Security Credentials and composing an IoT policy from AWS IoT Core

Lecture 10 Communication protocols and security for devices on AWS

Lecture 11 Sending JSON test payloads from the AWS CLI and the IoT Core console

Lecture 12 Download the MQTT.fx test tool

Lecture 13 Using the MQTT.fx tool to test our MQTTs connection and send data to AWS IoT

Lecture 14 Using a MQTT.fx script for automated testing as a virtual IoT device

Lecture 15 Troubleshooting MQTT.fx connection error

Lecture 16 Using the cURL tool to test our AWS IoT certificates via HTTPS to IoT Core

Lecture 17 Automated testing using a bash script and the AWS CLI

Section 3: MQTTs Arduino sketch to AWS IoT Core for the ESP8266/ESP32

Lecture 18 Arduino Sketch to connect your ESP8266/ESP32 directly to AWS IoT Core

Lecture 19 Modified ESP8266/ESP32 Arduino Sketch to deliver JSON payload to AWS IoT Core

Lecture 20 ESP8266 Updated sketch changes for Board Manager 3+

Section 4: HTTPs Arduino sketch to AWS IoT Core for the ESP8266 and ESP32

Lecture 21 A word about Node-Red and the Arduino Sketch.

Lecture 22 The Arduino HTTPS Sketch to connect your device to AWS IoT Core

Section 5: MicroPython to AWS IoT Core using Thonny on the ESP32 and ESP8266

Lecture 23 Introduction to MicroPython and Thonny for the ESSP32 and ESP8266

Lecture 24 Setting up your ESP device for MicroPython and the Thonny IDE

Lecture 25 Programming the ESP32 to connect to AWs IoT Core with Thonny in MircoPython

Lecture 26 Programming the ESP8266 to connect to AWs IoT Core with Thonny in MircoPython

Section 6: Using Mongoose OS on embedded devices for AWS IoT

Lecture 27 Introduction to Mongoose OS

Lecture 28 Reviewing the init.js demo code for our device

Lecture 29 Programming our own init.js firmware with Mongoose OS in Javascript

Lecture 30 Using Mongoose OS in 2022 to connect with IoT Core with a custom loop program

Section 7: Programming the ESP32DevKitC in Python with Zerynth (optional in 2022)

Lecture 31 Registering your Device and Installing the virtual machine

Lecture 32 Configuring Zerynth to AWS IoT

Lecture 33 Running the Test program

Lecture 34 Customizing the test program

Section 8: Programming the RaspberryPi3 with the AWS IoT SDK in Python

Lecture 35 Provisioning AWS IoT to receive our JSON sensor data from our RaspberryPi-3

Lecture 36 Setting up our RaspberryPi3 with the AWS SDK in Python, and the AWS CLI tool.

Lecture 37 Modifying the basicPubSub.py program to send our data to AWS IoT with our Rpi3.

Section 9: Programming the RaspberryPi3 with the AWS IoT SDK in Node.js

Lecture 38 Programming the RPi

Section 10: SNS Push Notifications

Lecture 39 Set up a text notification for our sensor data

Lecture 40 Set up an email notification for our sensor data

Lecture 41 Using conditional data testing for notifications

Section 11: S3 and data objects

Lecture 42 Saving a data object driectly to S3

Lecture 43 Exporting data to CSV or JSON

Lecture 44 Creating an open and accessible public S3 data bucket in 2022

Section 12: Using Kinesis Firehose for stroring timeframe defined data

Lecture 45 Introduction to Kinesis Firehose from the AWS IoT panel

Lecture 46 Configuring Kinesis Firehose for data transfer

Section 13: Storing data into the Dynamo Database from the AWS IoT control panel

Lecture 47 Introduction to DynamoDB

Lecture 48 Configuring the DynamoDB for our sensor data

Section 14: Using the AWS Data Pipeline to move data from DynamoDB to S3

Lecture 49 Introduction to the AWS Data Pipeline

Lecture 50 Configure and implement the Data Pipeline for data transfer to S3

Section 15: Using AWS Glue to index and transform our data

Lecture 51 Introduction to AWS Glue

Lecture 52 Using Glue to crawl our data file

Lecture 53 Using a Glue ETL job to transform our JSON data to CSV

Section 16: AWS Quicksight for data analytics and visulizations

Lecture 54 Introduction to AWS Quicksight

Lecture 55 Editing permissions and S3 bucket access

Lecture 56 Creating a proper manifest to import the CSV file from S3

Lecture 57 Cleaning our data with QuickSight functions

Lecture 58 Further cleaning with functions

Lecture 59 Designing a Line Chart with our data

Section 17: AWS Lambda Functions for IoT

Lecture 60 Introduction to AWS Lambda for IoT

Lecture 61 Creating a Cloudlogger.js function in Lambda

Lecture 62 Advanced Lambda: IoT Publisher from Lambda

Lecture 63 IoT Data Publisher from Lambda

Section 18: Bonus Section: AWS IoT Analytics

Lecture 64 AWS IoT Analytics: Setup Channel, Pipeline, and Datastore

Lecture 65 AWS IoT Anlytics: Ingesting and Displaying our IoT Data

Lecture 66 AWS IoT analytics: Using AWS Sagemaker on our Dataset

Section 19: Bonus Section: AWS Device Shadows and multiple Pub/Sub's

Lecture 67 Intro to Shadow devices and duplex Pub/Sub

Lecture 68 Arduino PubSub sketch with $aws/../shadow/update topics

Lecture 69 Using Multiple Topics with AWS Shadow Sate

Lecture 70 Arduino sketchs with multiple topics and subscription repsonses

Lecture 71 Intro into Shadow/Get and Shadow/Get/Accepted

Lecture 72 Setting up shadow multiple 'Things' representing devices in the wild

Lecture 73 Our Arduino Sketch to maintain state on multiple trucks as IoT devices.

Section 20: Bonus Section: Timestream data ledger with Grafana visualizations

Lecture 74 Create a Timestream database and send IoT data from IoT Core to the new database

Lecture 75 Connect the free Grafana online visualization tool to our Timestream database

Section 21: Bonus Section: Amazon FreeRTOS for the ESP32

Lecture 76 Amazon FreeRTOS Part 1 Intro

Lecture 77 Amazon FreeRTOS Part 2 Setting up the environment and programming files

Lecture 78 Amazon FreeRTOS Part 3 Exploring the code

Section 22: Optional Material: Node-Red for AWS IoT Core

Lecture 79 Intro to using Node-Red with Arduino and AWS IoT

Lecture 80 Creating an IBM Cloudant account and Node-Red App

Lecture 81 Configuring our Node-Red application

Lecture 82 interfacing our Arduino Sketch with Node-Red

Engineers interested in the Internet of Things (IoT),Electronic Hobbyists wanting to acquire more IoT skills,Web or Cloud Programmers interested in Embedded Devices,Embedded device Programmers interested in learning AWS Cloud