Course Outline
- Basics of IoT devices
- Architecture of IoT system – IaaS vs PaaS based IoT system
- Basics of “The things”, Sensors, business functions and mapping between them to build deliverable IoT data.
- Essential components of IoT system- Hardware, Middleware, Security, Fleet manager (sensors and things manager), sensor onboarding, thing onboarding, geofencing, time series data, alert/alarm, data visualization
- AWS Paas functions for Middleware, Security, Fleet manager, alert/alarm etc.
- IoT device security, why we need it?
- Basics of IoT device communication with cloud with MQTT
- Early history of IoT communication.
- Basics of MQTT and why we use MQTT for IoT devices.
- Message queue and PubSub system.
- Connecting IoT devices to AWS with MQTT (AWS IoT Core)
- How to configure IoT core to connect your device.
- Onboarding and deboarding sensors
- Onboarding and deboarding of “The things”
- Connecting AWS IoT core with AWS Lambda function for computation and data storage using DynamoDB
- Connect AWS Core with AWS Lambda.
- What is AWS Lambda.
- What is DynamoDB.
- Collect data from AWS IoT Core and store it to DynamoDB using Lambda.
- Connecting Raspberry PI with AWS IoT core and simple data communication
- Code on Raspberry PI to connect with AWS IoT Core using python.
- Send and receive data.
- AWS SDK/Functions for Middleware security, connectivity and device management
- Hands on with Raspberry PI and AWS IoT Core to build a smart device
- Code on Raspberry PI to read data from sensor and send it to AWS.
- Code on AWS Lambda to read sensor data, process it and control the device based on sensor data to make the device smart.
- Sensor data visualization and communication with web interface
- Building a simple Angular based application to visualize sensor data and host it on AWS S3 for public access.
- SaaS on PaaS for AWS IoT : How to build a SaaS network around AWS Lambda
- Alert and event capture
- Sensor calibration
- Rule addition for alert and events
Requirements
Purpose:
Currently any new IoT development must be done on PaaS (Platform as a service) IoT infrastructure. Leading PaaS IoT systems include, Microsoft Azure, AWS IoT (Amazon), Google IoT cloud and Siemens Mindsphere etc. It’s also important for the developers to know associated PaaS functions necessary to connect IoT data to other ecosystem. In this course a customer will be trained hands on with a Raspberry Pi, a multi-sensor TI sensor Tag chip (which has 10 sensors built in – motion, ambient temperature, humidity, pressure, light meter etc.). A trainee will learn basics of all IoT functions and how to implement them in AWS IoT PaaS cloud using Lambda functions.
Testimonials
IOT applications
Palaniswamy Suresh Kumar - Makers' Academy
The trainer is good - willing to share, ask question and answer queries. The trainer's first hand sharing on the different types of IoT, different applications (e.g., in durians), the demonstration parts.
Makers' Academy
I genuinely liked the new technology.
- PCCW
examples, preparation of materials, level of knowledge of trainer, excellent communication
Michał Krasucki - Instytut Lotnictwa
Practice parts
- Instytut Lotnictwa
The training is practical and it is good for understanding how to use AWS step by step
- PCCW
That it was all new technology and offerings to myself. After being shown how quick and easy it is to set up certain services in AWS, I feel I could get a real benefit out of it for quick project and proposal prototyping.
MDA Systems Ltd.
Fernando knew the products and how to use them. His willingness and friendliness to assist in the hands-on lab was great.
MDA Systems Ltd.
There was a good general pass over what seemed like the most important parts of AWS. The instructor was open to questions and addressed areas of AWS that were not part of the outline based on our questions.
MDA Systems Ltd.
I liked getting to understand the breadth of the services offered by AWS and gaining a better understanding of their pricing model for each of those services.
William Crowdis - MDA Systems Ltd.
Thought it was a good overview of a lot of different services. Liked the detail on IAS.
MDA Systems Ltd.
Explaining why it's financially viable to do these things
MDA Systems Ltd.
It provided context for the things we do in AWS.
MDA Systems Ltd.
Everything. I had played around with AWS before but just on my own personal time. The training really brought everything together, with real world examples and how many individual pieces can be bolted together for a applicable solution.
Matt Sartain - MDA Systems Ltd.
Hands-on labs
MDA Systems Ltd.
Related Courses
Amazon Redshift
21 hoursAmazon Redshift is a petabyte-scale cloud-based data warehouse service in AWS. In this instructor-led, live training, participants will learn the fundamentals of Amazon Redshift. By the end of this training, participants will be able
AWS Advanced Architecture
28 hoursAWS Advanced Architecture refers to the design, setup and deployment of enterprise infrastructure and applications on AWS. This instructor-led, live training (online or onsite) is aimed at cloud engineers wishing to understand and implement the
AWS Developer Associate
28 hoursNOTE: to get the course 100% subsidized by the goverment of Quebec (Quebec residents only) please contact us at quebec@nobleprog.ca REMARQUE: pour que le cours soit subventionné à 100% par le gouvernement du Québec
Amazon ECS (AWS ECS)
14 hoursAmazon Elastic Container Service (Amazon ECS or AWS ECS) is a container orchestration service for running containerized applications on AWS. This instructor-led, live training (online or onsite) is aimed at engineers who wish to use Amazon ECS to
Amazon EKS (AWS EKS)
14 hoursAmazon Elastic Container Service for Kubernetes (Amazon EKS, or AWS EKS) is a service for running Kubernetes on AWS without having to install and operate Kubernetes yourself. This instructor-led, live training (online or onsite) is aimed at
AWS: A Hands-on Introduction to Cloud Computing
7 hoursThis instructor-led, live training provides an overview of AWS products, services and solutions. It is aimed at individuals and teams who are: evaluating/preparing for an initial deployment of their IT infrastructure on
Introduction to AWS Services Storage - Micro Learning
6 hoursThis instructor-led, live online training is delivered as a micro learning event. Aimed at participants who wish to learning the specific aspects of Storage within Amazon Web Services By the end of the session, participants will be able
Creating a CDN with Amazon CloudFront
14 hoursAmazon CloudFront is a CDN (content delivery network) service in AWS. It consists of a globally-distributed network of proxy servers that cache content to improve the download speed for users in different locations. This instructor-led, live
Docker and Kubernetes on AWS
21 hoursThere are a number of options for deploying Docker and Kubernetes on AWS, including Amazon Elastic Container Service, Amazon ECS for Kubernetes, AWS Fargate, and Amazon EC2. This instructor-led, live training (online or onsite) is aimed at
Kubernetes on AWS
14 hoursEKS is a self-managed Kubernetes-as-a-service offering from AWS. EKS is fully scalable and customizable and allows a Kubernetes deployment to mimic and/or integrate with an existing on-premise Kubernetes setup. In this instructor-led, live
AWS IoT Core
14 hoursThis instructor-led, live training (online or onsite) is aimed at engineers who wish to deploy and manage IoT devices on AWS. By the end of this training, participants will be able to build an IoT platform that includes the deployment and
Amazon Web Services (AWS) IoT Greengrass
21 hoursAmazon Web Services (AWS) Greengrass is an open source, cloud service that helps users create and deploy Internet of Things (IoT) applications on devices in homes, cars, hospitals, businesses, and more. AWS IoT Greengrass provides local compute,
Industrial Training IoT (Internet of Things) with Raspberry PI and AWS IoT Core 「4 Hours Remote」
4 hoursSummery: Basics of IoT architecture and functions “Things”, “Sensors”, Internet and the mapping between business functions of IoT Essential of all IoT software components- hardware, firmware, middleware, cloud and
Kubeflow on AWS
28 hoursKubeflow is a framework for running Machine Learning workloads on Kubernetes. TensorFlow is a machine learning library and Kubernetes is an orchestration platform for managing containerized applications. This instructor-led, live training (online
Terraform on AWS
21 hoursAmazon Web Services (AWS) provides infrastructure for building applications in the cloud. Terraform, created by Hashicorp, is a tool for managing that infrastructure. The combination of AWS and Terraform make managing highly complex,