Internet of Things

This module will detail the training package learners will receive and assist them to configure the learning environment so they can plan, test and document their studies and assigned IoT project.

This unit provides guidance on a choice of projects that can be chosen as part of the practical content of the course.  Categories for your elected project include IoT projects in Home, Industry or Commercial contexts.

What is the IoT, is it new?  Well, we have actually been using it for years now, but the principles and technologies upon which it is built have finally achieved more definition and standardization has followed. This module explores the IoT, Its structure, components, capabilities, and terminology.

1. Automation – Past Present & Future
2. IoT and the new industrial revolution
3. The IoT landscape- Presenting a model view of A&IoT
4. IoT Evolution – Machine learning & Artificial intelligence
5. Understanding the technologies that underpin IoT

A good understanding of the underlying technology is essential for working seriously with the IoT. This module exposes key topics in order that the learner can understand the functionality of interconnecting technologies while using them to construct their IoT project.

A key concept with automation and the IoT is the ‘sense, solve, actuate’ nature of its functionality. This module focuses on the ‘solve’ aspects of such projects and introduces Python as an ideal platform for ‘programming’ IoT projects.

1. Introduction to programming languages
2. Understanding the Python language
   • Using the Anaconda distribution with Jupyter Notebook and Python
   • Python IDLE, shell and syntax basics
3. General arithmetic functions, properties, and data types
4. Creating & using variables
5. Simple python functions
6. Importing functions from other distributions
7. Soliciting operator input to your programs
8. Simple Lists, Tuples, Sets, and Dictionaries
9. Simple Loops and Software structs

With advances in technology, electronic components and integrated circuits have become small enough to embed in a number of different things. This module explores the hardware and architecture components that make up the hardware in IoT

1. Current technology microcontrollers and the IoT
2. Embedded systems
3. Raspberry Pi & Arduino example systems
   • GPIO pins, LEDs & Shields
   • Peripherals
     • Displays, Keyboards, etc
4. Raspbian Stretch OS for Raspberry PI3

Automation and IoT solutions require sensors to sample the real world and feedback data to the controller for processing and the corresponding output. This module looks at the many sensors and actuators that are available and connects them to your hardware to illustrate the ‘sense, solve, actuate’ principle covered earlier.

1. Getting data from the physical world to the digital world
2. Real-time data for analysis & action
3. Temperature, Pressure, Motion, Humidity, transducers, etc.
4. Introduction to Microelectromechanical systems (MEMS)
5. Interfacing & Breadboarding choice project sensors and actuators
6. Using Python to access, process and display the received data

Without communication, the Internet of Things does not exist. In this unit, we look at the options and principles that allow our remotely attached IoT devices to communicate over long (or short) distances and provide valuable, timely and cost-effective data for analysis.

1. Real-Time communications dilemma for the IoT
2. Understanding the internet
   • Basic architecture
     • TCP/IP principles and addressing
     • IP v4 & 6 explained

3. The cloud defined
4. Interfacing to the internet cloud using WiFi & Cellular services
5. Transmit data over the Internet and control an IoT device
6. Wired & Wireless communications Overview
   • Cellular, Ethernet & Wi-Fi, GPS
7. Protocols & Standards for the IoT cloud
   • Cloud, Fog & Mist (Edge) computing
   • Using FLASK with Raspian
   • Core IoT Functional Stack

This module explores more in-depth Python 3 features, topics, and packages for data science specialisms.

Machine learning is a data analysis technique that teaches computers to ‘learn from experience’; something that we humans do reasonably well in simple scenarios.

In this module, we will consider and address the possibilities that exist to enhance the project you built during this course by looking at Smart Machines & Artificial Intelligence.

Options will be determined by the elected project chosen.