IoT devices are implemented using both hardware and software components. Dedicated hardware components are used to implement the interface with the physical world, and to perform tasks which are more computationally complex. Microcontrollers are used to execute software that interprets inputs and controls the system. This module discusses the roles of both the hardware and software components in the system.

This course will start by providing a definition of the term. We will talk about how various trends have enabled the Internet of Things, and how it changes the way programming is done. We will also discuss some of the ramifications that IoT is having on society today.

In IoT architecture, edge computing is a distributed computing paradigm which brings computer data storage closer to the location where it is needed. Computation is largely or completely performed on distributed device nodes. Edge computing pushes applications, data and computing power (services) away from centralized cloud points to locations closer to the user. Edge computing does not need contact with any centralized cloud, although in IoT archetectures it interacts with one.

This module explores key Rust concepts in depth, such as ownership, the type system, error handling, and fearless concurrency. This Rust programming language introduction will also show you how to: - Grasp important concepts unique to Rust, like ownership, borrowing, and lifetimes - Use Cargo, Rust’s built-in package manager, to build and maintain your code, including downloading and building dependencies - Effectively use Rust’s zero-cost abstractions and employ your own You’ll learn to develop reliable code that’s speed and memory efficient, while avoiding the infamous and arcane programming pitfalls common at the systems level.

A hands-on module teaches the Rust programming language in the context of embedded systems. As well as giving students a full grounding in the Rust programming language, this module teaches delegates how to program a modern embedded microcontroller using real-time development tools. The examples and exercises are tuned to the practical requirements of embedded microcontroller programming. What will you learn? The syntax and semantics of the Rust language for embedded programming The principles of embedded software programming and real-time programming How to program an embedded microcontroller in Rust A practical introduction to real-time development tools How to debug a Rust program on an STM32F3 Discovery device How to access memory-mapped peripherals using Rust How to write interrupt handlers in Rust An introduction to Real Time For the Masses (RTFM) framework An introduction to low power software design Best practices for embedded programming

In this module we will learn to control IoT devices with the Google Assistant by building apps that integrate Smart functionality.

Before implementing deep-learning algorithms in this quarter, we will first familiarize ourselves with mathematical blocks of neural networks theory. We going to start by getting our hands dirty writing some simple TensorFlow 2.0 code in Rust. And then move on to advanced deep learning concepts applicable to IoT projects. This module will also cover some essential advantages of TensorFlow 2.0 to convince you it’s the deep-learning library of choice.

In last optional quarter we will discuss and implement an emerging aspect of the blockchain economy, machine-to-machine (M2M) transactions. We will cover, how machines can use IOTA blockchain to become autonomous market participants with their own bank accounts. We will then merge these blockcain concepts with artificial intelligence (AI) concepts learned in the previous quarters. These combine IoT, AI and Blockchain technologies allow machines in the Internet of Things to be able to lease themselves out, schedule and pay for their own maintenance, purchase their own replacement parts and keep their own transactional records, using blockchain.