This court will carry you through the construction of a control system, that deliverable is a terrorism
controller.
Along the way, you learn a great deal about useful technologies such as the node rate, programming,
environment and and cut.
Ideally, you want to complete this course because you want to learn new trade and market it and extend
your existing knowledge of the Espiritu and the Raspberry Pi.
Consider this project as a powerful tool because it provides you with clear and verifiable objectives
in this lecture of talk about the deliverables so that you know what you've built and the main learning
outcomes and also talk about the skills that you will need to have before you begin.
Let's start with a project deliverable by the end of this project, you have created a control system
for a terrarium.
A terrarium is simply a container in which you add some soil and a small plant.
Personally, my motivation for this project was not the terrorism itself, I'm not very good with plants
and only have limited interest in being a gardener.
But when I combined plants with technology, things became much more interesting.
I decided to do this project because it gave me the opportunity to work with several technologies that
I find very interesting.
And more about this in a moment.
That deliverable of the project is that the radium controller, which consists of the hardware and the
software, you can see the hardware in the photo in this slide implemented on a breadboard.
You can also choose to implement it on a piece of me that I've designed.
The software part of the controller consists of the main logic implemented in Node Red and the E.S.P
32 sketch note read is where all the decision making and logging takes place and the E.S.P 32 sketch
is simply there to report sensor values and execute decisions from note.
Read the layer that connects the two software components together is the market mosquito broker.
OK, now that you know what you're about to build, I'll explain what you learned along the way, which
I think is a lot more important.
You learn how to use note, read, note, read is a powerful graphical programming environment, it's
built on note.
Dautrich is a JavaScript framework from where it got its name.
Node read is very good in enabling hardware devices, small and large APIs and all kinds of online services
to work together.
I found that it's a learning curve was relatively gentle, and once I got my head around how flows are
assembled, configured and executed, I was able to quickly create prototypes because node red is lightweight.
It runs perfectly well on any Raspberry Pi, even the original in this project.
I used an old Raspberry Pi to that I had forgotten in one of my drawers and uncounted no issues at all
installing the new Raspberry Pi and running node red on it.
Notar it actually comes with the Raspberry Pi OS, so you don't even need to install it.
By going through this project, you'll become skilled in using node rate in a variety of control projects.
You learn how to use the Raspberry Pi as the brain of these projects and implement elaborate control
flows.
As I mentioned, Node Red is designed to be light on resources so that it can be used on low powered
computers.
It's also designed to work well with it.
A transport system that like node red is very light on resources as well.
First, have a look at mentality now, nudity is a way of messaging that allows clients to talk to each
other using the public and subscribe model.
The idea is simple.
If a client wants to send data to another client, it will publish the data to a topic that is maintained
by the broker.
Think of a topic as an address.
The client essentially will post or publish the data to this address.
When another client wants to get the data, it will subscribe to the same topic.
The mediated broker operates as the intermediary between publishing and subscribing clients.
Think of it as the server in this set up.
Many clients can subscribe or publish to the same topic, making it possible to design all kinds of
topologies you can think of.
The military Berocca sits in the middle of these communications when a client publishes data to a topic,
the broker will immediately push it to any client that has subscribed to the same topic for the clients.
This means total freedom from having to maintain information about who that data should go to as an
extension for us, the terrorism control designers, we don't have to worry about programming complicated
client relationships in the note read flow or the ability to sketch.
All we need to do is to know which topic a client should publish or subscribe to and the broker will
take care of the messaging.
And Quiddity is a technology that is very useful to Iot projects.
And by completing this Tyrolean project, you'll get hands on experience in using it.
And with no trade, you have a complete solution for control and messaging between lightweight clients.
Because and quiddity is lightweight, it works very well on low power.
I do not like the UNO or the more powerful E.S.P 32.
Although in this project, we are using the E.S.P study to mainly because I wanted a simple way to connect
to my Wi-Fi network.
You can use the exact same knowledge to implement encoded messaging in any arduino.
A project gives us an opportunity to branch out and explore.
While my primary learning objectives were not red, and could it be a more complete deliverable required
adding additional components?
I decided to use Google's drive and sheet APIs and if this and that as representative technologies of
what is available to make us right now, both technologies are mature and very useful.
No fluff there, of course, not yet made it easy to interface my float with both.
Integrating these two in the terrorism controller project made the project itself much more complete,
but also proved to me that there is massive potential for growth.
I feel that I'm only confined by my imagination and time, for example.
Think about what might be possible if I somehow integrate Tancer flow in my terrorism controller project.
Tenzer Flow is a public service by Google for creating machine learning models on the cloud.
Imagine using tenso offload technology to get artificial intelligence to learn using sensor data from
your terrarium, which can then be used to automatically control it for optimal growth of your plant.
Many of the elements of utilizing technologies such as tends to flow are same or very similar to using
a regular Google API or if this and that.
Last, what do you need to know before starting this project, so to complete this project, you do
need to be comfortable with a few technologies and I have listed the minimum knowledge requirements
in this slide if you are watching this video.
Chances are that you are already insured.
If you completed my two other courses, E.S.P 32 for busy people and Raspberry Pi full stack, then
you are ready to start with this new project and challenge.
But if not, I suggest that you do some work on these two courses.
First, you don't need to complete them, but at least go through the first three or four sections to
get up to speed with things such as installing the operating system on the Raspberry Pi, getting comfortable
with the command line and understanding how to use the Arduino idea with the E.S.P 32.