Specialization in a Nutshell

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Del curso dictado por University of California San Diego

Internet of Things: How did we get here?

663 calificaciones

University of California San Diego

Internet of Things: How did we get here?

663 calificaciones

Curso 1 de 6 en SpecializationInternet of Things

It is hard to imagine life without your Smartphone – you have come to rely on it so much – for your work; to stay in touch with family and friends; to capture and share those special moments; to find your way around in a new neighborhood. Did you ever wonder how and when all this happened? Or how and when GPS sensors came to be in your cell phone? In this course, we will explore the convergence of multiple disciplines leading to todays’ Smartphones. You will learn about the birth and evolution of Telephony Networks, Broadcast Networks (TV and Radio) and Consumer Electronics. We will discuss the impact of Internet, (multimedia) content, smartphones and apps on everyday lives. We will then look at how this emerging platform called the Internet of Things – wherein billions and trillions of devices communicating with each other and “the cloud” – could enable unprecedented, innovative products and services. Take this course if you want to understand what great new advances in mobile-enabled products will be coming our way! Learning Goals: This course provides a core grounding in how science and technology have developed to enable the Internet of Things – in a way appropriate for any learner. For those interested in developing further hands-on expertise in designing and developing for the Internet of Things, this course will provide a context to the discoveries and converging technologies that will springboard the next round of innovations. After completing this course, you will be able to: 1. Compare how the telephone system works (that is, peer-to-peer networks) with how media delivery works (that is, broadcast/multicast networks). 2. Explain the tradeoffs between circuit switched networks (that is, dedicated resources) and packet switched networks (that is, shared resources). 3. Tell interesting stories about key innovations that transformed the communications, entertainment and consumer electronics industries. 4. Explain how email, YouTube, SMS, etc. work. 5. Find resources for those wishing to do more of a “deep-dive” into the above topics.

De la lección

Future Outlook

Congratulations! You’ve made it to the last module in this course! At this point, you should know the history of the internet and many innovations that it has advanced with, but what is the Internet of Things anyway? That question and many more will be answered in this final course!

Introduction to Lesson 11:09

IoT: What the heck is it?8:36

Build your own IoT5:33

Specialization in a Nutshell6:23

Conoce a los instructores

Harinath Garudadri
Associate Research Scientist
Qualcomm Institute of Calit2, UC, San Diego
Ganz Chockalingam
Principal Engineer
Qualcomm Institute of Calit2, UC, San Diego

In this lesson, we're going to go over all the courses in this specialization,

as you know there are six courses.

You're watching Course 1.

So, let me kind of go over what's in each of these courses.

Let me switch the slides here.

Course 2, this is the Introduction to DragonBoard and the 96Boards ecosystem.

We'll show you all about waiting at the DragonBoard, unpacking,

installing the things you need,

and setting up, so it's all DragonBoard oriented.

This form is kind of the core of the specialization.

We'll also talk about the 96Boards specs to get the most of the on processors,

so it's a pretty detailed course.

Course 3, we'll kind of move away from the DragonBoard a bit,

it's about the Cloud Services.

Very soon you'll hit maximum processing power off the DragonBoard,

you can't do it on the board you have to off load processing to the cloud,

so we have chosen Amazon Cloud Services as to follow along in this course,

you're welcome to use other services.

Course 3 we're going to cover AWS.

How to set up on Amazon,

what are the services offered in Amazon,

all the image processing services.

In particular, we're going to cover the Amazon IoT SDK kit.

There are two parts to the kit.

One is the server kit and there is the client kit,

and you'll do a few projects in this specialization using the Amazon IoT SDK.

So that's course by itself where it's not,

we don't do too much on DragonBoard in Course 3 but it's a very useful course by itself,

it will get you up and running with Cloud Services.

So now, let's move to Course 4.

Course 4 and 5 got plenty of material,

two and three form the backbone of the specialization.

If you have finished two and three you'll be firing on all cylinders.

You've got all the kind of basics you need to kind of build your own IoT.

Three and four form offer some advanced concepts,

in particular Course 4, communication.

We do a lot of audio and MIDI.

MIDI stands for music instrument digital interface.

It's a protocol invented to kind of

make musical instruments communicate with each other in an easy fashion,

like computers and all that.

So we'll talk a lot about processing music signals in Course 4, using the DragonBoard.

Course 4 also forms the backbone of Capstone 1.

We'll come to what Capstone 1 is a little bit later but

we offer you all the fundamentals you need to deal with Capstone 1,

if you want to follow along.

Course 5 there's a bunch of stuff here.

It's multimedia in particular,

a lot about image processing and computer vision.

Some of the concepts we cover have to do with 2D signals.

Course 4 was mainly time series signals.

Course 5 deals with 2D signals like images.

We'll talk about sensing 2D signals of thd DragonBoard.

We'll also be using the Arduino GPU and Diggler computer vision also on DragonBoard,

we'll talk about how to use OpenCV

and we'll also touch upon deep learning on DragonBoard using Google TensorFlow.

At a higher level Course 4 is music related,

Course 5 image computer vision related,

so you can deal with a lot of image processing concepts in Course 5.

Finally, Course 6, Capstone.

We got two sample Capstones out there for you pretty small Capstones.

You don't of course have to follow what we offer there but it kind of

gives you the basics of what you learned in four and five in particular.

Capstone 1 is about sonification of sound.

What it is, is you are in front of a camera and it's kind

of processing an image and you can control qualities of your music using your hands.

You flick, for example,

you can do this to kind of bring the volume up or bend the page,

and it ties into the MIDI concept you learned in Course 4.

It also ties into the concepts in Course 5,

how to process images.

That's Capstone 1.

Capstone 2 is using Cloud processing.

In particular, we are going to use the Amazon IoT SDK.

It's about getting signals from

various sensors and these signals are flowing to the cloud from

the DragonBoard and you process those signals in

the cloud and then make some decisions based on that.

While we have chosen is biometrics,

not biometrics, I should say,

EKG signals like heartbeats,

other signals which we're not actually collecting

with a real EKG but we have a database of signals stored from real machines.

We're going to stream it from the DragonBoard to the cloud and in

the cloud AWS we're going to process these using readily available SDKs,

which makes inference from these time series signals.

For example, it can analyze your EKG,

see if you have any existing conditions like bundle branch block

or other kinds of abnormalities and it can give you the results in real time.

So we got two different flavors here so 2 is about using an Amazon IoT SDK.

It kind of fits in if you have projects where you have a lot of sensors,

data flowing to the server,

to the cloud, and we use the Amazon IoT SDK.

Capstone 1 has a different take, image processing,

music signal processing, and you can take ideas from these two Capstones and do your own.

We'll release all these to give you ideas about how it's

done and that kind of summarizes all the courses in this specialization. Thank you.

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