Sensing and Actuation Paradigms

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From the course by University of California San Diego

Internet of Things: Sensing and Actuation From Devices

88 ratings

University of California San Diego

Internet of Things: Sensing and Actuation From Devices

88 ratings

Have you wondered how information from physical devices in the real world gets communicated to Smartphone processors? Do you want to make informed design decisions about sampling frequencies and bit-width requirements for various kinds of sensors? Do you want to gain expertise to affect the real world with actuators such as stepper motors, LEDs and generate notifications? In this course, you will learn to interface common sensors and actuators to the DragonBoard™ 410c hardware. You will then develop software to acquire sensory data, process the data and actuate stepper motors, LEDs, etc. for use in mobile-enabled products. Along the way, you’ll learn to apply both analog-to-digital and digital-to-analog conversion concepts. Learning Goals: After completing this course, you will be able to: 1. Estimate sampling frequency and bit-width required for different sensors. 2. Program GPIOs (general purpose input/output pins) to enable communication between the DragonBoard 410c and common sensors. 3. Write data acquisition code for sensors such as passive and active infrared (IR) sensors, microphones, cameras, GPS, accelerometers, ultrasonic sensors, etc. 4. Write applications that process sensor data and take specific actions, such as stepper motors, LED matrices for digital signage and gaming, etc.

From the lesson

Course 3 Lecture series

Before jumping into the lab section of this course, we would like to offer you a short lecture series. This lecture series will compliment everything you are about to do for the remainder of the course.

Introduction to the Lectures1:53

What's in Sensor6:38

Sensing and Actuation Paradigms5:21

Inspiration from Hollywood8:08

Discrete Signals and digital Signal Processing12:10

Life below the Nyquist (Advanced)7:05

Resolution, Bandwidth, and Power7:50

Meet the Instructors

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

So, I would like to talk briefly about the different ways we can

stitch these different blog diagrams.

And what we saw before, we started with the real world signals,

sensing and acqulation.

It doesn't have to be like that.

There are sometimes.

Real world phenomenon that we cannot directly observe.

So we start with activation first,

that is create some signal to change the real

world and then we go and sense what.

Changes we have made in the real world and

this will let us observe the parameters that we could not observe directly.

So let me give an example to illustrate what exactly I mean.

This is a pulse oximeter,

[COUGH] it's a medical device that was invented in the early 70s.

Very shortly between ten years, it became a standard issue in many healthcare and

fitness applications including anesthesia during surgeries,

respiratory problems or mountaineering or climbing Everest, so on and so forth.

The task is to see if all body parts are getting enough oxygen.

So we look at the arteries in the periphery, the finger or

the ear lobe and the heart pumps oxygen to the blood.

There is a pulsatile flow reaching the tissues.

So if you try and read the LED on one side and

you have a photodetector on the other side,

depending on the oxygen content the signal that the photo diode keeps changing.

In fact, in a pulse oximeter you have two LEDs.

One is a red LED and one is an infrared LED that is used

as a baseline ad this are lit alternatively, so

that you can look at the signal that comes out of the photodetector and

do some simple math to calculate the O2 level.

It is called SpO2, saturation of peripheral oxygen.

The invention of pulse oximeter and

transport many many innovations in anesthesia and surgical care.

So the point I'm trying to make is you could not directly

look at the oxygen in your blood, but by actuating first and

sensing later, you actually build a really clever system.

Here is another example, motion capture.

Again, this is also based on infrared cameras and sensing the reflections.

The connect and video games work like this.

They're many Hollywood animations that measure slight,

ever so slight, changes in the body movements that

are used in animations, Pixar and Disney movies.

[COUGH] In fact, for a useful IoT application,

sometimes you don't even need to have both sensing and the actuation parts.

In some cases, just desensing pipeline is adequate to

build a very useful application.

Typically in these cases, the recipient of the information is an expert in the dummy.

One of the examples is in the healthcare, in the ICU or hospital floors.

There are many, many parameters.

This is a multi parameter system that actually monitors the patients health.

You have the ECG, you have the respiratory rate,

you have the blood pressure, you have the temperature, so on and so forth.

Similarly on the actuation side,

you can build a very useful product without having

any of these sensing and this is the example for

the iPod, Pandora, e-reader.

In summary, we have actually looked at

the different sensing and actuation paradigms.

You do not need to have both the sensing and actuation or in that order.

You can have it reversed or you could have just one,

the sensing part or the actuation part.

So keep thinking about all of these different modes.

You can stitch these different blocks together as you get yourself

familiarized with the dragon board and interfacing different sensors and

keep thinking about how you would use these capabilities in your capstone or

to advance your ideas.

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