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Week 02 Β· Sensors and Perception

Monday

Eyes and ears for computers
// How computers sense the world
⏱ about 15 min

Monday: Eyes and Ears for Computers

Nova zips over the sample table. Click! Her camera snaps a photo of a rock.

"So that is where the photo pile comes from," Rocket says.

Raven listens. "What do you notice? Nova just turned toward my voice."

Nova hovers closer. "Here is a hint," she says. "How do you see and hear? Computers need parts for that too."

Rocket reaches for his notebook. Time to list some parts!

Sensors pick up the world

You have eyes to see and ears to hear.

Computers sense the world with sensors.

A camera is a sensor that picks up light. It makes pictures.

A microphone is a sensor that picks up sound.

What a sensor picks up is called a signal.

Your bodyA computer sensorWhat it picks up
EyesCameraLight, to make pictures
EarsMicrophoneSound
MATCH THE SENSOR
  • Read the question.
  • Tap your answer.
Which sensor picks up sound?
Which sensor picks up light to make pictures?
Nova snapped a photo of a rock. Which sensor did she use?
StatementTrue or false?
A camera is a sensor.?
A microphone picks up light.?
What a sensor picks up is called a signal.?
Computers sense the world with sensors.?
WHY THIS EXERCISESensors are how a computer gets signals from the world.
What is the name for a part that picks up light or sound?
WHY THIS EXERCISESensors are the first step for any computer that senses the world.

Signals are not meaning yet

A camera picks up light. A microphone picks up sound.

But a signal by itself does not say what it is.

The computer still has to work out what the signal means.

This week, you will learn how that works.

SIGNAL OR MEANING?
  • Read the question.
  • Tap your answer.
A microphone picks up a loud sound. Is that a signal or a meaning?
Someone says, "That sound was a door closing." Signal or meaning?
Try it
Close your eyes for one minute. Listen.
Count how many different sounds your ears pick up.
Then name what made each sound.

Great listening, explorer! Tomorrow we learn how computers get meaning from signals.