Lesson: How Does a Light Sensor Work?

Contributed by: GK-12 Program, Computational Neurobiology Center, College of Engineering, University of Missouri

Three images: A photo shows an illuminated lamp next to a sofa in a dark room. A cutaway side-view diagram of the human eye shows a light beam entering through the pupil, bending at the lens and focusing at the back of the retina. A hand holds a credit card, ready to slip it into an ATM slot on a wall.
Engineers have used their understanding of how the human eye (our light sensors) works to design electronic light sensors.
copyright
Copyright © (left, bottom) 2004 Microsoft Corporation, One Microsoft Way, Redmond, WA 98052-6399 USA. All rights reserved; (right) National Eye Institute http://office.microsoft.com/en-us/images/results.aspx?qu=lamp&ex=1#ai:MP900448314|mt:2| http://www.nei.nih.gov/healthyeyes/problems.asp http://office.microsoft.com/en-us/images/results.aspx?qu=credit+card&ex=1#ai:MP900149068|mt:2|

Summary

Students learn more about how light sensors work, reinforcing their similarities to the human sense of sight. They look at the light sensing process—incoming light converted to electrical signals sent to the brain—through the human eye anatomy as well as human-made electrical light sensors. A mini-activity, which uses LEGO® MINDSTORMS® NXT intelligent bricks and light sensors gives students a chance to investigate how light sensors function in preparation for the associated activity involving the light sensors and taskbots. A PowerPoint® presentation explains stimulus-to-response pathways, sensor fundamentals, and details about the LEGO light sensor, including its two modes of gathering data and what its numerical value readings mean. Students take pre/post quizzes and watch a short online video. This lesson and its associated activity enable students to gain a deeper understanding of how robots can take sensor input and use it to make decisions via programming.
This engineering curriculum meets Next Generation Science Standards (NGSS).

Engineering Connection

Biological engineers and neuroscientists perceive the human body as a functioning, controlled system, similar to a robot. More and more findings show that mathematical principles similar to those used in robotics are extremely useful or even necessary for a complete understanding of the human body. Through comparison of their similarities, students strengthen their understanding of the functioning of both human and robotic sensors. Light sensors are being used in all sorts of devices. For instance, when you scan your credit card to buy groceries, a light sensor reads the credit card numbers. Cameras continuously monitor activity in stores and banks. The cameras on cell phones are light sensors, too.

Pre-Req Knowledge

Learning Objectives

After this lesson, students should be able to:

  • Describe how light sensors work.
  • Compare electrical light sensors to human eyes.
  • Program the LEGO MINDSTORMS NXT robot with the light sensor.
  • Provide a basic explanation of how sensors are integrated into robots via careful programming.

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Educational Standards

Each TeachEngineering lesson or activity is correlated to one or more K-12 science, technology, engineering or math (STEM) educational standards.

All 100,000+ K-12 STEM standards covered in TeachEngineering are collected, maintained and packaged by the Achievement Standards Network (ASN), a project of D2L (www.achievementstandards.org).

In the ASN, standards are hierarchically structured: first by source; e.g., by state; within source by type; e.g., science or mathematics; within type by subtype, then by grade, etc.

  • Use argument supported by evidence for how the body is a system of interacting subsystems composed of groups of cells. (Grades 6 - 8) Details... View more aligned curriculum... Do you agree with this alignment?
  • Gather and synthesize information that sensory receptors respond to stimuli by sending messages to the brain for immediate behavior or storage as memories. (Grades 6 - 8) Details... View more aligned curriculum... Do you agree with this alignment?
  • Various relationships exist between technology and other fields of study. (Grades 3 - 5) Details... View more aligned curriculum... Do you agree with this alignment?
  • Knowledge gained from other fields of study has a direct effect on the development of technological products and systems. (Grades 6 - 8) Details... View more aligned curriculum... Do you agree with this alignment?
  • Describe how new technologies have helped scientists make better observations and measurements for investigations (e.g., telescopes, magnifiers, balances, microscopes, computers, stethoscopes, thermometers) (Grade 4) Details... View more aligned curriculum... Do you agree with this alignment?
  • Describe how new technologies have helped scientists make better observations and measurements for investigations (e.g., telescopes, electronic balances, electronic microscopes, x-ray technology, computers, ultrasounds, computer probes such as thermometers) (Grade 5) Details... View more aligned curriculum... Do you agree with this alignment?
  • Explain the interactions between the nervous and muscular systems when an organism responds to a stimulus (Grade 8) Details... View more aligned curriculum... Do you agree with this alignment?
Suggest an alignment not listed above

Introduction/Motivation

(Be ready to show students the 17-slide How Does a Light Sensor Work? Presentation, a Microsoft® PowerPoint® file, to teach the lesson, as well as a computer/projector with Internet access to show a short online video. In advance, make copies of the Light Sensor Pre-Quiz and Light Sensor Post-Quiz, one each per student, provided as attachments and slides. For a mini-activity, student pairs use LEGO robot components to experiment with light sensors.)

How do we see using our eyes? How do you think a robot light sensor works? Let us consider these questions in detail. We will explore the principles that make light sensors work.

This will prepare you for an activity during the next class. You will program a LEGO robot with a light sensor to follow a flashlight. This means that as the flashlight moves, the robot follows it! Let's get started.

(Continue by showing the presentation and delivering the content in the Lesson Background section.)

Lesson Background and Concepts for Teachers

Present the lesson using the content provided in the slide presentation, as described below. The quizzes are embedded in the presentation if you wish to go through them as a class. During the lesson, students engage in a mini-activity (slides 13-14) that requires the following for each student pair:

How Does the Light Sensor Work? Presentation Outline (Slides 1-8)

  • Administer the pre-quiz by handing out paper copies; the quiz is also on slide 2. The answers are provided for the teacher on slide 3 for discussion after students have completed the quiz.
  • Tell students that after a brief review of the "stimulus-sensor-coordinator-effector-response" framework using the human eye as a sensor, they will do a mini-activity that shows them how light sensors function.
  • (slide 4) Explain the "stimulus-sensor-coordinator-effector-response" framework. Expect students to be able to understand the idea of a sensing element (eye), and then the transmission of the signal to the brain (via the nervous system).
  • Give students a few minutes to think of and write down how a stimulus-to-response sequence might be implemented in a robot. An example answer is provided on the post-quiz answer key on slide 16. Review student answers as a class.
  • Using slides 5-7, explain the eye anatomy and function of the human sense of sight. Talk specifically about the sensing elements in the eye—the rods and cones—and how signals from the rods and cones are sent to the brain, which integrates all of the signals to make sense of what is being seen (slide 6).
  • Make sure students understand the human sensing process of the eye: Incoming light is refracted or made to change direction by the cornea, the outermost part of the eye. This light is directed through the pupil, which is a hole through which it can pass. The surrounding muscular tissue in the iris (the colored part of the eye) controls the pupil size. The light that enters the back of the eye through the pupil is redirected by the eye's lens, to receptors in the back of the eye that convert light into electrical signals. The two main types of sensing elements in the eyes, or photoreceptors, are rods and cones. Rods are concentrated in the sides of the eye and detect the presence of objects in poor light. Cones are concentrated in the middle of the eye and detect details and colors in good light. The rods and cones send electrical signals through the optic nerve to the brain.
  • Emphasize the "conversion" or "transduction" function of this human sensor, that is, converting light to electrical impulses that are sent via the nerves (optic nerve in this case). This is a key concept in sensing, so make sure students grasp it.
  • As a summary, have students watch a two-minute video, "Sense of Sight—How Human Eyes Work," (link provided on slide 8).

What Is the Structure of the Light Sensor? Presentation Outline (Slides 9-17)

  • (slide 9) Review how robotic sensors work in general.
  • (slide 10) Explain briefly the principle behind light sensors, emphasizing that the LEGO NXT light sensor only senses brightness and not specific colors.
  • (slide 11) Hold up a LEGO NXT light sensor to show students the two bulbs poking out at the front end. The one on top is a phototransistor that measures light intensity. The one on the bottom is a light-emitting diode (LED) transmitter, which sends out a bright red light.
  • Go on to explain how the NTX light sensor's ability to sense light brightness works in two different ways: 1) it can detect the amount of ambient light, and 2) it can send out light and detect how much of that light is reflected back. In both cases, it detects the amount of brightness and reports it as a numerical value.
  • Show the graphics on slide 12 to make sure students understand what the NXT sensor "sees," before starting the mini-activity.
  • For the mini-activity, divide the class into pairs and give each pair a LEGO intelligent brick connected to a LEGO light sensor (see equipment setup on slide 1).
  • Direct student pairs to follow the instructions on slides 13-14 to experiment with the 1) reflected light mode, 2) ambient light mode, 3) and the Try Me option. Have them test the brightness of various colors and surfaces that they can find in the classroom. Have them test the ambient light in different areas of the classroom. Have them write down their observations and take notes about what they learn about how the sensor works. Doing this gives students an idea of how the sensor is calibrated and a deeper understanding of the intelligent brick's "Try Me" option. Understanding the different modes and how to read the light sensor measurements is helpful for students to know when programming LEGO robots. Wrap up the mini-activity by asking the class the questions provides in the Assessment section.
  • Administer the post-quiz by handing out paper copies; the quiz is also on slide 15. The answers are provided on slide 16. This concludes the lesson. Slide 17 contains vocabulary terms and definitions. Next, conduct the associated activity.

Vocabulary/Definitions

peripheral: Surrounding.

sensor: A device that converts one type of signal to another; for instance, the speedometer in a car collects physical data and calculates and displays the speed the car is moving.

transducer: Another term for a sensor.

visual: Related to sight.

Associated Activities

  • Follow the Light - Students program LEGO MINDSTORMS NXT robots to follow the movement of flashlights. They gain more experience in programming, as well as stronger understanding of how light sensors work and how they can be used in robotics, as well as other engineered technologies.

Lesson Closure

Our human eyes detect light and convert information from the light into electrical signals that are sent to our brains. Similarly, the LEGO MINDSTORMS NXT light sensor detects the brightness of light it receives and converts it to a numerical value as a percentage of the maximum brightness it can detect. Then it sends this signal to the intelligent brick, which is the equivalent of a brain. We looked at both of these in a "stimulus-sensor-coordinator-effector-response" framework, which is used commonly in engineering for a variety of systems. So, you have learned some basics of engineering now!

Attachments

Assessment

Pre-Lesson Assessment

Pre-Quiz: Administer the three-question Light Sensor Pre-Quiz (also on slide 2) to gauge students' prior knowledge about the light sensor in humans, as well as engineered systems that use light sensors. Have students answer as best as they can. Answers are provided in the Light Sensor Pre-Quiz Answer Key (and on slide 3).

Post-Introduction Assessment

Hands-On Learning: Observe students as they engage in the mini-activity described on slides 13-14. Make sure all pairs are following the slide instructions to experiment with the light sensor and its two different modes: ambient light and reflected light. Question individual students to verify that they understand how the light sensor works. Ask the students: Which mode are you using now? What happens in this mode? How is it different from the other mode? What does a higher number indicate? A lower number? Zero?

Investigation Wrap-Up: Wrap up the mini-activity by asking the class some questions to verify their knowledge gained in preparation for the associated activity:

  • What does the NXT light sensor measure? (Answer: The brightness or intensity of light.)
  • What does the light sensor do with this information? (Answer: It converts it to a numerical value as a percentage of the maximum brightness it can detect. Then it sends this signal to the intelligent brick/computer.)
  • Which is the brighter light—one that measures a higher number or a lower number? (Answer: Higher numbers indicate brighter lights, as a percentage of the maximum light that the sensor can read.)
  • What is the difference between the ambient light mode and the reflected light mode? (Answer: The ambient light mode uses the top bulb to sense the amount of light that exists around it. The reflected light mode sends out light from the lower bulb and senses how much is reflected back by any object or surface in front of it. Both report the amount of light detected in a numerical value, a percentage.)
  • Can the NXT light sensor tell you if a color is orange or blue? (No)
  • What are some of the readings you obtained for different colors and surfaces you tested? (Listen to student answers. Different colors reflect light differently.)
  • What are some of the readings you obtained in different areas of the room? (Listen to student answers.) What were readings by the window, under a table, in a corner?
  • What can the light sensor detect? (Answers: It can distinguish between light and darkness, read the light intensity in a room, and measure the light intensity on colored surfaces.)

Lesson Summary Assessment

Post-Quiz: Administer the Light Sensor Post-Quiz (also on slide 15) to assess student understanding, as well as how much they learned during the course of the lesson. Quiz answers for the teacher are provided on the Light Sensor Post-Quiz Answer Key (and on slide 16).

Additional Multimedia Support

NXT robots and sensors: http://mindstorms.lego.com/eng/Overview/default.aspx

What is a transducer? http://en.wikipedia.org/wiki/Transducer

What is a sensor? http://en.wikipedia.org/wiki/Sensors

List of sensors http://en.wikipedia.org/wiki/List_of_sensors

Compare the parts of a camera to the human eye, WikiAnswers: http://wiki.answers.com/Q/Compare_the_parts_of_a_camera_to_the_human_eye

How Your Eyes Work (interactive eye anatomy diagram), American Optometric Association: http://www.aoa.org/x6024.xml

How Your Eyes Work, Kids' Health, Women's and Children's Health Netowrk: http://www.cyh.com/HealthTopics/HealthTopicDetailsKids.aspx?p=335&np=152&id=1730

Contributors

Srijith Nair, Pranit Samarth, Satish S. Nair

Copyright

© 2013 by Regents of the University of Colorado; original © 2013 Curators of the University of Missouri

Supporting Program

GK-12 Program, Computational Neurobiology Center, College of Engineering, University of Missouri

Acknowledgements

This curriculum was developed under National Science Foundation GK-12 grant no. DGE 0440524. However, these contents do not necessarily represent the policies of the National Science Foundation, and you should not assume endorsement by the federal government.

Last modified: July 20, 2017

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