School Buses Benefit Everyone | Boson Artificial Intelligence Starter Kit 06

0 2670 Easy


By the end of the lesson, students should be able to:

1. Understand the function of neural network

2. Complete the project under the guidance of teachers

3. Renovating the project through the transformation of the learned knowledge


*The parts in the red dotted box are non-essential, and you can implement the process according to the actual teaching schedule.

Materials Preparation


Computer with Mind+ software installed, BOSON Artificial Intelligence Starter Kit (Micro:bit*2, Expansion Board*1, Neurone Module*6, Ultrasonic Sensor*2, Smart Grayscale Sensor*2, Sound Sensor*2, Logic AND Module*2, Logic OR Module*2, Red LED Module*1)

*Students need to be grouped according to the number of BOSON Artificial Intelligence Starter Kits.


Textbook, pen, the vehicle module in the previous lesson, scissor, utility knife, double-side adhesive tape

*The tools and consumables required for the project can be freely selected.


Preface: This is the third lesson of School Bus Transformation, also the last lesson of the part “Initial decipherment of Artificial Intelligence”. After learning the previous 5 lessons, this lesson will help students reach a new level of understanding of artificial neural networks. Based on the previous two lessons, in this lesson, we are going to build a more complex school bus intelligent network to deal with more practical problems.


For reference: In this part, you can lead students to explain the phenomenon in practice through the knowledge and skills learned in the previous chapter, and then discover the driving problems of this project, disassemble the functional requirements and general steps, so as to initially clarify their own design ideas.

Intro Question: In order to drive safely, driverless vehicles have a very complex artificial intelligence control system. Can you choose one of the functions below and connect with the neurone module and artificial neural network to briefly explain how it works?


Driving Question: In the previous project, we implemented some functions of driverless driving. However, the practical situation is much more complicated. For example, stop when a gradually-approaching obstacle is recognized. In our project, only one speed situation is considered, when an obstacle approaches at other speeds, it can’t be recognized; when recognizing pedestrian's "slow down" voices, the vehicle will slow down. Voice commands such as “speed down”, “slow down”, and “stop” all have the effect of reducing the vehicle speed. But we have to consider the difference between dialect and Mandarin. How can we make our driverless car project "smarter"?

Function Decomposition:

Function 1: Identify two objects at different approaching speeds and realize the stopping effect;

Function 2: Recognize two different voices and realize the deceleration effect.


For reference: This session will help students sort out design ideas based on the lead-in session.

Design Ideas

Since a set of ultrasonic sensors and smart grayscale modules can recognize one approaching speed, and a sound sensor can recognize one decelerating voice, why don't we use more sensors to collect more characteristic data and build a more complex neuron module network, so that it can handle more complicated situations!

Structure Design


For reference: Since the difficulty of the project procedures in this section, teachers are required to lead students to complete them step by step.

1. Hardware Connection

2. Arrange Stage Scenes

Background: upload background-"lane 1.png", "lane 2.png"...... "lane 8.png"

Roles: upload role-"school bus.png", "car.sprite3", "accident.png", “you win.png”,“you lose.png”,“school.png”

3. Write Programs

Open Mind+, select “Online” mode.


Open another Mind+, select offline mode, and upload the program to another Micro:bit.


4. Adjustment
5. Hands-on Practice (Sample)


6. Debug


For reference: This part will ask students to rethink and share their works. You can remind them to complete this part from these aspects: how do you feel after finishing this project? Do you encounter any difficulties in making, and how do you overcome them; What do you think about artificial intelligence? Let two students share their work and ideas after a given time.


For reference: In this part, you can summarize the curriculum project by raising questions to let students think and discuss so as to recall the content of this lesson and deepen the understanding of the project.

Qusetion1: If three deceleration voices need to be recognized, please design a connection diagram.



Qusetion2: Talk about your understanding of neural networks.

Answer: "More people produce greater strength, more logs make a bigger fire.". When multiple neurone modules form a complex network, it becomes "intelligence".


For reference: At the end of this lesson, you can assign homework to students as an extension of the course.

Extension: Use as many single neuron modules as possible to make your school bus “smarter”!



Emergence is one of the most fascinating and wonderful phenomena in our universe. In a word, many small individuals interact to produce a large individual, and this large individual exhibits characteristic the small individuals that make it do not have. For example, it is an emergence phenomenon that water molecules gather to form snowflakes with regular shapes.


Although today's scientists have not deciphered "wisdom", we can see a glimpse from the emerging phenomenon. For example, the characteristic of a single ant in nature is with no intelligence. It has no brains, desires, and plans. But when many ants gather, they are smart. A colony of ants can form a complex structure. They show wisdom that a single ant does not possess in multiplying and building nests, foraging for food, launching war, self-defense and other behaviors. If we think of a neuron as one single ant, then the neural network is an ant colony. A large number of neurons are connected according to specific rules to form a neural network, and then wisdom is born.

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