Tag Archives: Fusion AI Lab Kit

AI on the Edge LESSON 9: Make Your Raspberry Pi Talk with TTS

April 26, 2026 admin

In today’s lesson, we’re going to make a huge leap forward in giving our Raspberry Pi some real personality. We’re going to teach it how to talk using Text-to-Speech (TTS). Instead of just blinking LEDs or printing text to the screen, our Pi will now speak out loud with a clear, natural-sounding voice.

This is a really fun and important lesson because one of the main goals of this class is to build intelligent systems that can interact with us in more human ways. Being able to make your Raspberry Pi speak opens up all kinds of exciting possibilities — whether you want your robot to tell you what it sees, have your AI assistant read sensor data out loud, or just add some personality and humor to your projects.

In this video, I show you how to use the TTS capabilities on the SunFounder Fusion AI Hat. You’ll learn how to install and set up the TTS engine, speak simple sentences, change voices, and control when the Pi talks. We’ll also look at how to make the speech sound more natural and how to integrate it smoothly into your programs without freezing everything else.

By the end of this lesson, your Raspberry Pi will be able to speak clearly and confidently — which is going to make the rest of our AI on the Edge journey a lot more exciting. Voice output combined with voice input (which we’ll work on soon) is what turns a simple circuit into a real interactive AI companion.

So go ahead and grab your Fusion AI Hat, plug in a speaker, and let’s give your Raspberry Pi a voice! As always, I encourage you to code along with me in the video and then experiment. Try making it say funny things, read temperatures, announce when it detects a face — whatever sparks your creativity.

This is where your projects start to feel truly alive.

I’m really excited for you on this one — let’s make your Raspberry Pi talk!

This is the schematic we are using on these projects;

Fusion Hat Circuit Diagram — This is the circuit we will use moving forward in the class

This Schematic is explained in detail in LESSON #5.

Then this is the code we developed in today’s lesson.

from fusion_hat.adc import ADC
from fusion_hat.pwm import PWM
from fusion_hat.tts import Piper
from time import sleep
tts = Piper()
tts.set_model('en_US-amy-low')
potPin = 0
myPot = ADC(potPin)
redPin = 5
redLED = PWM(redPin)
rangeOld = 100

while True:
    potVal = myPot.read()
    writeVal=100*(potVal/4095) - .005
    if writeVal < 1:
        msg = "Your LED is Off"
        range = 0
    if writeVal >=1 and writeVal<10:
        msg = "Your LED is Brightness 1"
        range =  1
    if writeVal >=10 and writeVal<20:
        msg = "Your LED is Brightness 2"
        range=2
    if writeVal >=20 and writeVal<30:
        msg = "Your LED is Brightness 3"
        range=3
    if writeVal >=30 and writeVal<40:
        msg = "Your LED is Brightness 4"
        range=4
    if writeVal >=40 and writeVal<50:
        msg = "Your LED is Brightness 5"
        range=5
    if writeVal >=50 and writeVal<60:
        msg = "Your LED is Brightness 6"
        range=6
    if writeVal >=60 and writeVal<70:
        msg = "Your LED is Brightness 7"
        range=7
    if writeVal >=70 and writeVal<80:
        msg = "Your LED is Brightness 8"
        range=8
    if writeVal >=80 and writeVal<90:
        msg = "Your LED is Brightness 9"
        range=9
    if writeVal >=90 and writeVal<99:
        msg = "Your LED is Brightness 10"
        range=10
    if writeVal >=99:
        msg = "Your LED is full Brightness"
        range=11
    if rangeOld != range:
        tts.say(msg, stream = False)
    rangeOld=range
    redLED.pulse_width_percent(int(writeVal))
    sleep(.1)

from fusion_hat.adc import ADC

from fusion_hat.pwm import PWM

from fusion_hat.tts import Piper

from time import sleep

tts = Piper()

tts.set_model('en_US-amy-low')

potPin = 0

myPot = ADC(potPin)

redPin = 5

redLED = PWM(redPin)

rangeOld = 100

while True:

potVal = myPot.read()

writeVal=100*(potVal/4095) - .005

if writeVal < 1:

msg = "Your LED is Off"

range = 0

if writeVal >=1 and writeVal<10:

msg = "Your LED is Brightness 1"

range = 1

if writeVal >=10 and writeVal<20:

msg = "Your LED is Brightness 2"

range=2

if writeVal >=20 and writeVal<30:

msg = "Your LED is Brightness 3"

range=3

if writeVal >=30 and writeVal<40:

msg = "Your LED is Brightness 4"

range=4

if writeVal >=40 and writeVal<50:

msg = "Your LED is Brightness 5"

range=5

if writeVal >=50 and writeVal<60:

msg = "Your LED is Brightness 6"

range=6

if writeVal >=60 and writeVal<70:

msg = "Your LED is Brightness 7"

range=7

if writeVal >=70 and writeVal<80:

msg = "Your LED is Brightness 8"

range=8

if writeVal >=80 and writeVal<90:

msg = "Your LED is Brightness 9"

range=9

if writeVal >=90 and writeVal<99:

msg = "Your LED is Brightness 10"

range=10

if writeVal >=99:

msg = "Your LED is full Brightness"

range=11

if rangeOld != range:

tts.say(msg, stream = False)

rangeOld=range

redLED.pulse_width_percent(int(writeVal))

sleep(.1)

AI On the Edge, Tutorial

AI on the Edge LESSON 7: Homework Solution for Dimmable LED

April 18, 2026 admin

In Lesson 6, I gave you a homework challenge: build a dimmable LED using a potentiometer. In today’s Lesson 7, we go through the solution together step-by-step.

This lesson is all about taking analog input from a potentiometer and converting it into smooth PWM output to control the brightness of an LED. It’s a very practical project because it teaches you how to read real-world analog values and turn them into useful control signals — skills we’ll use again and again as we build smarter AI-powered projects.

In the video, I walk you through the complete working code. You’ll see how we read the potentiometer value (0 to 4095), convert that raw number into a proper brightness percentage using a bit of math (with a nice logarithmic curve so the brightness feels natural to the human eye), and then send that value to the LED using PWM. The result is a very smooth, responsive dimmer that feels professional.

Even though this seems like a simple project, it’s actually an important stepping stone. Understanding how to read sensors and smoothly control outputs is fundamental to building real AI on the Edge systems — whether you’re controlling motors, adjusting screen brightness, or varying the speed of a robot based on sensor input.

By the end of this lesson, you should have a solid understanding of how to combine the ADC (Analog to Digital Converter) with PWM output, and more importantly, how to think about mapping real-world inputs to useful outputs.

So if you did the homework, great job! If you got stuck, don’t worry — we go through the full solution together. And as always, I strongly encourage you to take the code and make it your own. Try changing the response curve, add multiple LEDs with different colors, or combine it with things we’ve learned in earlier lessons.

This is the kind of foundational hardware skill that will serve you well as we continue moving deeper into the AI on the Edge class. You’re doing great — keep going!

We are still using the schematic from our earlier project.

In this lesson, this is the code which we came up with:

#!/usr/bin/env python3
from fusion_hat.adc import ADC
from fusion_hat.pwm import PWM
from time import sleep
import math
potPin=0
myPot = ADC(0)
redPin=5
redLED=PWM(redPin)

while True:
    potVal = myPot.read()                     # 0 to 4095
    writeVal=100**(potVal/4095)-.005
    redLED.pulse_width_percent(int(writeVal))
    print(potVal,writeVal)
    sleep(0.1)

#!/usr/bin/env python3

from fusion_hat.adc import ADC

from fusion_hat.pwm import PWM

from time import sleep

import math

potPin=0

myPot = ADC(0)

redPin=5

redLED=PWM(redPin)

while True:

potVal = myPot.read() # 0 to 4095

writeVal=100**(potVal/4095)-.005

redLED.pulse_width_percent(int(writeVal))

print(potVal,writeVal)

sleep(0.1)

AI On the Edge

AI on the Edge LESSON 1: Introduction and Class Overview

March 29, 2026 admin

Welcome to our all new AI on the Edge class! I will need you to buckle up, get your hardware together, and get ready to teach AI who is boss! We will be using a Pi 5, and the Fusion AI Lab kit. I will show links to the hardware below. In today’s lesson I describe the Class Introduction, and will show you some demos of the types of projects we will be doing. You will either Drive AI or your will be Destroyed by AI. Don’t be one of the ones who will be eaten by it

The Future will Belong to Those Who Can Drive AI

Guys, get your gear, and make sure you end up on the right side of the Dystopian future that awaits the world.

I have provided Amazon links, so you can order everything in the same place

You Will need a Raspberry Pi 5
Order Pi 5

You will need a heat sink and fan
Order Heat Sink and Fan

You Will Need the Fusion AI Lab Kit
Order Fusion AI Lab Kit

You Will Need a 25 Watt Power Supply
Order Power Supply

You Will Need a Micro HDMI Cable
Order Micro HDMI Cable

You Will Need a Keyboard and Mouse
Order Wireless Keyboard and Mouse

This isn’t just another Raspberry Pi class. This is a complete journey where we’re going to take the powerful Raspberry Pi 5, combine it with the SunFounder Fusion AI Lab kit, and build real, practical, intelligent systems that run completely on the edge — no cloud, no internet required.

In this class, you’re not going to just learn how to blink an LED or run someone else’s pre-made script. You’re going to learn how to build smart machines that can see, listen, speak, think, and act in the real world. We’re going to combine computer vision, voice recognition, speech synthesis, sensor reading, motor control, and modern AI techniques — all running locally on your Raspberry Pi 5.

Over the course of this series, you will learn how to:

Capture and process live video from the Raspberry Pi Camera
Detect faces and track objects in real time using MediaPipe and OpenCV
Control hardware with voice commands
Make your Raspberry Pi speak with natural-sounding Text-to-Speech
Build smooth, responsive control systems using threading
Use displays like the SSD1306 OLED to show live information
Combine everything into impressive AI-powered projects

This class is designed for makers, students, hobbyists, and engineers who want to move beyond basic tutorials and start building real intelligent edge devices. Whether you dream of building smart robots, autonomous monitoring systems, interactive AI companions, or just want to gain serious skills in modern embedded AI, this class is for you.

I’m going to teach this the way I always do — step by step, clearly, and with lots of hands-on projects. We’ll start with the fundamentals and gradually build up to more advanced and exciting projects as the class progresses.

If you’ve ever wanted to move from “playing with the Raspberry Pi” to “building truly intelligent systems,” then you’re in the right place. This is going to be a fun, challenging, and incredibly rewarding journey.

So if you’re ready to stop just watching AI videos and start building your own AI on the edge… then buckle up, because we’re about to do exactly that.

Welcome to the class! I’m really glad you’re here. Let’s get started!

Technology Tutorials

Tag Archives: Fusion AI Lab Kit

AI on the Edge LESSON 9: Make Your Raspberry Pi Talk with TTS

AI on the Edge LESSON 7: Homework Solution for Dimmable LED

AI on the Edge LESSON 1: Introduction and Class Overview

Making The World a Better Place One High Tech Project at a Time. Enjoy!