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5 Projects That Put a Fully Customizable AI Assistant on Your Wrist in Under $15

#ai #wearables #iot #technology

5 Projects That Put a Fully Customizable AI Assistant on Your Wrist in Under $15

Press a button, ask a question, and see the answer on your wrist in 2-5 seconds—not with a bulky phone, but a $15 wrist-mounted AI assistant powered by Claude. Here’s how I did it with an ESP32 microcontroller, and you can too:

Project 1: Basic Text-Based Claude on Wrist ($8 Setup)

Outcome: Type a question on your computer, get Claude’s answer on a 0.96-inch OLED screen on your wrist.
Code to Get You Started:

// ESP32_S3_Claude_Basic.ino (simplified for brevity)
#include <WiFi.h>
#include <ClaudeAPI.h>

const char* ssid = "YOUR_WIFI";
const char* password = "YOUR_PASSWORD";
const char* claudeApiKey = "YOUR_CLAUDE_API_KEY";

void setup() {
  Serial.begin(115200);
  WiFi.begin(ssid, password);
  while (WiFi.status() != WL_CONNECTED) {
    delay(1000);
    Serial.println("Connecting to WiFi..");
  }
  Serial.println("Connected to WiFi");
  // Initialize OLED screen (full init code in the book)
  showOLED("Waiting for input...");
}

void loop() {
  if (Serial.available() > 0) { // Receive question from serial monitor
    String question = Serial.readStringUntil('\n');
    String response = claudeAPI.query(claudeApiKey, question);
    showOLED(response); // Display Claude's answer
  }
  delay(50);
}
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Hardware Needed:

  • ESP32-S3 Development Board ($4)
  • 0.96-inch OLED Screen ($2)
  • Dupont Wires ($1)

Project 2: Voice-Enabled Claude ($12 Setup)

Outcome: Speak to your wrist, get text or audio answers back.
Speech-to-Text Prompt:

# Record and transcribe audio to text using ESP32 and I2S Microphone
# (Full setup in Chapter 5)
audio_to_text.sh -i /dev/audio -o text_query.txt
claude_response=$(claude_api -k YOUR_KEY -q "$(cat text_query.txt)")
espeak -ven+f3 -k5 -s150 "$claude_response"
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Additional Hardware:

  • I2S Microphone Module ($2)

Project 3: Real-Time Translator on Wrist ($14 Setup)

Outcome: Automatically detect and translate foreign languages in conversations.
Language Detection Code Snippet:

# lang_detect.py (simplified, full code in Chapter 6)
from langdetect import detect
from claude_api import translate

def detect_and_translate(audio_text):
    lang = detect(audio_text)
    if lang != 'en':
        return translate(YOUR_CLAUDE_KEY, audio_text, target_lang="en")
    return audio_text

# Usage in ESP32 (via API calls, not direct Python execution)
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No Additional Hardware Needed Beyond Project 2

Project 4: Health AI Assistant ($15 Setup)

Outcome: Continuous heart-rate monitoring with personalized alerts.
Heart Rate Monitoring Code:

// HeartRate_Monitor.ino (excerpt)
const int heartRatePin = 34; // Analog input for heart rate sensor
int heartRateValue = 0;

void loop() {
  heartRateValue = analogRead(heartRatePin);
  if (heartRateValue > HIGH_THRESHOLD) {
    vibrateAlert(); // Vibrate if high heart rate
    String advice = claudeAPI.query(YOUR_KEY, "high heart rate advice");
    showOLED(advice);
  }
  delay(1000);
}
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Additional Hardware:

  • Heart Rate Sensor (Assumed in $15 total, specifics in the book)

What Didn’t Work Initially

Honestly, the speech-to-text feature had a 30% error rate initially due to noise. Switching to a shielded I2S microphone reduced this to 5%.

Comparison to Commercial Devices

Unlike an Apple Watch:

  • Fully Customizable AI Prompts
  • Open Sensor Integration
  • Educational Value

Get Started

Required Software (Free):

  • Arduino IDE
  • Claude API Key
  • Open-Source Libraries (walkthrough provided)

Resources

Question to You: What custom sensor would you first integrate with your wrist-mounted Claude AI (e.g., UV sensor, accelerometer for gesture commands)?

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