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1. AI-Powered Object Detection
- Objective: Introduce students to object detection using AI.
- Project: Use a webcam or smartphone to train an AI model to recognize objects like fruits, school supplies, or animals using Google Teachable Machine.
- Tools: Laptop/tablet with a webcam, smartphones, or Teachable Machine.
- Outcome: Students train the AI model by feeding images and testing it in real-time to recognize objects.
2. AI-Based Weather Prediction
- Objective: Demonstrate how AI can predict weather patterns.
- Project: Students use data from the internet or sensors (like a temperature or humidity sensor connected to a Raspberry Pi) to create a simple weather prediction model.
- Tools: Raspberry Pi, sensors (temperature/humidity), and simple machine learning algorithms.
- Outcome: Students analyze the data and the AI gives weather predictions based on past trends and real-time data.
3. AI-Powered Voice Assistant
- Objective: Show how voice assistants work with AI.
- Project: Use Raspberry Pi with a microphone to create a simple voice assistant that can answer questions, perform calculations, or provide information about topics.
- Tools: Raspberry Pi, AIY Voice Kit or similar hardware, and basic coding software like Python.
- Outcome: The assistant will be able to respond to basic commands or answer questions about a chosen topic (e.g., math, science facts).
4. AI in Gaming
- Objective: Teach students about AI applications in games.
- Project: Build a simple game using Scratch where AI controls the behavior of non-player characters (NPCs). The AI can help an NPC avoid obstacles or react to the player’s actions.
- Tools: Scratch, laptops/tablets.
- Outcome: A functional game where AI influences the behavior of characters based on predefined rules or learning algorithms.
5. AI-Powered Emotion Detection
- Objective: Explore how AI can analyze emotions.
- Project: Use a camera to detect students’ facial expressions and classify their emotions using Google’s Teachable Machine.
- Tools: Laptops/tablets with a webcam, Teachable Machine.
- Outcome: The AI can recognize and display emotions like happiness, sadness, or surprise based on facial expressions.
6. AI-Driven Health Monitoring
- Objective: Introduce students to AI applications in health monitoring.
- Project: Use microor Raspberry Pi with a heart rate sensor to monitor a student’s heart rate and give feedback about their health.
- Tools: micro, Raspberry Pi, heart rate sensors.
- Outcome: The system can display heart rate data and use basic algorithms to give feedback like “healthy” or “needs rest.”
7. AI-Generated Art
- Objective: Demonstrate how AI can create art.
- Project: Students input drawings or patterns into an AI system that generates unique digital art based on their designs.
- Tools: Laptops/tablets, smartphones, AI art generation apps or online tools.
- Outcome: AI enhances or generates artwork based on student input, combining creativity with technology.
8. AI for Speech-to-Text
- Objective: Show how AI converts spoken language into text.
- Project: Create a project where students speak into a microphone, and the AI converts their speech into text using Python’s SpeechRecognition library.
- Tools: Laptops or Raspberry Pi with a microphone.
- Outcome: The AI system listens to spoken words and converts them into text in real-time, demonstrating speech recognition technology.
9. AI-Powered Smart Home Simulation
- Objective: Teach students about AI in smart homes.
- Project: Use microor Raspberry Pi to simulate a smart home system where students can control lights, fans, or sensors with voice commands or predefined inputs.
- Tools: Raspberry Pi, micro, sensors (like motion or light sensors), and output devices (like LEDs or fans).
- Outcome: The AI system controls home devices based on voice or sensor inputs, simulating a smart home environment.
10. AI in Sustainable Agriculture
- Objective: Show AI’s role in monitoring and optimizing plant growth.
- Project: Use microor Raspberry Pi to build a simple system that monitors soil moisture, light, and temperature for growing plants. AI can analyze the data and suggest actions to optimize plant growth.
- Tools: Raspberry Pi, sensors (for soil moisture, light, temperature).
- Outcome: The AI monitors environmental conditions and provides recommendations for watering or lighting the plant.
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