Class-7 Projects

Objective: Teach students about object tracking using AI.
Project: Create an AI-powered camera using Raspberry Pi that can track moving objects, such as a ball or a toy car.
Tools: Raspberry Pi, camera module, pre-installed OpenCV and Python libraries.
Outcome: The camera follows the movement of objects in real-time, introducing students to AI applications in surveillance and robotics.

Objective: Introduce students to AI-powered language translation tools.
Project: Build a basic language translator that converts speech or text from one language to another using AI-powered APIs.
Tools: Laptops/tablets, Raspberry Pi with a microphone, Google Translate API.
Outcome: The system can recognize spoken sentences or typed text and translate them into another language, helping students understand the concept of natural language processing.

Objective: Show how AI can be applied to monitor and predict weather patterns.
Project: Build a weather station that uses AI to predict local weather conditions based on data from temperature, humidity, and pressure sensors.
Tools: Raspberry Pi, weather sensors (temperature, humidity, pressure), Python with machine learning libraries.
Outcome: The AI analyzes the sensor data to predict weather changes, providing real-time weather forecasts for students.

Objective: Explore gesture recognition and its applications.
Project: Use a camera or sensors to create a system that recognizes hand gestures, which students can use to control lights, music, or games.
Tools: Raspberry Pi with a camera or microwith accelerometer, Python (OpenCV or machine learning libraries).
Outcome: Students perform hand gestures, and the system responds by performing specific tasks, introducing them to the field of human-computer interaction.

Objective: Teach students about self-driving cars and their reliance on AI.
Project: Create a basic self-driving car using a robot kit and AI to avoid obstacles or follow lines on the ground.
Tools: Raspberry Pi or micro, robotics kit, sensors (ultrasonic for distance detection), Python.
Outcome: The car can navigate through an obstacle course or follow a path autonomously using AI-powered decision-making.

Objective: Demonstrate how AI is used to monitor and optimize farming.
Project: Use sensors to monitor soil moisture, temperature, and light conditions. The AI provides recommendations for watering or adjusting the environment for optimal plant growth.
Tools: Raspberry Pi or micro, sensors (soil moisture, temperature, light).
Outcome: The system collects data and uses AI to suggest actions to improve plant health, teaching students about AI’s role in sustainable agriculture.

Objective: Help students understand AI in communication systems.
Project: Build a school chatbot that can answer common questions about homework, school events, or class schedules.
Tools: Laptops/tablets, Python (NLP libraries), or use Scratch with AI extensions.
Outcome: The chatbot can answer questions and assist students with daily school-related queries, demonstrating AI’s role in automating communication.

Objective: Introduce students to AI image classification techniques.
Project: Train a model to classify different types of images, such as animals, plants, or vehicles, using a gadget like Raspberry Pi or Google Teachable Machine.
Tools: Raspberry Pi with a camera, or laptops/tablets with Teachable Machine.
Outcome: Students upload images and the AI categorizes them, showing how AI can be trained to recognize objects.

Objective: Introduce students to AI applications in health and fitness.
Project: Build a fitness tracker using Raspberry Pi or microthat monitors physical activity, heart rate, and suggests exercises based on the data.
Tools: Raspberry Pi or microwith sensors (accelerometer, heart rate), Python or visual programming tools.
Outcome: The tracker analyzes movement and heart rate, using AI to recommend personalized fitness routines.

Objective: Show how AI can assist in creative processes like music composition.
Project: Use AI to generate music or assist students in composing a simple melody based on their input or preferences.
Tools: Smartphones/tablets with AI music composition apps or Raspberry Pi with speakers.
Outcome: Students provide a melody or rhythm, and the AI generates accompanying music or enhances their creation, combining creativity with AI.