Class-8 Projects

Objective: Teach students about AI’s role in automating household tasks.
Project: Build an AI-based smart home system that controls lights, fans, or other devices based on voice commands or sensor inputs.
Tools: Raspberry Pi, micro, or similar with sensors (motion, light, temperature), relays, and basic coding with Python.
Outcome: Students create a system that automates household devices, learning how AI can be applied to make everyday life easier.

Objective: Introduce students to autonomous systems.
Project: Build a robot that can navigate its surroundings using sensors and AI algorithms to avoid obstacles or follow a pre-defined path.
Tools: Raspberry Pi, micro, or Arduino with sensors (ultrasonic, infrared), and AI-powered libraries for obstacle avoidance or line-following.
Outcome: The robot moves autonomously based on input from its environment, showing how AI is used in robotics and autonomous systems.

Objective: Teach students about AI in healthcare applications.
Project: Create a system that monitors heart rate, temperature, and other health metrics using sensors and provides feedback or suggestions for maintaining good health.
Tools: Raspberry Pi or micro, health monitoring sensors (heart rate, temperature), and Python or block-based programming.
Outcome: The system tracks vital signs and uses AI algorithms to provide personalized health suggestions, giving students insights into AI’s role in medical technology.

Objective: Show how AI can monitor environmental conditions.
Project: Build a system that uses sensors to collect environmental data (air quality, humidity, temperature) and AI to analyze trends and provide recommendations for a cleaner environment.
Tools: Raspberry Pi or micro, environmental sensors (air quality, humidity), Python with machine learning libraries.
Outcome: The AI provides real-time feedback on environmental quality and trends, helping students understand how AI can help solve environmental challenges.

Objective: Teach students about facial recognition technology and its applications.
Project: Build a basic facial recognition system using a camera module and AI software. It can be used to unlock a device or identify different people.
Tools: Raspberry Pi with a camera module, OpenCV or other Python libraries for facial recognition.
Outcome: The system recognizes faces and performs actions based on the user’s identity, helping students explore the ethical and practical aspects of AI in security.

Objective: Demonstrate how AI can assist in education.
Project: Create an AI-powered language learning tool that listens to students’ pronunciation and gives feedback, or translates words and phrases in real-time.
Tools: Laptops/tablets, Raspberry Pi, Python with speech recognition and translation libraries (like Google Translate API).
Outcome: The tool helps students practice language skills, while learning how AI can be used in personalized education.

Objective: Help students understand AI image classification techniques.
Project: Train a machine learning model to classify objects (like fruits, animals, or vehicles) using images and gadgets like Raspberry Pi or Google Teachable Machine.
Tools: Raspberry Pi with a camera, or laptops/tablets with Teachable Machine.
Outcome: The system classifies images based on student-provided data, introducing them to AI in image recognition and machine learning.

Objective: Teach students how AI can be used for predictive modeling.
Project: Build a weather prediction model that collects temperature, humidity, and pressure data through sensors and uses machine learning algorithms to predict the weather.
Tools: Raspberry Pi with weather sensors, Python with machine learning libraries.
Outcome: The system predicts the weather based on real-time sensor data, demonstrating AI’s application in data analysis and forecasting.

Objective: Show students how AI can assist with mental health.
Project: Build a simple chatbot that interacts with users, offering support and advice based on mood analysis and pre-programmed responses.
Tools: Laptops/tablets, Python with natural language processing (NLP) libraries like NLTK or chatbot frameworks.
Outcome: The chatbot provides basic mental health advice, teaching students about the importance of AI in social applications.

Objective: Demonstrate AI’s role in creative fields like music.
Project: Use AI to help compose music by suggesting melodies, harmonies, or rhythms based on user input.
Tools: Laptops/tablets, Raspberry Pi, music composition apps with AI features (like AIVA or Google Magenta).
Outcome: Students create their own musical compositions with AI assistance, blending technology and creativity in a practical project.