Class-10 Projects

Objective: Teach students about AI and autonomous systems.
Project: Build a small self-driving car prototype using sensors and AI for decision-making. The car can navigate through an obstacle course or follow a specific path.
Tools: Raspberry Pi or Arduino, sensors (ultrasonic for obstacle detection), motors, camera module, and AI algorithms for decision-making.
Outcome: The car autonomously navigates a track or avoids obstacles, showing students how AI is used in real-life self-driving vehicles.

Objective: Introduce students to facial recognition and AI’s application in security systems.
Project: Create a security system that uses facial recognition to identify authorized users and deny access to unauthorized individuals.
Tools: Raspberry Pi with a camera module, OpenCV, Python, and facial recognition libraries (such as Face_recognition or Dlib).
Outcome: The system identifies faces and allows or denies access based on a pre-trained database, helping students understand how AI is applied in security and privacy.

Objective: Show students how AI can predict equipment failures in industrial applications.
Project: Build a predictive maintenance system that monitors machine vibration, temperature, or noise to predict when the machine is likely to fail.
Tools: Raspberry Pi or micro, sensors (vibration, temperature), and machine learning models for predictive analysis.
Outcome: The system collects data from the machine and uses AI to predict maintenance needs, demonstrating how AI can improve operational efficiency in industries.

Objective: Teach students how AI can be used to automate household tasks.
Project: Build a smart home system where lights, fans, or appliances are controlled by voice commands or automated using environmental data (temperature, motion detection).
Tools: Raspberry Pi, micro, relays, motion or temperature sensors, and voice recognition tools.
Outcome: The AI system automates tasks based on inputs from sensors or voice commands, providing students with insights into AI-powered IoT systems.

Objective: Show students how AI can analyze text data to determine sentiment.
Project: Build a sentiment analysis tool that collects data from social media or reviews and uses AI to classify the sentiment (positive, neutral, negative).
Tools: Laptops/tablets, Python with natural language processing (NLP) libraries (such as NLTK, SpaCy, or TextBlob).
Outcome: The AI system analyzes text and provides insights into public opinion or customer feedback, introducing students to NLP applications in business and social media.

Objective: Teach students how AI is used in healthcare monitoring.
Project: Build a system that monitors vital signs like heart rate, blood pressure, and body temperature using sensors and provides health feedback using AI.
Tools: Raspberry Pi with health monitoring sensors (heart rate, temperature), Python for data processing, and machine learning models for health predictions.
Outcome: The system provides real-time monitoring and analysis, showcasing AI’s role in modern healthcare and telemedicine.

Objective: Introduce students to AI applications in the financial sector.
Project: Create a system that analyzes financial transaction data and uses AI to detect fraudulent activities.
Tools: Laptops/tablets, Python with machine learning libraries (scikit-learn, TensorFlow), and a dataset of financial transactions.
Outcome: The system identifies suspicious transactions and flags potential fraud, teaching students how AI is applied in banking and finance.

Objective: Teach students how AI can help optimize energy consumption.
Project: Build a system that monitors energy usage in a home or office and uses AI to provide recommendations for optimizing energy efficiency.
Tools: Raspberry Pi or Arduino, energy monitoring sensors, Python or block-based programming with AI algorithms.
Outcome: The AI system tracks energy usage patterns and suggests improvements for reducing energy consumption, helping students explore sustainability solutions using AI.

Objective: Demonstrate how AI can assist with real-time language translation.
Project: Create a tool that translates spoken or written text between multiple languages using AI-powered APIs.
Tools: Laptops/tablets, Python with speech recognition and translation APIs (such as Google Translate API).
Outcome: The system translates text or speech, showing how AI can bridge language barriers and assist in global communication.

Objective: Teach students how AI can be used to analyze financial markets.
Project: Build a model that uses AI to analyze historical stock data and predict future trends in the stock market.
Tools: Laptops/tablets, Python with machine learning libraries (such as Pandas, NumPy, TensorFlow), and a dataset of stock market prices.
Outcome: The AI system predicts stock price movements, introducing students to AI applications in the financial sector and helping them understand how AI is used in forecasting.