Class 7 — Computer Vision & Advanced AI

📚 Class 7 Modules

What You'll Learn

6 comprehensive modules covering everything from theory to hands-on projects!

👁️

Computer Vision with OpenCV

Use OpenCV in Python to capture video, detect faces, recognise gestures and track objects in real time. Build a face detector that triggers Arduino when it sees you!

OpenCVPythonFace DetectionReal-Time CV

🗣️

Voice-Controlled AI

Use Python's speech_recognition library to capture voice commands. Integrate with Arduino to control LEDs, motors, and buzzers by speaking. Build Alexa-like functions!

speech_recognitionNLPVoiceArduino Serial

🏙️

Smart City Model

Design and build a miniature smart city: adaptive traffic lights (computer vision), auto street lamps, air quality monitor (MQ-135), flood sensors, and a central dashboard!

Smart CityTraffic AIAir QualityDashboard

⚡

Renewable Energy Tech

Build solar and wind energy models with sensors. Measure voltage/current output. Compare energy sources. Build a solar-powered USB charger and understand green tech!

Solar PanelWind EnergyGreen TechEnergy Monitor

🌐

Web + Hardware Dashboard

Build a live web dashboard in HTML/CSS/JS that shows real-time sensor data from your Arduino. Send data via Serial/WiFi to a beautiful browser interface you coded yourself!

HTMLCSSJSSerialDashboard

🧬

Advanced Python & Algorithms

Dive into sorting algorithms, recursion, and data structures in Python. Understand Big-O notation. Implement pathfinding algorithms (BFS/DFS) — the brains behind maze robots!

AlgorithmsBFSDFSSortingRecursion

⚡ Interactive Labs

Try It Right Now!

8 interactive simulators — code editor, robot sim, circuit lab, quiz, binary game, AI pattern, sequences, and sorting!

🖥️ Remesys Interactive Lab — Class 7

# 👁️ Python — Class 7 Computer Vision!
# Simulating OpenCV face detection:

import json  # pretend this is cv2

# In real code this would be:
# import cv2
# img = cv2.imread("photo.jpg")
# faces = face_cascade.detectMultiScale(img)

# Simulated output:
faces = [(120, 80, 100, 100), (320, 90, 95, 95)]

print(f"👁️ Detected {len(faces)} face(s)!")
for i, (x, y, w, h) in enumerate(faces):
    cx, cy = x + w//2, y + h//2
    print(f"  Face {i+1}: centre ({cx},{cy}), size {w}×{h}px")
    confidence = 0.92 - i*0.08
    print(f"  Confidence: {confidence:.0%}")

▶ Click "Run Code" to see output!

Ready

🕹️ CONTROLS

📡 LIVE SENSORS

🔊 Ultrasonic --

🌡️ Temperature 28°C

💡 Light (LDR) --

🔋 Battery 85%

Select a component above, then click on the canvas to place it!

Score: 0

Q: 1/5

Level: Beginner 🌱

Convert the decimal number to binary! Score streak points!

Convert this number to binary:

Score: 0 | Best: 0

2⁷

128

2⁶

64

2⁵

32

2⁴

16

2³

8

2²

4

2¹

2

2⁰

1

Draw a pattern, teach the AI, then draw a similar one and see if it recognises it!

Spot the number pattern and type the next number — just like AI sequence prediction!

Drag each item into the correct bin — just like an AI sorting algorithm!

🍎 FRUIT

🚗 VEHICLE

🐶 ANIMAL

Correct: 0 | Wrong: 0

🔨 Build & Create

Class 7 Projects

Real hands-on projects you'll build during the year!

👁️

🔥 Advanced

AI Face & Emotion Detector

OpenCV system that detects faces and classifies emotions (happy, sad, neutral) in real time!

⏱️ 10 hrs

🏙️

🔥 Advanced

Smart City Model

Full city model with traffic lights, street lamps, pollution sensors and a central dashboard!

⏱️ 18 hrs

🗣️

🔥 Advanced

Voice Assistant Robot

Robot that responds to voice commands: 'move forward', 'turn left', 'stop', 'report status'.

⏱️ 12 hrs

⚡

⚡ Medium

Solar USB Charger

Solar panel system with charge controller, battery, and USB output with voltage/current display.

⏱️ 8 hrs

📅 Annual Schedule

Class 7 Roadmap

2 classes per week, quarterly projects, and the Annual Innovation Showcase

7

Class 7 — Full Year Schedule

40 weeks · 2 classes/week · 80 sessions

Wk 1–4OpenCV — face detection, gesture recognition

Wk 5–8Smart City Model — full build

Wk 9–10Q1 Project — Smart City Model 🏙️

Wk 11–12Voice-controlled AI with speech_recognition

Wk 13–14Web + Hardware dashboard in HTML/JS

Wk 15–16Renewable energy — solar/wind models

Wk 17–18Python algorithms — BFS, DFS, sorting

Wk 19–20Q2 Project — AI Face Detector 👁️

Wk 21–28Voice robot, emotion classifier, data viz

Wk 29–40Annual Showcase — My AI Invention 🏆

❓ Class 7 FAQ

Common Questions

Is OpenCV hard to learn at this level? ▼

We use beginner-friendly wrappers and pre-trained Haar cascades, so students can build a working face detector in under 20 lines of Python — very achievable!

Does the Smart City actually work? ▼

Yes — it's a physical model with real LEDs, sensors, and servos. The 'traffic AI' uses a photoresistor to count vehicles (simulated by passing a finger over the sensor).

How does the quarterly project work? ▼

Every 10 weeks, students complete a major project. They design, build, test and present it to the class. Feedback is given by teachers and peers. This mirrors real engineering and design-thinking workflows!

Can I use this simulator to practise at home? ▼

Yes! The simulators on this page work in any modern browser — no installation needed. Students can practise coding, circuit design, and robot control from home anytime!

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Class 7 👁️ Computer Vision & Advanced AI

What You'll Learn

Try It Right Now!

🖥️ Remesys Interactive Lab — Class 7

Class 7 Projects

Class 7 Roadmap

Class 7 — Full Year Schedule

Common Questions

Class 7
👁️ Computer Vision & Advanced AI