WORKSHOP GUIDE - SESSION 6

IoT + AI: Smart Cities

Connecting Physical Sensors (ESP32) to Digital AI Intelligence.

Part 1: Key Concepts

ESP32 Microcontroller

A ₹400 chip with WiFi. It reads data from sensors (Temperature, Dust, Gas) and sends it to your computer.

Edge Intelligence

Instead of sending massive video/audio streams to the cloud, we process data locally ("at the edge") using the AI PC. This saves bandwidth and privacy.

Part 2: The Lab - "AirOwl Smart Monitor"

The Mission

You are deploying an Air Quality Monitor for a School. The AI needs to read the PM2.5 levels and automatically advise if recess should be indoors or outdoors.

Wiring Checklist

Ensure your connections are secure:

VCC -> 3.3V
GND -> GND
RX -> TX (Pin 17)

Part 3: The Prompt Library

Level 1: Live Status Check

Goal: Read the raw data.

Fetch the latest sensor data from AirOwl. What is the current PM2.5 level?

Level 2: Health Advisory

Goal: Interpret the number.

The PM2.5 is currently 145. Is this safe for children with asthma? What precautions should the school take?
Note: PM2.5 > 100 is generally considered "Unhealthy".

Level 3: Debugging Mode

Goal: Identify sensor fault.

The sensor reports PM2.5 = 0 and Humidity = 0. Is this physically possible, or is the wire loose?

Level 4: Data Logging

Goal: Create a report.

Based on the last 5 readings (all above 100), write an incident report for the City Council complaining about the nearby factory pollution.