🌍 Innovating Environmental Testing for Transit with IoT + Node.js
Transit systems are becoming living labs for climate action. As developers, we can build tools that measure air quality, noise, and emissions — turning commutes into data-driven experiences. Let’s walk through a simple prototype using Node.js + MQTT for real-time sensor data.

🔧 What You’ll Need
A low-cost IoT sensor (e.g., ESP32 + air quality sensor like MQ-135).

An MQTT broker (e.g., Eclipse Mosquitto).

Node.js environment for data ingestion and visualization.

📡 Step 1: Publish Sensor Data
On your ESP32, you’d push readings to an MQTT topic:

cpp

include

include

void loop() {
int airQuality = analogRead(34); // MQ-135 sensor
char msg[50];
sprintf(msg, "AirQuality:%d", airQuality);
client.publish("transit/air", msg);
delay(2000);
}
🖥️ Step 2: Subscribe with Node.js
Create a Node.js script to listen for sensor data:

js
const mqtt = require('mqtt');
const client = mqtt.connect('mqtt://localhost:1883');

client.on('connect', () => {
client.subscribe('transit/air');
});

client.on('message', (topic, message) => {
console.log(Received ${topic}: ${message.toString()});
// TODO: push to database or dashboard
});
📊 Step 3: Visualize Data
Pipe readings into a database (MongoDB, InfluxDB) and connect to a dashboard (Grafana, Kibana). This lets operators see:

🚇 Air quality trends inside vehicles.

🔊 Noise levels across stations.

🌡️ Heat maps of crowded platforms.

🚀 Why This Matters
By innovating environmental testing with IoT + real-time analytics, developers can:

Detect pollution hotspots.

Predict maintenance needs.

Guide electrification and redesign.

Empower communities with open dashboards.

💡 Next Steps
Add noise sensors and temperature probes.

Use edge computing to process data directly on vehicles.

Build APIs so city planners and riders can access insight.