Code Logic Explained - santhoshsharuk/-AI-Weather-Station-MVP- GitHub Wiki

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# 🧠 Code Logic Explained

This page explains how the **AI Weather Station MVP** Arduino sketch works — step by step.

The code reads data from sensors (DHT11 & BMP180), applies rule-based logic, and outputs a weather forecast via the **Serial Monitor**.

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## 🔁 Main Flow of the Code

```cpp
void loop() {
  readSensors();
  calculateForecast();
  displayOutput();
  delay(5000); // Wait 5 seconds before next update
}

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📥 1. Reading Sensor Data

DHT11 — Temperature & Humidity

float temp = dht.readTemperature();
float humidity = dht.readHumidity();

• dht.readTemperature() gets the temperature in Celsius.
• dht.readHumidity() gets the relative humidity in percentage.

BMP180 — Pressure

float pressure = bmp.readPressure() / 100.0; // Convert to hPa

• bmp.readPressure() returns pressure in Pascals, so it’s divided by 100 to convert to hPa.

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🧠 2. Rule-Based Forecasting Logic

The forecast is made using simple if-else rules that simulate AI behavior:

if (humidity > 80 && pressure < 1000) {
  forecast = "Rain Possible";
} else if (humidity < 50 && pressure > 1015) {
  forecast = "Clear Day";
} else {
  forecast = "Stable Weather";
}

✅ Explanation:

• Rain Possible → High humidity AND low pressure
• Clear Day → Low humidity AND high pressure
• Stable Weather → Anything else (no strong weather signal)

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📤 3. Displaying Output

All the data is shown in the Serial Monitor using:

Serial.print("Temp: ");
Serial.print(temp);
Serial.println(" °C");

Serial.print("Humidity: ");
Serial.print(humidity);
Serial.println(" %");

Serial.print("Pressure: ");
Serial.print(pressure);
Serial.println(" hPa");

Serial.print("Forecast: ");
Serial.println(forecast);
Serial.println("-------------------------");

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⏱ Delay Between Updates

The following line ensures the system waits 5 seconds before repeating:

delay(5000);

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📄 Sample Output

Temp: 27.8 °C  
Humidity: 85.2 %  
Pressure: 998.7 hPa  
Forecast: Rain Possible  
-------------------------

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🧪 Want to Expand?

You can:

• Modify thresholds for your local environment
• Add more rules
• Integrate with machine learning later using SD card or cloud data

Check out the [Future Plans](./Future-Plans) page to learn how.

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Would you like the next page (like **Circuit Diagram**, **Future Plans**, or **FAQ**) too?