🌍 AERIS Environmental Telemetry Node

Simple ESP32-based environmental sensing prototype.

Collects:

• Gas concentration proxy (MQ-2)
• Temperature (DHT sensor)
• Moving average smoothing (SMA)

Designed for low-bandwidth telemetry preprocessing (e.g., CubeSat / remote node concept).

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📦 Hardware Used

🔥 MQ-2 Gas Sensor

• Analog output → ESP32 GPIO 34
• Digital output → ESP32 GPIO 4 (unused in this code)
• Used for gas concentration proxy

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🌡️ DHT Temperature Sensor

• Used for temperature readings
• dht.readTemperature() is called every loop
• Humidity not used in this version

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🧠 Microcontroller

• 12-bit ADC resolution (analogReadResolution(12))
• 0–4095 ADC range
• 3.3V reference

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⚙️ How It Works

1️⃣ Gas Concentration Proxy

float getGasPPM(int analogPin)

Steps:

1. Read raw ADC value (0–4095)
2. Convert to voltage
3. Convert voltage → percentage of 3.3V
4. Scale percentage to proxy PPM (0–400 range)

Formula used:

voltage = raw * (3.3 / 4095.0)
gasPercent = (voltage / 3.3) * 100
proxyPPM = gasPercent * 4

⚠️ This is NOT real calibrated PPM. It is only a linear proxy value for simulation/testing.

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2️⃣ Simple Moving Average (SMA)

#define TOTAL_SAMPLE 3

A rolling 3-sample window is used.

Structure:

struct SMA {
    float window[3];
}

Each loop:

• New value inserted
• Old values shifted
• Average calculated

Formula:

SMA = (w0 + w1 + w2) / 3

Smoothing helps reduce sensor noise before telemetry transmission.

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🔁 Main Loop Flow

Every 3 seconds:

1. Read gas proxy PPM
2. Read temperature
3. Add values to SMA buffers
4. After 3 samples → print SMA results

Output example:

proxy ppm: 173.24
G.getSMA() = 168.12
T.getSMA() = 29.87

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🛰️ Intended Architecture

Conceptually designed for:

• Onboard environmental sensing

• Local filtering (SMA)

• Reduced-noise telemetry transmission

• Future integration with:

  • GPS (e.g., Quectel L80)
  • Humidity sensing
  • Risk scoring logic

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📊 Why Use SMA?

Advantages:

• Very low computational cost
• Minimal memory usage
• Good noise reduction
• Ideal for embedded systems

Tradeoff:

• Adds slight latency (window size dependent)

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🚧 Current Limitations

• MQ-2 values are not calibrated
• No real PPM curve conversion (Rs/R0 method not implemented)
• DHT object not fully defined in snippet
• No GPS integration yet
• No packet encoding or radio transmission

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🔮 Future Improvements

• Implement proper MQ-2 logarithmic PPM calculation
• Store clean-air baseline (R0)
• Add humidity
• Add GPS coordinates
• Encode structured telemetry packet
• Add anomaly detection / wildfire risk scoring

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🛠 Build Notes

• Requires:

  • Arduino framework
  • DHT library

• Serial baud rate: 9600

• ADC resolution: 12-bit