umashankaharini/AIR_QUALITY_PREDICTION

Air Quality Monitoring Dataset (CO₂, LPG, Alcohol Levels & Classification)

📌 Overview

This dataset contains air quality sensor readings from an IoT-based air monitoring system. It includes measurements of CO₂ (Carbon Dioxide), LPG (Liquefied Petroleum Gas), and Alcohol concentration, along with a target label indicating whether the air quality is "Normal" or "Abnormal" based on gas concentration levels.

📊 Dataset Description

• Total Samples: [Specify the number of rows]
• Columns:
  • co2 → Carbon Dioxide level (PPM)
  • lpg → LPG concentration (PPM)
  • alcohol → Alcohol gas level (PPM)
  • temperature → Ambient temperature (°C)
  • humidity → Relative humidity (%)
  • target → Label (Normal / Abnormal)

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📡 Data Collection Methodology

• Hardware Used:

  • MQ135 Sensor → Measures CO₂ levels
  • MQ6 Sensor → Detects LPG concentration
  • MQ9 Sensor → Detects Alcohol gas levels
  • DHT11 Sensor → Temperature & Humidity monitoring
  • NodeMCU (ESP8266) → IoT device for real-time data transmission

• Procedure:

  • Sensors were placed in various indoor and outdoor environments.
  • Data was collected at fixed intervals over multiple days.
  • The dataset was balanced to ensure an equal ratio of normal and abnormal cases.

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🛠️ Preprocessing

• Data Cleaning: Removed inconsistent readings and sensor noise.
• Normalization: Scaled sensor values to ensure uniformity.
• Labeling Criteria: Threshold values for "Normal" and "Abnormal" air quality were defined based on environmental safety standards.

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🚀 Applications

This dataset is suitable for:
✅ Machine Learning Models: Train classifiers for air quality prediction.
✅ IoT-based Smart Air Monitoring Systems.
✅ Feature Analysis & Environmental Studies.

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📄 License

This dataset is released under CC BY 4.0 License – You are free to use, modify, and share it with attribution.

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