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Indoor CO2 Monitoring and Analysis System

Indoor CO2 Monitoring and Analysis System

  • Environmental Monitoring
  • Sensor Integration
  • Data Analysis
Tools: Python
Year: 2022

Overview

Reliable indoor air-quality studies require a flexible data acquisition and evaluation platform that can accommodate varying sensor configurations without extensive software modifications. This project focused on the development of a configurable Python-based monitoring application for collecting, managing, and analyzing CO₂ measurements from a large number of distributed sensors during experimental campaigns.

The software was designed around a configuration-driven architecture, enabling different sensor setups to be integrated through simple configuration changes. Automated data collection, state-machine-based system control, and reporting capabilities provided a streamlined workflow for measurements involving extensive sensor deployments and subsequent data evaluation.

Key Contributions:

  • Development of a Python-based indoor air-quality monitoring application
  • Support for large-scale deployments with numerous CO₂ sensors
  • Configuration-driven sensor integration without software modifications
  • Configurable system behavior using state-machine-based control logic
  • Reporting and visualization capabilities for measurement evaluation