Development of a Portable Sensor-based Indoor Air Quality Monitoring and Modeling System Using Artificial Intelligence Algorithm

-The study focuses on the development of a portable system for indoor air monitoring and modeling realized by interfacing semiconductor gas sensors with microcontroller capable of wireless short-range communication through Zigbee Module. An algorithm was developed to merge data from all of the sensors and to provide an intuitive graphical interface conveying the state of pollution. To evaluate the degree of health risk, results are categorized as Good, Moderate, Unhealthy for Sensitive Groups, Unhealthy and Very Unhealthy. Air Quality Index (AQI) developed by the US Environmental Protection Agency (EPA) was used since no such measures are presently available in the Philippines, where the system is intended to be used. Tests were conducted in selected indoor spaces suspected to have high concentration of pollutants and successfully showed real-time pollutant levels and their conformance to air quality standards. For large rooms, several measurements at different points were necessary. An averaging algorithm is applied to eliminate variations in readings and to remove redundancies. The average testing period for one measurement is 5 minutes, with a few additional minutes per sample taken following the first. Potential application includes alerting individuals to danger and encouraging authorities to take necessary action to improve air quality. Key-Words: -Air Pollution Monitoring, Sensor Networks, Fuzzy Logic