Seeking Cleaner Air - Accessible Air Quality Monitoring and Event Diagnosis

Airborne particulate matter has been shown to be associated with morbidity and mortality, and can have a detrimental impact on sensitive materials and processes. Understanding the levels and movements of particulate matter in an enclosed space can lead to a reduction in the negative consequences of poor air quality. A system of environmental sensors including particulate matter, selected gases, and other atmospheric factors can be used to provide a real-time assessment of air quality. This assessment can be used to assist in the diagnosis of the source of particulate matter. This dissertation describes the creation of a framework for the monitoring and diagnosis of air quality events that will assist in the move towards cleaner air. To achieve this goal, a low-cost optical particle counter is created for incorporation into a wireless sensor network (WSN), including the exploration of novel methods for improving the quality of such a sensor. A WSN is developed using the aforementioned sensors, along with a system for data collection and visualization. Finally, a distributed event detection framework is formulated to facilitate human interaction with the system. Test results from the prototype system are presented for real-world environments where air quality is of significant concern. The results of this work may be leveraged into multiple applications that assist in the diagnosis and treatment of air quality issues that have tangible impact on health and material quality