Disease surveillance is essential for the control of flu and respiratory infectious diseases including the novel coronavirus disease (COVID-19). Indoor air quality monitoring has been shown effective in understanding the effectiveness of airflow and circulation indoors to reduce the risk of infectious diseases. In this project, we developed low-cost indoor air quality monitoring devices and systems to tackle the disease surveillance problem. The monitoring device consists of a set of air quality sensors. By strategic deployment and real-time data analysis, the system is able to yield insightful air circulation information indoors. The real-time data analysis is performed on air quality for the indoor ventilation using Long Short-Term Memory (LSTM) on sensed data. A series of user-friendly visualization interfaces and chatbot applications are designed to interact with users and ensure the successful delivery of infection control information. Finally, we work closely with the Taiwan Centers for Disease Control (CDC) and conduct field experiments in 15 locations including hospitals, long-term care centers, schools with total of 144 IAQ devices.