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Image processing as the validation method of droplet dispersion modeling process

A pandemic of respiratory viral infections, which was spreading throughout the world during the first decade of the 21st century are believed to be easily contagious via direct contact through droplets and aerosol containing an infected particle which is spreading near the patient's environment. From the previous research, the role of droplet spreading during the coughing and talking are already investigated. However, massive viral infectious outbreaks during the SARS pandemic treatment procedure in the hospital on 2003 revealed that there is also a greater risk of viral dissemination process during the treatment practice. This project is aimed to understand about the droplet spreading characteristic during the dissemination process and to develop modeling method to make a prediction mechanism of droplet motion through a simple simulation program. The modeling has derived from basic theory of air viscosity, verified with droplet mist flow pattern images which are obtained through a digital image processing method. The results show that droplet modeling simulation which is based on the air viscosity factor gives an improved result to mimicking the droplet flow pattern, particularly during the operation of nebulizer. It also concluded that the droplet would perfectly evaporate as it travels more than 5 centimeters from the launch point and remain airborne during the treatment procedure.