Assessing the Effect of Water Quality on Public Health and Risk of Infectious Disease (2016)

I participated in New York Academy of Science’s Junior Academy where I collaborated with a team of 4 other students around the world to work on a project that requires finding a solution to address the Biodiversity problem. The problem we selected was to assess the effect of water quality on public health and risk of infectious disease.

Urban water quality is of great importance to our daily lives. Human development and population growth exert many and diverse pressures on the quality and quantity of water resources and on access to them. Nowhere are the pressures felt so strongly as at the interface of water and human health. Infectious, water-related diseases are a major cause of morbidity and mortality worldwide. Scientists agree that long-term, high-resolution measurements are necessary to improve our understanding of our water resources. Because of their multi-functional abilities, adding sensor networks to the underwater domain has the potential to improve governments’ and water organizations’ ability to monitor water quality and public health.

There needs to be a way to produce, collect and analyze data for scientists, governments, and community leaders so they can make informed decisions and propose strategies to minimize risk factors for water pollution and the spread of infectious disease. Prediction of urban water quality can help control water pollution and protect human health. However, predicting urban water quality is very challenging due to the multiple complex factors that affect water quality.

The solution which the team came up with would utilize sensors based on Raspberry Pi and a Neural Network model built with Wolfram Mathematica.