Ukko

Develop an app or platform to crowd-source information for comparing changes in environmental factors, such as temperature, relative humidity, air pollution, with occurrence of symptoms of allergies and respiratory diseases. Create tools for public entry and grading of symptoms, including but not limited to cough, shortness of breath, wheezing, sneezing, nasal obstruction, itchy eyes; and geographic mapping of symptom frequency and intensity. Create a platform for comparison of symptom map with NASA provided data, with visualization options for web and/or smart phone.

Ukko shows you how your health is affected by the world around you. It is:

• Accurate
• Predictive
• Updated in realtime
• Personalized to you and your lifestyle

Ukko uses machine learning algorithms to analyze NASA's climate and environmental data and relate this to what other people are saying about their health on social media.

When you tell Ukko a little about yourself and the health issues on your mind, Ukko gives you meaningful insights that are relevant to you, your health, and your location.

Ukko allows a user to submit a health symptoms they are currently experiencing, as well as the health conditions that they suffer from, such as asthma, allergies, or suppressed immune system. The user can also set locations in their profile, such as their location of home and work.

Ukko continues to deliver health trends with increased insight as newer environmental data is compared with user reported health symptoms.

Ukko has access to vast amounts of user reported health symptoms as a result of combining user data submission with Twitter search scripts.

The result is a highly insightful and predictive model that can alert the user if a changing environmental condition will affect their health.

At the core our application relies on two sources of data:

• atmospheric composition data from spacebourne sensors and
• crowdsourced data from the users reporting various health-related symptoms.

We used Worldview (https://worldview.earthdata.nasa.gov/) to find data about the atmospheric composition. The data we used to train the mode:

• SO2 and Relative Humidity from Aqua Satellite's Atmospheric Infrared Sounder (AIRS) instrument
• Aerosol data from the Aqua satellite's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument

For the croud-sourced data we used:

• Twitter's API to search for users reporting health-related symptoms
• Data raported by our users through our website http://ukko.space/

Full Team Members:

• Lee Sutton
• Parsian Asgari
• Tim Nosov
• Tobi Nakamura
• Jordan Lui
• Chris Neal
• Paul Nogas
• Samantha Yu
• Mike Henrey