Sustainable development is among the key challenges of the 21st century. One specific concern are microclimate areas in cities. Microclimates are correlated to high ozone levels that can cause respiratory problems, foliage injury, and in severe cases headaches, chest pain, and dryness of the respiratory tract.
What it does
Airis is a system that empowers cities to meet their sustainability goals with tools to assess microclimates and predict ozone levels. Equipped with this information cities can better combat their negative effects on humans and the environment. Airis is based on the CityIQ technology that uses sensors to collect temperature, barometric pressure, humidity, and nutrient pollution readings from around the city and employs machine learning to turn the data into usable information for implementing solutions.
How I built it
Airis uses microclimate readings provided by CityIQ nodes to monitor nutrient pollution. These readings include temperature, humidity, and pressure in the local San Diego region. The primary and secondary correlations of these readings with Nitrogen and Ozone reactions within the atmosphere and their additional relation to Phosphorus runoff are used to assess their impact on the environment. The sensor data, coupled with the sensor’s location, is then used to detect, store, plot, and illustrate appropriate readings; producing a reliable, accessible, and comprehensible means to track current environmental trends; determine the efficiency and impacts of sustainable actions in place; and approximate future environmental effects and hazards. After receiving the gathered microclimate data from the appropriate CityIQ node, it is sent and placed into its appropriate database. The database can then used to create models of the current state. The models are maps and charts identifying the areas of concern. In addition, Airis can use linear regression on the historical datasets over the past decade in order to make projections on the effects of the ozone due to changing microclimates.
Challenges I ran into
None of our team had really much web development experience, so creating a web application took time to learn the framework.
Accomplishments that I'm proud of
I think we are very proud of our project overall. Never having done a web application and being able to come up with not only a fully functional app but a product was truly amazing.
What I learned
We learned a ton about developing a web application, an overall product, and about the city of San Deigo.
What's next for Airis
The next step for Airis would be to incorporate real-time data and more sophisticated machine learning to provide a better all tool.