Eco-Analyst: Promoting Environmental Sustainability Through AI and Automated Machine Learning with Integrated Neural Networking

By Adam Warden

This project’s purpose is to serve as a means of accessing and controlling various environmental hazards, including atmospheric pollution and harmful micro-climates. It incorporates the use of programmed chemical sensors and micro controllers to collect data from their individual environments and relay the information to the app for the user to different operating systems for further use. The front end of this project has two parts: a mobile application and a web application. On both, the user is able to view in live time the various levels of each different recognized pollutant through a graphical representation displaying the max accepted level of concentration overlaid by the collected data. Each week, a custom email is sent by AI software trained with the weeks data and formatted neatly. These emails include basic stats of thee week, including the max, min, and mean value of each pollution through the entirety of the week. The email also conveys the data produced by machine learning algorithms which make predictions of future levels of pollution concentrations and implications of possible health hazards and precautions.

Additionally, I have created a functional prototype of an anti-gravity lifter capable of distributing bulk material a specified distance without the use of nonrenewable energy sources. This lifter is powered by an ionic wind produced by an electromagnetic field constantly surrounding the lifter. This wind supports the mass of the lifter, while magnetic guide rails offer further support for additional material and guidance along transit.

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