What is my SIP?

My project is Python program that uses spatial-correlated signals over-the-air computation to monitor air emissions and calculate the best outcome to catch problems and stop them before they spread. What separates this project from others is the correlation strategy across a given space range, this enable the program to leverage individual datasets mapping a dynamic amount of pollution modeling across different regions of the world. Data sources can include EPA AirNow, OpenAQ, U.S.E.P.A, and CAMS these sources are the most useful because the provide real-time information with Sever-Sent Events the data from each source is obtained and implemented.​ What separates this project from others is the correlation strategy across a given space range, this enable the program to correlate from how many ever data sources are available leveraging their individual datasets mapping a dynamic amount of modeling of pollution spread across different regions of the world. The algorithm identifies abnormal emission patterns or extreme events by using autoencoders to reconstruct input data and compares previous reconstruction errors against a predefined threshold yielding graph visualizations of emission predictions and spatiotemporal trends addressing potential emissions problems promptly.​