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pollution

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This project uses Long Short-Term Memory (LSTM) networks to forecast PM2.5 pollution levels based on environmental factors like temperature, humidity, pressure, wind speed, snow, and rain. It employs multivariate time series data, data preprocessing (normalization and sequence creation), and model training to predict future pollution levels.

  • Updated Dec 2, 2024
  • Python

EBFNflora is a University Project for the Arduino Uno (ATmega328) to check plants environment. It's not developed in Arduino native language, but it was written in ANSI-C, for this very reason was pretty challenging. The embedded machine can check light quality, pollution and temperature using values set by user. ProgettoSistemiOperativi2017_2018

  • Updated Mar 16, 2018
  • C

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