Contributions to Reduce the Gap on Water Quality Analysis in Chile and Latin America: State of the Art

EasyChair Preprint 11288

Abstract

The global environmental crisis is one of the serious threats facing humanity, specifically water pollution has become one of the main concerns of all societies, due to the harmful effects it has on health, as it endangers all living beings. This paper presents a state of the art in the advances of water quality monitoring systems that can help prevent these adverse effects, however, there is a gap between progress in this area in developed countries and Latin American countries. On the other hand, decision making to mitigate the negative impacts requires a programmable platform. IoT technologies, with real-time data collection are explored, evidencing the existence of alternatives for communication such as WiFi, LoRa, 4G, among others, implemented in devices based on Arduino Uno or Raspberry Pi. On the other hand, the most used data processing, modeling and classification techniques have been those based on Machine Learning, given their advantages for data science, which reflects their potential in the use of water quality analysis systems.

Keyphrases: IoT, Python, machine learning, water quality

@booklet{EasyChair:11288,
  author    = {Ricardo Rojas Flores and Marcela Jamett},
  title     = {Contributions to Reduce the Gap on Water Quality Analysis in Chile and Latin America: State of the Art},
  howpublished = {EasyChair Preprint 11288},
  year      = {EasyChair, 2023}}