Projeto de Pesquisa Apresentado ao Programa de Trabalho de Conclusão de Curso Relacionado ao Sistema de Tratamento de Água de Reuso com IoT

Over the past ten years, industry has experienced what is called the fourth industrial revolution, or Industry 4.0, introducing unprecedented intelligence into industrial processes through a series of digital "tools" such as IoT, Machine Learning, Artificial Intelligence, and so on. The volume of data produced by this fully digital and autonomous industry cannot be supported by local network networks, as there is a need for massive traffic and information storage. Hence, an ecosystem to support this demand began to be developed: the Cloud. The cloud is a network of servers connected via the internet, creating a network of nearly infinite sizes. It only requires the addition of more servers to expand the network. Several companies operate these servers and sell them as a service. To facilitate visualization of a cloud-connected system, this project proposes automating a water treatment system. The system's inputs and outputs will be connected to an IoT board, which in turn is programmed to "talk" to the internet. Throughout the project, all the electrical, electronic, and mechanical designs of the system are explained in detail, as well as the program written to automate the system and, most importantly, connect it to the cloud. Therefore, anyone interested in designing an IoT system will find excellent support in this final project.

Authors

Institutions

Publication Details

Journal
RCMOS - Revista Científica Multidisciplinar O Saber
Published
2025-09-04
DOI
https://doi.org/10.51473/rcmos.v1i2.2025.1342
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Projeto de Pesquisa Apresentado ao Programa de Trabalho de Conclusão de Curso Relacionado ao Sistema de Tratamento de Água de Reuso com IoT

João Pedro Maretti Basso, Wellington Ferreira do Nascimento, Mauricio Rodrigues Costa, Carlos da Silva Anthero
RCMOS - Revista Científica Multidisciplinar O Saber
Water Quality Monitoring Technologies
article

Projeto de Pesquisa Apresentado ao Programa de Trabalho de Conclusão de Curso Relacionado ao Sistema de Tratamento de Água de Reuso com IoT

João Pedro Maretti Basso, Wellington Ferreira do Nascimento, Mauricio Rodrigues Costa, Carlos da Silva Anthero
article en

Abstract

Over the past ten years, industry has experienced what is called the fourth industrial revolution, or Industry 4.0, introducing unprecedented intelligence into industrial processes through a series of digital "tools" such as IoT, Machine Learning, Artificial Intelligence, and so on. The volume of data produced by this fully digital and autonomous industry cannot be supported by local network networks, as there is a need for massive traffic and information storage. Hence, an ecosystem to support this demand began to be developed: the Cloud. The cloud is a network of servers connected via the internet, creating a network of nearly infinite sizes. It only requires the addition of more servers to expand the network. Several companies operate these servers and sell them as a service. To facilitate visualization of a cloud-connected system, this project proposes automating a water treatment system. The system's inputs and outputs will be connected to an IoT board, which in turn is programmed to "talk" to the internet. Throughout the project, all the electrical, electronic, and mechanical designs of the system are explained in detail, as well as the program written to automate the system and, most importantly, connect it to the cloud. Therefore, anyone interested in designing an IoT system will find excellent support in this final project.

RCMOS - Revista Científica Multidisciplinar O SaberVol. 1(2)
Faculdade Brasil (BR)
Openalex Percentile: Top 78%
Water Quality Monitoring Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.