Smart Flood Sensor Network with API for Real-Time Data and Alerts DOI
Ade Sutedi, Arif Hakim, Ridwan Setiawan

et al.

Published: Sept. 4, 2024

Language: Английский

Water sustainability: a review of advances in water quality management technologies DOI
Shama E. Haque,

Farhan Sadik Snigdho,

N. Tasneem

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 195 - 214

Published: Jan. 1, 2025

Language: Английский

Citations

0
Monitoring of Water Quality using Machine Learning - A Review DOI Open Access

Y. N. V. Shashank,

S. Amith,

Sudip Kumar Sahana

et al.

International Journal for Research in Applied Science and Engineering Technology, Journal Year: 2024, Volume and Issue: 12(5), P. 495 - 498

Published: May 6, 2024

Abstract: The incorporation of machine learning (ML) can improve the monitoring water quality. It improves sustainability and security resources by enabling forecasting early detection possible contamination. A real-time system that collects information on numerous parameters, including pH level, dissolved oxygen, turbidity, temperature, conductivity, is made combination IoT technology with ML algorithms. models complex links between quality parameters looks for variations from typical patterns using a mix supervised unsupervised anomaly methods. Advantage this method include cost-effectiveness, scalability, remote accessible,

Language: Английский

Citations

1
Smart Flood Sensor Network with API for Real-Time Data and Alerts DOI
Ade Sutedi, Arif Hakim, Ridwan Setiawan

et al.

Published: Sept. 4, 2024

Language: Английский

Citations

0