Environmental Parameters in Aquaculture: Temperature, pH, Oxygen, and Turbidity Measurements

Published: 11 October 2024| Version 1 | DOI: 10.17632/8s73jfvgr5.1
Contributors:
Rubén Baena-Navarro, Yulieth Carriazo-Regino, Francisco Torres-Hoyos

Description

This dataset contains key water quality measurements from aquaculture ponds, collected through a real-time monitoring system based on IoT sensors. The measured parameters include temperature, dissolved oxygen, pH, and turbidity, which are essential for assessing and maintaining water health in aquaculture systems. The dataset was collected from aquaculture ponds located in Montería, Colombia, during the year 2024. The data is organized in columns corresponding to the following variables: Temperature (°C): Water temperature measurement. Dissolved Oxygen (mg/L): Concentration of oxygen in the water. pH: Acidity or alkalinity level of the water. Turbidity (NTU): Water clarity or turbidity level. Date and time: Temporal information including hour, day, and month. Normalized values: Scaled variables for temperature and dissolved oxygen, used for predictive modeling. This dataset was used in the study titled "Intelligent Prediction and Continuous Monitoring of Water Quality in Aquaculture: Integration of Machine Learning and IoT for Sustainable Management" and is intended to support the reproducibility of the results and facilitate future research in the field of environmental monitoring in aquaculture. The data can be used for water quality analysis, predictive modeling, and sustainability studies in aquaculture. Format: .xlsx (Excel)

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Institutions

  • Universidad Cooperativa de Colombia
  • Universidad de Cordoba

Categories

Environmental Science, Aquaculture, Data Science, Machine Learning, Internet of Things, Water Quality

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