IoT Monitoring Dataset of Water Quality and Tilapia (Oreochromis niloticus) Health in Aquaculture Ponds in Montería, Colombia (2024))

Description
This dataset contains six months of water quality and tilapia (Oreochromis niloticus) health monitoring data collected from aquaculture ponds in Montería, Colombia. Using an IoT-based monitoring system, critical parameters such as dissolved oxygen (DO), pH, water temperature, and turbidity were recorded. Fish health indicators, including average fish weight and survival rate, are also included.
Data was collected from January to June 2024, with hourly readings to capture daily fluctuations and ensure comprehensive monitoring of aquaculture conditions and tilapia well-being.
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Included Files
1. Data Model IoTMLCQ 2024.xlsx
o Contains sensor readings and fish health data collected over six months.
o Columns:
 Datetime: Date and time of each reading.
 Month: Data collection month (January to June).
 Average Fish Weight (g): Average weight of the tilapia fish in grams.
 Survival Rate (%): Percentage of fish survival during the monitoring period.
 Disease Occurrence (Cases): Number of disease cases observed.
 Temperature (°C): Water temperature readings.
 Dissolved Oxygen (mg/L): Levels of dissolved oxygen in the water.
 pH: Water pH values.
 Turbidity (NTU): Water turbidity measured in Nephelometric Turbidity Units (NTU).
 Oxygenation Automatic: Indicates if automatic oxygenation was applied (Yes/No).
 Oxygenation Interventions: Oxygenation interventions applied (Yes/No).
 Corrective Interventions: Number of corrective measures taken.
 Thermal Risk Index: Indicates if the thermal risk is "High" or "Normal."
 Low Oxygen Alert: Shows "Critical" if DO levels are below 5 mg/L, otherwise "Safe."
 Health Status: Fish health status, showing "At Risk" or "Stable" based on thermal and oxygen risk alerts.
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Data Collection Method
Data was collected using IoT sensors strategically placed in the aquaculture ponds. Readings were taken every hour throughout the monitoring period. This dataset provides valuable insights into the relationship between water quality parameters and the health of tilapia (Oreochromis niloticus) in controlled aquaculture conditions.
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Usage Notes
• This dataset is useful for research in aquaculture management, water quality monitoring, and predictive modeling of fish health and growth.
• Missing data due to sensor or communication failures were addressed using interpolation methods.
• Regular sensor calibrations were performed to ensure accuracy in the collected data.