Fish Health and Water Quality Monitoring Dataset (Montería, 2024) – Tilapia (Oreochromis niloticus)

This dataset contains six months of water quality and fish health monitoring data collected from aquaculture ponds in Montería, Colombia. The dataset focuses on tilapia (Oreochromis niloticus), using an IoT-based system to monitor critical parameters such as dissolved oxygen (DO), pH, water temperature, and turbidity. Fish health indicators, including average fish weight and survival rate, are also recorded.

The data was collected from January to June 2024, with readings taken every 6 hours to capture daily fluctuations and ensure comprehensive monitoring of water conditions and fish health.

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Files Included:

1. Data Model IoTMLCQ 2024.xlsx
- Contains sensor readings and fish health data collected over six months.
- Columns:
- Month: Data collection month (January to June).
- Average Fish Weight (g): The 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 Interventions: Whether oxygenation was applied (Yes/No).
- Corrective Interventions: Number of corrective measures taken.

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Data Collection Method:

The data was collected using IoT sensors strategically placed in the aquaculture ponds. Readings were taken every 6 hours throughout the monitoring period. This dataset provides valuable insights into the relationship between water quality parameters and the health of Tilapia (Oreochromis niloticus).

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Usage Notes:

- This dataset can be used 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.

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本数据集包含从哥伦比亚蒙特里亚市（Montería）水产养殖池塘采集的6个月水质与鱼类健康监测数据。本数据集以罗非鱼（Oreochromis niloticus）为研究对象，采用物联网（IoT）监测系统对溶解氧（DO）、pH值、水温及浊度等关键参数进行监测，同时记录鱼类平均体重、存活率等健康指标。

本数据集的采集周期为2024年1月至6月，每6小时完成一次读数采集，以捕捉每日水质波动，确保全面覆盖水环境与鱼类健康的监测工作。

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包含文件：
1. Data Model IoTMLCQ 2024.xlsx
- 存储了6个月采集的传感器读数与鱼类健康数据。
- 包含以下字段：
- Month：数据采集月份（1月至6月）
- Average Fish Weight (g)：罗非鱼平均体重，单位为克
- Survival Rate (%)：监测周期内鱼类存活率百分比
- Disease Occurrence (Cases)：观测到的发病例数
- Temperature (°C)：水体温度读数
- Dissolved Oxygen (mg/L)：水体溶解氧含量，单位为毫克每升
- pH：水体pH值
- Turbidity (NTU)：水体浊度，单位为散射浊度单位（NTU）
- Oxygenation Interventions：是否实施增氧干预（是/否）
- Corrective Interventions：采取的补救干预措施次数

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数据采集方法：
本数据集通过布设于水产养殖池塘的物联网传感器完成数据采集，整个监测周期内每6小时进行一次读数。本数据集可为解析水质参数与罗非鱼（Oreochromis niloticus）健康状况之间的关联提供极具价值的参考依据。

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使用说明：
- 本数据集可应用于水产养殖管理、水质监测以及鱼类健康与生长预测建模等相关研究领域。
- 针对传感器或通信故障导致的缺失数据，已通过插值法进行补全处理。
- 已定期对传感器开展校准工作，以确保采集数据的准确性。