Water Quality Dataset from Water Sources in Kenya

This dataset contains water quality measurements collected using an IoT-based sensing system deployed across multiple water sources in Kenya. The data was gathered over February–March 2026 at two-minute intervals, resulting in 100,800 observations. Each record includes four key physicochemical parameters: pH, Total Dissolved Solids (TDS), turbidity, and temperature, a binary classification label indicating whether the water is safe for drinking or requires treatment. The dataset covers diverse water sources, including: Treated municipal and bottled water (safe) Rivers and lakes (surface water) Borehole water (groundwater) Marine water (Indian Ocean) Preprocessing steps included handling missing values through imputation, outlier assessment based on environmental plausibility, and feature normalization. The dataset is designed for machine learning applications, particularly binary classification of water quality and real-time monitoring using IoT or edge (TinyML) systems.本数据集包含基于物联网（IoT）传感系统采集的水质测量数据，该系统部署于肯尼亚的多处水源地。数据采集周期为2026年2月至3月，采集间隔为两分钟，总计生成100,800条观测记录。 每条记录包含四项关键理化参数：pH值、总溶解固体（Total Dissolved Solids, TDS）、浊度与温度，同时附带一个二元分类标签，用于标识该水体是否可安全饮用或需要进行处理。 本数据集涵盖多样化的水源类型，具体包括： - 处理后的市政供水与瓶装水（安全水源） - 河流与湖泊（地表水） - 钻孔井水（地下水） - 海水（印度洋海域） 数据预处理步骤包括通过插补法处理缺失值、基于环境合理性开展异常值评估，以及特征归一化操作。 本数据集专为机器学习应用设计，尤其适用于水质二元分类任务，以及基于物联网或边缘（TinyML）智能系统的实时监测场景。