Hydroponic Lettuce TDS Time-Series Dataset

This dataset contains time-series measurements of Total Dissolved Solids (TDS) collected from an Internet of Things (IoT)-based hydroponic lettuce monitoring system. TDS was measured using a DFRobot Gravity Analog TDS Sensor connected to an ESP32 DevKit V1 and is expressed in parts per million (ppm). The dataset consists of 4,320 sequential observations collected from January 17 to January 31, 2026, over a 15-day monitoring period. Measurements were automatically recorded at approximately five-minute intervals. Each record contains two variables: Datetime, representing the date and time of measurement, and TDS, representing the measured nutrient concentration in ppm. The TDS values range from 550 to 961 ppm. The dataset contains no missing values or duplicate records and is maintained in chronological order. The data are provided as raw timestamped measurements without feature engineering, allowing users to apply their own preprocessing and analytical methods. The dataset can support research on hydroponic nutrient monitoring, time-series analysis and forecasting, anomaly detection, machine learning and deep learning, adaptive sensing, and IoT-based smart agriculture. In particular, it can be used to develop and evaluate predictive models for nutrient concentration and data-driven monitoring strategies in hydroponic cultivation.本数据集收录了基于物联网（Internet of Things, IoT）水培生菜监测系统采集的总溶解固体（Total Dissolved Solids, TDS）时序测量数据。TDS由连接于ESP32 DevKit V1开发板的DFRobot Gravity模拟式TDS传感器测得，计量单位为百万分比浓度（parts per million, ppm）。 该数据集涵盖2026年1月17日至1月31日共15天监测周期内的4320条连续观测样本，测量间隔约为5分钟，采用全自动记录方式。每条记录包含两个变量：Datetime（测量时点的日期与时间）与TDS（以ppm为单位的实测养分浓度）。 本数据集的TDS数值分布区间为550至961 ppm，无缺失值与重复记录，且严格按时间先后顺序编排。数据集提供原始带时间戳的测量数据，未经过任何特征工程处理，可供使用者自行开展预处理与各类分析工作。 本数据集可支撑水培养分监测、时序分析与预测、异常检测、机器学习与深度学习、自适应传感以及基于物联网的智慧农业等领域的研究，尤其可用于开发并评估水培种植场景下的养分浓度预测模型与数据驱动的监测策略。