"IoT-Based Water Quality Time-Series Dataset in Hostel Environments"

"This data is a structured time-series dataset of various water quality parameters recorded by an IoT-based water quality monitoring system for hostel drinking water. There are a total of around 3360 records collected in a span of 14 days, with constant sample intervals of 30 seconds for 2-hour-long periods every day. These parameters consist of temperature (\u00b0C), conductivity (EC \u00b5S\/cm), total dissolved solids (TDS ppm), and timestamp for each record in the dataset. Various experiments have been performed to collect this dataset. Experiments conducted include baseline experiments, incremental quantities of salts, spike contamination scenarios, varied temperature ranges, and real-life scenarios at random.With this mixture of stable and dynamic environmental behaviors, the dataset not only covers normal operations but also abnormal behavior taking place in the environments. This is an effective dataset that can be used in many applications including time-series analysis, anomaly detection, predictive maintenance, and prediction of hostel water quality.This particular dataset can be of great use for researchers and practitioners working on the embedded AI domain, TinyML, and other real-life monitoring systems where models need to predict environmental factors and detect anomalies in real-time situations and resource constrained settings."