AquaSense_Dataset

Description

This data gives an insight into water quality. The dataset contains 10,800 readings taken each hour for 15 hypothetical ponds over a period of 30 days. These readings have six water quality parameters including dissolved oxygen (DO, mg/L), pH, temperature (°C), un-ionized ammonia (NH₃, mg/L), turbidity (NTU), and salinity. The data also include smoothed values (using the EWMA approach) of each water quality parameter, a binary indicator of anomalies in the parameter, a risk score, a ground truth label (if any) of an incident, and a ground truth severity level of the incident (NORMAL, WATCH, WARNING, or CRITICAL). Each pond has one to three independent incidents chosen from six types including a harmless pre-dawn diel DO dip, an independent DO excursion, an algal bloom crash signature (simultaneous decrease of DO, increase of NH₃, and decrease of pH), an independent ammonia excursion, a cold front, and an independent turbidity excursion.

Steps to reproduce

The data was computer-generated data, and not real-world sensor measurements. A discrete event simulator simulated multi-parameter trajectories for 15 separate ponds for 30 days. The simulator considered the following inputs: daily diel dissolved-oxygen trajectory, sensor noise corresponding to each parameter with a Gaussian distribution, a slow seasonal temperature trend, and incident profiles marked by their physiological category.

Institutions

• Bowen University

  Osun State, Iwo

Categories

Licence