A simple dataset of water quality on aquaponic fish ponds based on an internet of things measurement device

Aerial images and water quality dataset for fishpond's condition monitoring

This dataset is part of fundamental research to produce IoT monitoring in fishponds. The data consists of the results of measurements of pH, total dissolved solids (TDS), and water temperature obtained through manual sensor devices in several locations at different times. Additionally, this data also includes images taken by drones at consistent heights. These images are linked to the sensor data that has been collected. In this research, data will be used to monitor the health of fishponds through visual data. This data can be used for correlation analysis between visual data and sensor data. The hypothesis is the visual appearance of the pond (the colour) is affected by the number of mixed solid (mud and other organic material) in the water, which reflected in the TDS level of the water. In addition, the data can also be used for initial investigations into the development of machine learning models for pool condition recognition through image analysis.