HiPIC Lab has developed two datasets for machine learning sponsored by the Lacuna Fund and the Tertiary Education Trust Fund’s National Research Fund (TETFund NRF), respectively.
1. Sensor Based Aquaponics Fishpond Datasets: IoT Fishpond Monitoring Datasets
Funded by: Lacuna Fund 2020, USA. Grant No.: 0326-S-001, 2020.
We designed and developed an Internet of Things (IoT) sensor system consisting of an ESP-32 microcontroller (a kind of computer in a chip) which controls water quality sensors in aquaponics (a type of fish farming that include the planting of vegetables without soil but using the fishpond wastewater) fishponds for automatic data collection.
The sensors included temperature, pH, dissolved oxygen, turbidity, ammonia and nitrate sensors. The IoT system reads water quality data and uploads the same to the cloud in real time. Find the link to the dataset repository:
Repository name: Kaggle Direct link to the dataset:
2. Smart IoT Fresh Water Fish Pond Water Quality Monitoring and Control System for Yield Prediction
Tertiary Education Trust Fund (TETFUND NRF, 2020-2024)
This award was made under the 2020 TETFund National Research Fund for implementing a Smart IoT Fresh Water Fish Pond Water Quality Monitoring and Control System for Yield Prediction. Research was to generate water chemistry parameters using IoT sensors and build machine learning models. This dataset also contains nutritional contents from fish feeds administered during the course of the project. This feed in addition to the water physicho-chemical parameters are used in predict the growth of the fish. Link (coming soon)