A Real-Time Dataset of Pond Water for Fish Farming using IoT devices
This is the real-time dataset. This dataset is created for monitoring the real-time aquatic environment using an IoT framework. Three sensors named pH, Temperature, and turbidity along with Arduino controller are used for monitoring the water quality of 5 ponds. It has 4 columns and 591 rows. They are- pH, Temperature, Turbidity, and Fish. Here fish is the target variable and others are the independent variable. There are 11 fish categories, 86 pH distinct values, 46 temperature distinct values, and 85 Turbidity distinct values.
Steps to reproduce
This work presents an IoT framework for the efficient monitoring and effective control of different aquatic environmental parameters related to the water. The system is implemented as an embedded system using sensors and an Arduino. Different sensors including pH, temperature, and turbidity are placed in cultivating pond water and each of them is connected to a common microcontroller board built on an Arduino Uno. The sensors read the data from the water and store it as a comma-separated values (CSV) file in an IoT cloud named ThingSpeak through the Arduino microcontroller. To validate the experiment, we collected data from 5 ponds of various sizes and environments.