A Real-Time Dataset of Pond Water for Fish Farming using IoT devices
Description
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 an Arduino controller are used for monitoring the water quality of 5 ponds. It has 4 columns and 40280 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, having distinct values of tilapia 8830 rui 6336 pangas 5314 silverCup 3906 katla 3786 sing 3776 shrimp 3204 karpio 2112 prawn 1348 koi 964 magur 704.
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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.