PRECISION AQUACULTURE USING IOT & MACHINE LEARNING TECHNIQUES
Keywords:Aqua Farming, Internet of Things, Detection of Fish Disease, Machine Learning Techniques, Raspberry Pi
It is noted that the growth is very rapid for IoT as well as Machine Learning and it is highly spreading throughout all the areas. Small processors like Arduino & Raspberry Pi make the modernized development in the ground level within its application in the field of Aqua Culture. The farmers dealing with aquaculture were feeling difficulty in the quality of water maintenance, Feeding the food, and identifying the diseases. This is the exertion of the implementation of the quality of water monitoring by employing Arduino, Raspberry Pi along with different sensors along with the machine learning algorithms applicable in the field of aquaculture. This arrangement will monitor the quality of water, feeding of food, recycling of water and the detection of diseases. The pH, Temperature and Electrical Conductivity is taken as the important parameters to maintain water quality for the better growth of fish. To ensure the survival fitness of aquatic life, the water quality is continuously monitored by the use of sensors. The acquisition of sensors is steered by Arduino and the data processing is carried out by Raspberry Pi. To ensure that the overfeeding or underfeeding is not happening, the automatic food dispenser is used here to supply constant food at certain periods. The Machine Learning algorithm techniques are being established to detect the diseases in the fish in the initial stage itself. The water pump is integrated with this process to make water recycle in a regular time gap. Hence, the projected smart arrangement is assumed to be the gainful and fully automated aquafarming process that can reduce the efforts and loss of large scale and small-scale investors.
How to Cite
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.