Abstract
1 RESEARCH SCHOLAR IN SAGI RAMAKRISHNAM RAJU ENGINEERING COLLEGE, BHIMAVARAM, ANDHRAPRADESH, INDIA.
2 PROFESSOR IN ECE IN SAGI RAMAKRISHNAM RAJU ENGINEERING COLLEGE, BHIMAVARAM, ANDHRAPRADESH, INDIA.
Abstract: Aquaculture is one of the generally stretching out ventures inferable from the quick interest for fish everywhere throughout the world. While aquaculture and Internet of things (IoT) have exponentially grown in the world in the last years, the combination of both domains still remains at its early stage. We believe that developing user-friendly Internet of things (IoT) tools for fish farming will lead to a new era of connected, responsible and efficient aquaculture. Internet of things (IoT) for aquaculture needs to be smart, affordable, easy to deploy, reliable and highly efficient. This undertaking proposes an ongoing monitoring answer for estimating the physiochemical parameters of water and a choice emotionally supportive network for information stockpiling, monitoring, breaking down and sending the data to the users required at the ideal time and furthermore our proposed model uses raspberry pi to underpin remote real time monitoring of aqua-culture. In this undertaking, we utilize different sensors like pH esteem, temperature sensors and computerized surveillance with a remote pi camera module v2/v3 to empower live monitoring of the aqua-culture refined locales and their environment.
In this work we present the prototype and proof of concept of a distributed monitoring system of the aquaculture is totally dependent on the physical parameters of water to most of the extent. Water quality is determined by variables like temperature, transparency, turbidity, water colour, carbon dioxide, pH, alkalinity, hardness, unionized ammonia, nitrite, nitrate, primary productivity, BOD, plankton population etc. In our proposed model, real time monitoring of culture and the water quality management principles in fish culture have been reviewed to make aware farmers about the important parameters that influence health of a pond. The experimental results show that the system has great prospect and can be used to operate in real world environment in large scale for optimum control of aquaculture environment.