Smart Aquaculture: A Cost Effective IoT Integrated Model for Monitoring Environmental and Pond Parameters

The fishing sector is becoming increasingly interested in Internet of Things (IoT)-based aquaculture. Aquaculture 4.0 is a field that is lagging in many nations despite the fact that IoT technology is propelling agriculture 4.0 forward. This article describes the development of a precise, smart aquaculture device that is based on the Internet of Things. It offers a thorough method for monitoring many water and environmental parameters, such as temperature, humidity, salinity, pH, and dissolving oxygen. Multiple sensors, including DO, salinity, pH, turbidity, MQ-135, and DHT-11 sensors, are integrated with the ESP32 NodeMcu microcontroller in the system. This is our device’s front-end hardware. Google Spreadsheet and Blynk are two prime parts of the backend sector. Blynk assists with monitoring all metrics using desktop and Android applications on smart devices. The spreadsheet is an essential component of the prototype model since it functions as a safe database to hold all the parameters for additional research. Using the paired sample t-test in SPSS software, sensor validation was conducted to verify our findings regarding commercial products. In this paper we are going to monitor, store real time environmental and pond parameters along with statistical analysis of those metrices so that anyone can decide this pond is suitable for aquaculture or not. This paper is a crucial component of our research that will assist later researchers in reconstructing this model for use in their studies.