REAL TIME IOT BASED DATA MANAGEMENT IN HATCHERIES

Fresh Water Management is very much essential which demands an increase in agricultural, industrial and other requirements in India. The Quality of Fresh Water is characterized by chemical, physical and biological content present in water. Traditional water quality monitoring involves three steps namely water sampling, Testing and investigation. These are done manually by the scientists. The manual methods of determining the water quality parameters are tedious, time consuming and non economical process. It is high time to maintain the water quality parameters using automated techniques because the fish health and survival rate are the two important parameters for increase production rate. Now there is a huge demand in maintaining a real time database for storing and analyzing the selective water quality parameters in hatcheries. Firebase is a powerful, simple, and cost-effective object storage service built for Google scale to provide efficient and real time storage.

The present study aimed to investigate the performance of sensors and database management in hatcheries. The selective water quality parameters are set inside the hatchery tank. The sensors are interfaced to the microprocessor and data are transmitted to the firebase through the NODE MCU an efficient Wi-Fi module. The captured analog data is converted to digital format by Analog and Digital Convertor.

The Software Algorithms are written in Arduino IDE. The selective water quality parameters are checked with the threshold limits. The coding is also done for connecting the Wi-Fi module to the firebase. The LCD display is connected to the circuit and the reading is noted. Firebase stores the values continuously and it will be helpful in terms of any anomalies (Fig2) This study will help us to find out the exact time of failures. It will be helpful for the farmers to have increased survival rate and help them to monitor the fish health.

The (Fig1) represents the storage of values in firebase from the sensors and it is used to analyze the data in terms of anomalies. In future the data collected and stored in firebase will be linked with mobile application and alert the user in terms of anomalies.