Smart bivalve purification system development - Ferreira, Gonçalo Diniz (2023)
The contamination of coastal areas caused by rising industrial activity is an expanding issue that substantially impacts bivalve molluscs. Known for their ability to filter their surroundings and essential to the world’s fishing industry for food, molluscs affected by bacteria require decontamination. The objective of this dissertation is to develop a purification system for areas classified as Class C in terms of E. coli contamination. The proposed system involves immersing bivalves in a tank of filtered seawater for a specified duration, where they expel the bacteria from their organisms via excrement, liberting bacteria eliminated within the Water Purification Zone. During the preliminary stage, LEDs with a wavelength of 254 nm were chosen as they were optimal for dealing with E. Coli. A circuit was constructed to monitor and regulate the energy supplied to the LEDs. Furthermore, the radiated power was analysed in relation to the input power and the wavelength where that power was being irradiated. Three depuration experiments were carried out. 3D structures were created and printed for the first trial to support one and three LED strip configurations. A comparison was made between their performance and a conventional UV lamp, with the result that the three-strip LED configuration was more effective. During the second round of testing, two different configurations of three LED strips were trialled, with one-strip configuration being excluded due to its previous underperformance. To monitor water quality, pH, temperature, ORP, water flow and turbidity sensors were integrated into the process, and both LED configurations were found to outperform the conventional UV lamp. In the final section of the experiment, the system’s ultimate design was showcased. This included a PCB responsible for controlling the LED power and monitoring sensors, alongside solenoid valves designed for filling and emptying the tank’s water. In addition, nitrite and salinity sensors were also installed. To collect and store data from the purifiers, a data centre was implemented into a Raspberry Pi utilising the MQTT protocol, and a graphical user interface was created for visualising the data. The findings have established that LEDs are more effective than conventional UV lamps at purifying E. Coli in shellfish.