Application of Regression Analysis to Achieve a Smart Monitoring System for Aquaculture

Abstract

The consumption awareness of people in recent years has increased, with food safety becoming more and more important. While non-toxic products can be achieved by avoiding using too much antibiotics to control growth factors in a water environment, the measurement tools for dissolved oxygen on the market are very expensive and a great economic burden to fishermen. Thus, the purpose of this study is to design more economical measurement modules and algorithms for monitoring ponds. The research collected pond data through Oxidation-Reduction Potential (ORP), pH and temperature sensors, used regression analysis to infer Dissolved Oxygen (DO) by ORP and pH, and employed a real-time pond monitoring data map to figure out pond conditions. Compared with traditional equipment, findings show our approach reduces costs by about 20%, and increases production capacity and output value.

Overview of Smart Aquaculture System: Focusing on Applications of Machine Learning and Computer Vision

“…The results on two data sets show that this is a successful system which can be applied in real. Hsu et al [75] collected water quality parameter's data through sensors such as oxidation-reduction potential (ORP), pH and temperature. They also employed a monitoring data map in real-time in order to find out the pond conditions.…”

Recent advances on portable photoelectrochemical biosensors for diagnostics

“…Changes in interfacial electron transfer, electrolyte environment, electron donor/acceptor mass transfer and light absorption can be induced according to changes in target concentration [6][7][8]. And then achieve the purpose of monitoring and analysis [9,10]. Due to the absolute separation of signal generation and output, the sensitivity of PEC sensing technology is much higher than conventional electrochemical detection methods [11,12].…”

Aquicultura 4.0: Uma Revisão Da Literatura Orientada Ao Uso E Interpretação De Dados Na Aquicultura Inteligente

“…Pesquisas sobre o uso de tecnologias da onda tecnológica já podem ser encontradas em bases científicas, desde aplicações IoT simplificadas , até sistemas complexos que utilizam inteligência artificial (AI) e computação em nuvem [10]. Com o uso de tecnologias digitais na aquicultura um novo termo surgiu, a aquicultura inteligente, é o processo de utilização de sensores para monitoramento e aquisição de dados relativos à qualidade da água e controle e monitoramento de equipamentos de forma remota [11][12] [13] [14][15] [16][17] [18], ela é realizada de dife-rentes formas com diferentes tecnologias wireless. Porém, em grande parte destas aplicações desenvolvidas há existência da mesma lacuna pode ser encontrada, a coleta e organização dos dados não é devidamente estruturada o que torna as informações inutilizáveis para estudos e análises futuras [19].…”