Optimization of Chemical Water Monitoring in Fishponds Through Automated Systems

This study outlines the design and development of an automated system to optimize chemical water monitoring in fishponds. The prototype facilitates automatic sample collection, precise reagent dosing, and uniform mixing, alongside real-time analysis and visualization of results through a touchscreen interface. Key parameters, including Nitrite (NO2), Nitrate (NO3), and Ammonia (NH3/NH4), were targeted. The methodology involved designing electromechanical systems and integrating them with sensors and software to automate manual tasks. Tests conducted have confirmed the system’s accuracy in detecting chemical concentrations, optimizing operational times, and minimizing errors. The results highlight the system’s ability to enhance decision-making in aquaculture by enabling constant and timely monitoring of water conditions. This directly contributes to improved fish welfare and increased economic profitability for producers. The prototype represents an innovative and accessible technological solution for the aquaculture sector, with significant potential for scaling up to larger production processes.

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Publication Details

Journal
Revista Facultad de Ciencias Básicas
Published
2024-12-26
DOI
https://doi.org/10.18359/rfcb.7409
Primary Topic
Water Quality Monitoring Technologies
Type
article
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article

Optimization of Chemical Water Monitoring in Fishponds Through Automated Systems

Adolfo Duarte Rueda, Luisa Fernanda García Salazar, Ronald Alexander Vacca Ascanio
Revista Facultad de Ciencias Básicas
Water Quality Monitoring Technologies
article

Optimization of Chemical Water Monitoring in Fishponds Through Automated Systems

Adolfo Duarte Rueda, Luisa Fernanda García Salazar, Ronald Alexander Vacca Ascanio
article en

Abstract

This study outlines the design and development of an automated system to optimize chemical water monitoring in fishponds. The prototype facilitates automatic sample collection, precise reagent dosing, and uniform mixing, alongside real-time analysis and visualization of results through a touchscreen interface. Key parameters, including Nitrite (NO2), Nitrate (NO3), and Ammonia (NH3/NH4), were targeted. The methodology involved designing electromechanical systems and integrating them with sensors and software to automate manual tasks. Tests conducted have confirmed the system’s accuracy in detecting chemical concentrations, optimizing operational times, and minimizing errors. The results highlight the system’s ability to enhance decision-making in aquaculture by enabling constant and timely monitoring of water conditions. This directly contributes to improved fish welfare and increased economic profitability for producers. The prototype represents an innovative and accessible technological solution for the aquaculture sector, with significant potential for scaling up to larger production processes.

Revista Facultad de Ciencias BásicasVol. 19(1)
Popular University of Cesar (CO), Universidad Nacional Abierta y a Distancia (CO)
Openalex Percentile: Top 73%
Water Quality Monitoring Technologies
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