MODULAR IOT ARCHITECTURE FOR MONITORING AQUACULTURE VARIABLES IN TILAPIA (COLOSSOMA MACROPOMUM) PONDS
DOI:
https://doi.org/10.15665/7dqprp64Keywords:
Automation, cachama breeding, control of aquaculture variables, real-time monitoring, fish farmingAbstract
This work presents the design and implementation of a modular IoT architecture aimed at the real-time monitoring of critical water quality variables in ponds for the breeding of cachama (Colossoma macropomum). The proposed architecture integrates three main layers: a sensing layer composed of devices that record temperature and pH, a control layer based on open hardware with data processing and transmission capabilities using standard protocols, and a cloud supervision layer that enables remote visualization of the information. The architecture was designed under criteria of modularity, low cost, and ease of installation, which facilitates its application in rural contexts and at different aquaculture production scales. The tests carried out in the laboratory and in the field confirmed the technical feasibility of the proposal, achieving an accuracy of 98.15% in temperature and 99.15% in pH, with an average latency of 0.95 s and stable transmission even under limited connectivity conditions. In addition to its technological contribution, this architecture contributes to the fulfillment of the Sustainable Development Goals (SDGs) related to food security, innovation, and sustainable production, contributing to the strengthening of the fish farming sector through practical, economical, and scalable solutions.
References
L. Cordova, A. Cabral, D. Guimarães, A. Janati, B. Guterres, V. M. Oliveira, A. Bezerra, E. Flores, S. Botelho, P. Drews, N. D. Filho, L. Poersch, W. Wasielesky y M. R. Pias, Energy-Efficient LoRaWan Communication: Real-Time Applications in Aquaculture, 2024, pp. 1-6.
J. Fuentes‐Pérez y F. Sanz‐Ronda, A Custom Sensor Network for Autonomous Water Quality Assessment in Fish Farms, 2021.
D. Pikulins, R. Gotlaufs, T. Solovjova, A. Aboltins, J. Grizans y S. Migla, On the Development of Long-Range Water Quality Monitoring System for Outdoor Aquaculture Objects, vol. 18, 2022, pp. 37-42.
H. Zhang, C. Li, Z. Hua, W. Ren, Y. Gao y Z.-r. Hao, Design of aquaculture monitoring system based on LoRa and 4G network of Internet of Things, vol. 11878, 2021, pp. 1187827 - 1187827-6.
R. Kanishka, V. Saravanan, S. Dinesh y N. Rajasekaran, IoT based Fish Farming Management, 2025, pp. 705-710.
U. A. Ahmad, A. Isnawati, W. Pamungkas, A. Virgono, P. K. Goran, Y. D. Pratama, M. R. Fadhlullah, A.A.Ngurah, D. Pratanca y R. D. Setiady, Design of LoRa Technology as GPS Tracker and SoS Panic Button on Fish Lift Nets, 2023, pp. 254-259.
C. Schultz y M. Smith, Enhanced IoT Water Quality Monitoring System for Data-Based Aquaculture, 2024, pp. 329-334.
A. Fernández, Y. Rodriguez, R. Cruz, E. Auquiñivin, L. Muñoz, R. Mori, D. Mori, C. Culqui, G. Idrogo y R. Cruzalegui, «Efecto de la temperatura de agua en el desarrollo inicial de gamitana (Colossoma macropomum) en condiciones de selva alta,» Revista de investigación Agropecuaria Science and Biotechnology, vol. 3, p. 01–09, October 2023.
B. Cabezas, J. Amaguay, K. Diéguez-Santana, S. Neyfe y N. Sablón Cossío, «FACTORES MEDIO AMBIENTALES QUE INFLUYEN EN EL DESARROLLO DE LA CACHAMA EN LA AMAZONÍA ECUATORIANA» Revista Observatorio de la Economía Latinoamericana, October 2017.
M. A. Díaz Céspedes, M. Rojas Paredes, J. E. Guevara, F. P. Gonzáles y R. Soria, «Toasted mucuna bean (Mucuna pruriens L.) flour in gamitana (Colossoma macropomum cuvier 1818) diet,» Livestock Research for Rural Development, vol. 30, August 2018.
J. A. López Ramírez, «Cultivo De Gamitana (Colossoma Macropomum) En Las Fases De Reproducción Y Alevinaje En El Eje Carretero Iquitos,» Nauta, Loreto, 2021.
D. Singh, G. Sharma, I. Minhas, G. Singh, P. Mahajan, P. Verma y G. C. Manocha, LoRaWAN Gateway Architecture for Aquaculture Monitoring in Rural Area, 2023, pp. 1-4.
P. Peniak, P. Holecko, E. Bubeníková y A. Kanáliková, LoRaWAN Sensors Integration for Manufacturing Applications via Edge Device Model with OPC UA, 2023, pp. 1-6.
H. P. P. D. S. Pimentel, F. A. D. Freitas, O. O. Nóbrega y D. R. B. de Araujo, Proposal of Communication Infrastructure for Aquaculture 4.0 Based on LoRaWAN, 2025, pp. 177-180.
A. Bhawiyuga y W. Yahya, MA LPWAN based Wireless Sensor Node for Aquaculture Water Quality Monitoring System, 2018, pp. 252-256.
M. Dafare, S. Waghmare, A. Bhoyar, A. S. Titarmare y P. Chandankhede, LoRa-Enabled Smart RS485 Data Logger and MQTT Gateway for Industrial IoT Applications Using ESP32, 2023, pp. 1297-1302.
M. Flores-Iwasaki, G. A. Guadalupe, M. Pachas-Caycho, S. Chapa-Gonza, R. C. Mori-Zabarburú y J. Guerrero-Abad, Internet of Things (IoT) Sensors for Water Quality Monitoring in Aquaculture Systems: A Systematic Review and Bibliometric Analysis, 2025.
J. Wang, X. Wang, Y. Shi, H. Yang, B. Jia, X. Zhang y L. Lin, A review of the application prospects of cloud-edge-end collaborative technology in freshwater aquaculture, 2025.
J. Trevathan, S. Schmidtke, W. Read, T. Sharp y A. Sattar, «An IoT General-Purpose Sensor Board for Enabling Remote Aquatic Environmental Monitoring,» Internet of Things, vol. 16, p. 100429, 2021.
I. A. Adeleke, N. I. Nwulu y O. A. Ogbolumani, «A hybrid machine learning and embedded IoT-based water quality monitoring system,» Internet of Things, vol. 22, p. 100774, 2023.
M. A. Rahu, A. F. Chandio, K. Aurangzeb, S. Karim, M. Alhussein y M. S. Anwar, «Toward Design of Internet of Things and Machine Learning-Enabled Frameworks for Analysis and Prediction of Water Quality,» IEEE Access, vol. 11, pp. 101055-101086, 2023.
P. Megantoro, A. W. Anugrah, M. H. Abdillah, B. J. Kustanto, M. Fadhilah y P. Vigneshwaran, «Smart measurement and monitoring system for aquaculture fisheries with IoT-based telemetry system,» Bulletin of Electrical Engineering and Informatics, vol. 13, no. 3, pp. 1555–1565, 2024.
K. G. R. Sowmiya V, «Brackish water parameters monitoring dashboard using Internet of things and industry 4.0. EAI,» EAI Endorsed Trans IoT [Internet]., 2024.
A. Riyadh y N. M. Peleato, «Exploring spatial and temporal importance of input features and the explainability of machine learning-based modelling of water distribution systems,» Digital Chemical Engineering, vol. 14, p. 100202, 2025.
A. Alshami, E. Ali, M. Elsayed, A. E. E. Eltoukhy y T. Zayed, «IoT Innovations in Sustainable Water and Wastewater Management and Water Quality Monitoring: A Comprehensive Review of Advancements, Implications, and Future Directions,» IEEE Access, vol. 12, pp. 58427-58453, 2024.
H. Kamyab, T. Khademi, S. Chelliapan, M. SaberiKamarposhti, S. Rezania, M. Yusuf, M. Farajnezhad, M. Abbas, B. H. Jeon y Y. Ahn, «The latest innovative avenues for the utilization of artificial Intelligence and big data analytics in water resource management,» Results in Engineering, vol. 20, p. 101566, 2023.
R. Wiryasaputra, C.-Y. Huang, Y.-J. Lin y C.-T. Yang, «An IoT Real-Time Potable Water Quality Monitoring and Prediction Model Based on Cloud Computing Architecture,» Sensors, vol. 24, 2024.
R. Bogdan, C. Paliuc, M. Crisan-Vida, S. Nimara y D. Barmayoun, «Low-Cost Internet-of-Things Water-Quality Monitoring System for Rural Areas,» Sensors, vol. 23, 2023.
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