Construcción de un sistema de adquisición y transmisión remota de la calidad del agua basado en el Internet de las cosa (IoT) para la acuicultura

Published in: Innovation in Education and Inclusion : Proceedings of the 16th LACCEI International Multi-Conference for Engineering, Education and Technology
Date of Conference: July 18-20, 2018
Location of Conference: Lima, Perú
Authors: César Contreras (Universidad Nacional Experimental del Táchira, VE)
José Andrés Molina (Universidad Nacional Experimental del Táchira, VE)
Pedro Osma (Universidad Nacional Experimental del Táchira, VE)
Daniel Zambrano (Universidad Nacional Experimental del Táchira, VE)
Full Paper: #367

Abstract:

Intensive aquaculture is increasing worldwide and to know in real time the parameters of water quality that affect the growth and development of fish is essential, since the operators of aquatic farms require reliable information and timely environmental variables to plan and adjust the necessary controls and avoid economic losses. In general, the technology currently used is expensive and dependent on many TIC platforms; so it is necessary to know how to develop equipment with high benefits, simple to implement and low cost. An alternative to solve this problem is the IoT as it is increasingly common in all areas, thanks to the penetration of the Internet and WiFi platforms facilitate and lower the implementation of TIC solutions. This article proposes the development of a remote water quality monitoring system for aquaculture based on IoT. Built from the low cost NodeMCU embedded development kit, and operating in low power consumption mode, capable of taking, backing up in a micro-SD memory and transmitting via Wi-Fi (802.11 b / g / n.) to a station of supervision and monitoring the measurements of: pH, Dissolved Oxygen (DO), Water temperature, Water level, Solar radiation, Relative humidity and Air temperature. The system was tested in an aquaculture farm producing of cachamas (Colossoma macropomum) and tilapia (Oreochromis niloticus). The data was contrasted with standardized laboratory measurement methods resulting in a robust, reliable and simple to implement system at a low cost.