A Pilot Implementation of a Remote IoT Sensors for Aquaponics System Datasets Acquisition

ABSTRACT

Fish farming is gradually becoming one of the fastest-growing local enterprises in Nigeria and Sub-Saharan Africa. Among the commonly bred freshwater fishes are the catfish and tilapia, which have high survival rates and local demands. Aquaculture faces the challenges of availability and affordability of the major inputs such as land space and cost, water supply, and cost of fish feed. Lack of requisite knowledge by the farmers in managing the Physico-chemical properties of the pond water hampers the rate of growth of the fishes, and in most cases leads to the mortality of the fishes. To this end, this paper offers a pilot implementation of the first indigenous IoT sensors for the aquaponics system. Aquaponics system combines conventional aquaculture with hydroponics to allow plants to use the waste from the fish as food while at the same time filtering the water for immediate re-use by the fish. Accordingly, the project is aimed at building a remotely monitored and controlled IoT fishpond water quality management system for the generation of environmental datasets of the conventional ponds and the aquaponics pond systems. Through these datasets, machine learning researchers can build models for predicting fish yield in the aquaponics production system in terms of weight gain, water quality parameters, and feed consumption. The outcome of the data modelling would provide Fish farmers with the requisite information that would increase fish production in Nigeria. The pilot project using a submersible temperature sensor and turbidity sensor produced promising results which are in tandem with industry standards.

INDEX TERMS Arduino, Aquaponics, IoT, Temperature sensor, Turbidity sensor