IoT-based On-demand Feeding System for Nile Tilapia (Oreochromis niloticus)

Abstract

Fish feeding management is one of the most crucial considerations in aquaculture production. The traditional feeding method such as table-based and scheduled automated feeding schemes are inaccurate. In contrast, the automated on-demand feeding system has reduced the inaccuracies of the older feeding schemes. However, existing on-demand systems have limited accessibility because their monitoring systems are only stored by their local devices. This paper proposes an on-demand fish feeding system with online and real-time monitoring using the Internet of Things (IoT) and an accelerometer to sense the fish' demand by hitting it. An overhead surveillance camera was installed on the fish tank to automatically record and monitor the fish feeding activity on the first day of the implementation. Two groups of fish were used for the observation—the adults and pre-growth Nile tilapia (Oreochromis niloticus). Results have shown that the on-demand feeding system is highly effective on 21 pre-growth fish with an average weight of 88 grams and a standard deviation (SD) of ± 39 grams. Additionally, the feed intake ratio (FIR) of the pre-growth fish was <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1.35\pm 0.69$</tex> grams, i.e., 73% to 86% lower than the recommended table-based feeding scheme. Thus, more efficient.