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High fingerling mortality caused by poor water quality and cannibalism limits the production of African catfish. A proposed seven-layer Internet of Things architecture combines real-time sensing with threshold-based automated actuation to manage fingerling pond environments. Informed by surveys of twelve catfish farmers and forty-eight Internet of Things practitioners in Kenya, the design was evaluated using a simulation-based computational experiment. Under simulated automated control, modelled fingerling mortality decreased from 59.7 percent in an uncontrolled baseline to 22.5 percent, though this reflects simulated conditions rather than live biological trials. Multiple linear regression indicated that dissolved oxygen and ammonia levels were the primary predictors of the survivability index. The proposed system is designed as a scalable, low-cost option for resource-constrained fish farming, with an estimated single-pond capital cost of around 52,000 Kenyan shillings, or 400 US dollars.
Catfish farming provides valuable food production across Africa, but losing high numbers of young fingerlings limits farm viability. Demonstrating how affordable automated sensing systems might stabilise pond water quality helps bridge the gap between high-tech precision aquaculture and small-scale, resource-constrained farmers, potentially improving yield predictability if validated in live aquatic environments.
The work outlines an automated monitoring and actuation system targeted at resource-constrained catfish hatcheries and farmers. With an estimated hardware setup cost of 400 US dollars per pond, it presents an affordable proposition for digital aquaculture. However, the technology is at an early, simulated stage of research: the architecture and performance models have only been tested computationally, meaning field prototyping and validation on live fish stocks are required before commercial deployment.
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African catfish (Clarias gariepinus Burchell, 1822) is a valuable aquaculture species in Africa, but fingerling mortality driven by poor water-quality and cannibalism remains a key constraint on production. Drawing on a mixed-methods survey of twelve catfish farmers and forty-eight IoT practitioners in Kenya, this paper proposes a seven-layer Internet of Things (IoT) architecture for environmental and behavioural management of the fingerling ecosystem, integrating four complementary theories with real-time sensing and threshold-based automated actuation. The model was evaluated through a simulation-based computational experiment, comparing an automated control scenario against an uncontrolled baseline. Modelled mortality fell from 59.7% to 22.5% under the automated control scenario relative to the uncontrolled baseline. Because no live fish were reared or observed, these figures describe the model’s behaviour under author-specified virtual conditions and should be read as an upper-bound estimate rather than a demonstrated biological outcome. Multiple linear regression identified dissolved oxygen and ammonia as the strongest predictors of the modelled survivability index (R² = 0.846, RMSE = 0.128). The seven-layer architecture is proposed as a scalable, low-cost design for resource-constrained aquaculture, with an estimated capital cost of approximately KES 52,000 (USD 400) for a reference single-pond configuration. The study introduces the Integrated Cyber-Ecological IoT Survivability Framework (ICEISF), synthesising General Systems, Water-Quality, Fish Behaviour and Physiology, and Cyber-Physical Systems theories; only the water-quality construct currently has simulation-based quantitative support. The model contributes a testable, cost-specified architecture to precision fish farming and digital aquaculture.
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DOI: 10.58721/f8qjc419
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