This project explores the implementation of smart, data-driven control systems in solar-powered post-harvest processes in aquaculture, focusing on rural African contexts. Our work, part of the INNOECOFOOD project, emphasizes developing secure, proprietary infrastructure for data management and IoT connectivity, enabling the networking of multiple hubs across different locations to benefit from a shared, optimized system.
We developed smart algorithms leveraging real-time sensor data to optimize post-harvest operations, particularly drying processes of fish and other produce. This approach ensures consistent product quality, addresses energy scarcity, and enhances overall sustainability. The system prioritizes energy efficiency, optimizing processes like ice production, cooling, drying, and processing based on solar energy availability. By intelligently managing these energy-intensive operations, we significantly enhance the overall sustainability and economic viability of the post-harvest processes.
The system’s design prioritizes user-friendliness, employing AI to analyze complex datasets and present actionable insights to local operators without requiring advanced data analysis skills. This democratization of technology significantly reduces reliance on individual expertise while maintaining high efficiency and product quality standards.
Recent studies show smart systems can significantly improve efficiency and product quality in aquaculture [2]. Additionally, we explore the potential for integrating these systems with Recirculating Aquaculture Systems (RAS), further optimizing energy and water usage throughout the entire production process.
This work highlights the potential of smart control systems in revolutionizing aquaculture processes, particularly in resource-constrained environments. It underscores the importance of secure, locally-controlled data infrastructure and AI as tools to empower local operators, contributing to the sustainability and economic viability of aquaculture operations in Africa and beyond.[4].
This project has received funding from the European Union’s Horizon Innovation action under Grant Agreement no. 101136739 (INNOECOFOOD).
[1] Salam, A., Khater, E.S.G., Alhusainy, A.M.A. et al., Sci Rep 15, 2807 (2025).
[2] Biazi, V. & Marques, C., Aquacult. Eng., 103, 102360 (2023).
[3] Natarajan, S. K. et al., Environ. Sci. Pollut. R., 29, 40478-40506 (2022).
[4] Gupta, S. et al., Aquac. Res. (2024)