SQCDM analysis for pv and vawt-based smart aquaponic systems - Yohanes Leonaldo Sinaga; Rofiq Husni Fajarudin; Apriliyan Kurnia Falah (Journal of Biopesticides and Agriculture Technology, 2025)
Background: Rapid urbanization, climate stress, and resource limitations increase the need for resilient urban food production systems. Aquaponics offers a sustainable approach by integrating aquaculture and hydroponics, but challenges remain in environmental monitoring, operational efficiency, and energy reliability. Emerging technologies such as IoT, AI, automation, and renewable energy can enhance system performance. Methods: This study develops a conceptual design of a grid-aware smart aquaponics system through a literature review and practice-grounded system description. The proposed architecture integrates IoT-based water quality sensing, AI-assisted plant monitoring, automated feeding, a Fuzzy Logic Controller on a Raspberry Pi 4, and a hybrid photovoltaic–vertical-axis wind turbine (PV–VAWT) power supply. The design is evaluated using the SQCDM framework (Safety, Quality, Cost, Delivery, and Morale). Findings: The proposed system enables continuous monitoring and feedback control of water quality parameters, supports fish and plant health, reduces routine labor through automation, and ensures uninterrupted operation through hybrid renewable energy. The SQCDM assessment highlights enhanced operational safety, quality assurance through real-time monitoring, cost transparency, deployment feasibility using off-the-shelf components, and improved user confidence through accessible interfaces and training support. Conclusion: The conceptual architecture provides a practical framework for future smart aquaponics implementation. The integration of cyber-physical supervision, intelligent control, and renewable energy has the potential to improve system resilience, operational stability, and sustainability in urban food production. Novelty/Originality of this article: This study proposes an integrated grid-aware smart aquaponics framework that combines IoT sensing, AI-based crop assessment, fuzzy logic control, automated feeding, and hybrid PV–VAWT renewable energy. It also introduces the SQCDM framework as a comprehensive and practice-oriented tool for evaluating smart aquaponics system design and operational readiness.