Architectural design of artificial intelligence-based integrated farming system: Automated fertigation, hydroponics and aquaculture, a panacea for food security - Segun, Adebayo; AWORINDE, Halleluyah Oluwatobi; KOLADE, Morenikeji; ADENIYI, Abidemi Emmanuel; AROBA, Oluwasegun Julius (Edelweiss Applied Science and Technology, 2026)
Agriculture is the foundation of food production worldwide, and as populations continue to grow, agricultural output struggles to keep up, leading to increasing food insecurity. AI is increasingly recognized as a powerful tool for making farming more efficient and sustainable. This paper presents the architectural design of an AI-enabled integrated farming system that combines automated fertigation, hydroponics, and aquaculture. The framework incorporates sensors, actuators, and microcontrollers for monitoring and controlling resources, utilizing AI algorithms to provide predictive analytics, optimize resource use, and support real-time decision-making. Experiments demonstrate improvements in productivity and the sustainable use of water and nutrients. Real-time data from these sensors can be remotely controlled using a microcontroller, which receives and stores it in the cloud. Notifications on mobile devices or a web dashboard alert farmers when parameters exceed predetermined thresholds, facilitating emergency management of water pollution or nutrient deficiencies. The proposed system offers a scalable approach to enhancing food security, advancing smart agriculture, and promoting sustainable rural development.