S.A.B.E.R - Sustainable AI-automated Bioreactor for Environment Remediation

Carbon waste from sewage disposal presents an escalating environmental challenge, necessitating innovative and sustainable solutions. This project introduces a fully automated, high-efficiency algae bioreactor designed to convert carbon waste from sewage into valuable resources for isolated environments such as space habitats, bunkers, and factories. The system leverages an integrated sensor network that continuously monitors key parameters including pH, turbidity, and CO levels. These real-time measurements feed into a Random Forest-based AI model that dynamically regulates three specialized pumps: one for clean water intake, one for nutrient-rich waste infusion, and one for removing nutrient-depleted algal water. Our approach involves three main phases. First, we engineered the bioreactor hardware to ensure robust, hands-free operation under variable conditions. Second, we implemented machine learning algorithms to optimize algae growth by fine-tuning the environmental parameters for normal solutions. Third, we implemented a sewage nutrient solution with the AI. Experimental results demonstrate that the system achieves consistently high oxygen production and stable algae growth. Waste-derived nutrients perform comparably to conventional nutrient sources, effectively reducing CO emissions and ammonia levels in controlled settings. This work validates the feasibility of transforming sewage-based carbon waste into essential resources while mitigating environmental degradation. Furthermore, the bioreactor’s design and autonomous operation offer a relatively scalable solution that can be adapted for extreme and isolated environments. Future research will focus on enhancing system scalability, longterm operational efficiency, and integration with broader sustainability networks (such as specific ai-models for each sewage), ultimately contributing to innovative waste-to-resource strategies for both terrestrial and extraterrestrial applications.