A universally applicable “optimal photobioreactor” design has yet to be established, as the success of such systems varies depending on the algal species used, environmental conditions, and intended applications. Meanwhile, the accelerating pace of climate change necessitates not only passive monitoring of atmospheric carbon but also its active mitigation through biologically driven interventions. In this study, we propose a drone-integrated mobile photobioreactor (m-FBR) concept that utilizes the highly photosynthetically efficient cyanobacterium Synechococcus elongatus PCC 3055, combined with artificial intelligence technologies. The developed system is equipped with GNSS-based positioning, NDIR-based CO₂ sensors, and environmental sensing modules for temperature, light, and humidity, enabling real-time adaptive response to ambient conditions. Route optimization is based on Lagrangian atmospheric modeling, allowing the system to anticipate the origin, trajectory, and accumulation zones of airborne carbon masses, and to navigate toward areas with high CO₂ concentrations. The drone-mounted flat-panel reactor includes a high-transparency polycarbonate casing, energy-efficient LED light modules, and micro-level thermal regulation units, allowing rapid adaptation to changing environments and real-time optimization of photosynthetic efficiency. Beyond carbon fixation, the system also passively ventilates oxygen directly into the atmosphere, contributing to local air quality. Notably, the m-FBR autonomously absorbs atmospheric greenhouse gases such as CO₂ and water vapor—utilizing them as internal metabolic inputs. Thus, it sustains its nutrient demands without external supplementation and converts these gases into biomass and atmospheric oxygen via photosynthesis. With its capacity to absorb greenhouse gases in situ, utilize atmospheric resources as nutrient inputs, and release oxygen through photosynthetic processes, the proposed m-FBR system offers a versatile and novel biotechnological paradigm. It is applicable to carbon trading, urban air quality management, post-disaster atmospheric diagnostics, and sustainable oxygen production. Positioned at the intersection of nature-based solutions and artificial intelligence, this system functions as an autonomous biotechnological agent that not only monitors and analyzes the atmosphere but also actively contributes to its restoration. By overcoming the limitations of stationary photobioreactors, the m-FBR introduces a mobile, environmentally intelligent, and circular production model suited to contemporary climate challenges.

Keywords - Microalgae, Synechococcus elongatus, drone, photobioreactor, carbon capture, artificial intelligence, Lagrangian modeling

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