In addition, the collection and separation of biomass from liquid phase reactors can be complex and, above all, costly. Traditional methods such as centrifugation and filtration can significantly affect biomass production costs, accounting for between 20% and 60% of total costs [17; 18]. Nevertheless, the economic sustainability of microalgae cultivation also relies on profits deriving from the sale of biomass or bioproducts, which are usually expected to be higher with purer biomass [19]. Therefore, optimising existing cultivation processes and integrating innovative technologies are essential to making microalgae production competitive in commercial markets. In this context, twin-layer technology, recently introduced in the scientific community, has proven effective for cultivating _G. sulphuraria_ and other microalgae using both standard culture media and secondary urban effluents [4; 20; 21]. Beyond enhancing cultivation efficiency, this system addresses many of the operational limitations previously discussed. When considering the scalability of cultivation systems, one critical aspect is the implementation of efficient management strategies. In large-scale applications--such as wastewater treatment plants, often located far from urban areas and research facilities--remote monitoring of system performance becomes essential [22]. Smart monitoring technologies allow operators to track system conditions in real time and intervene only when necessary, such as in cases of malfunction or biomass harvesting, thereby optimising maintenance and operational efforts [23]. Within this framework, the present study aims to address current challenges in sustainable microalgae cultivation by developing an attached-biomass photobioreactor designed for the growth of _G. phlegrea_, using urban wastewater as a nutrient source. The system integrates a platform based on IoT (Internet of Things) to enable continuous, remote monitoring of environmental parameters, contributing to enhanced process control and scalability. In addition to the engineering innovation, the study introduces a robust analytical approach by combining conventional spectrophotometric methods with high-resolution techniques such as EA-IRMS (Elemental Analysis-Isotope Ratio Mass Spectrometry) and SEM-EDS (Scanning Electron Microscopy-Energy-Dispersive Spectroscopy). This integrated methodology enables the tracking of carbon and nitrogen concentrations in the biomass, along with their isotopic compositions (\(\delta^{13}\)C and \(\delta^{15}\)N), offering valuable insights into nutrient assimilation and the metabolic responses of _G. phlegrea_ under different cultivation conditions. The structure of the manuscript reflects this dual focus on system design and experimental validation. It first outlines the scientific and technical rationale behind the selection of twin-layer technology for the photobioreactor configuration, emphasising its advantages for surface-adhered cultivation and compatibility with wastewater-based media. The subsequent section provides a detailed description of the physical layout and operating principles of the prototype, highlighting the integration of the IoT-based monitoring system and its capacity to measure key environmental variables such as temperature, pH, and light intensity in real time. This is followed by a presentation of the cultivation experiments, which were designed to evaluate the performance of _G. phlegrea_ under varying environmental conditions. Each test involved controlled modifications of individual parameters--namely, temperature, nutrient concentrations, and light exposure--to assess their impact on biomass growth. Particular attention is devoted to the physiological and metabolic responses of the microcalga, as characterised through the combined use of spectrophotometric, isotopic, and microscopic analyses.