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Lo-Fi. Agritecture reimagines the future of rural-urban integration by proposing a low-tech construction yet highly intelligent ecological system designed to repair the metabolic rift between cities and the countryside. The project responds to the urgent challenges of industrialized agriculture, nitrogen pollution, and the disconnection between urban consumption and rural production.

Set in the Baltic region but scalable to global contexts, the design introduces a hybrid framework combining environmental sensing, AI-based spatial generation, and traditional farming practices. At its computational core is a Generative Adversarial Network (GAN), trained to simulate land-use patterns and optimize ecological layout scenarios based on regional environmental inputs. This is further integrated with multi-objective optimization algorithms that coordinate nitrogen flow, solar exposure, and water systems to generate resilient planting clusters.

The system incorporates crop rotation algorithms that dynamically assign seasonal planting across modular grids, enhancing soil regeneration and minimizing runoff. A digital interface serves as both sensor dashboard and community planning tool, enabling farmers to interact with real-time environmental feedback and adjust operations accordingly.

Architecturally, the proposal uses modular tensegrity greenhouses鈥攍ightweight, prefabricated units that are algorithmically generated and easily assembled in various landscapes. While construction remains intentionally low-tech and accessible, the system鈥檚 intelligence lies in its closed-loop AI integration: from sensing, simulation, and decision-making to feedback, learning, and adaptation.

Lo-Fi. Agritecture frames AI not merely as a tool but as a co-designer of ecological systems, advancing new paradigms of human-machine collaboration in sustainable territorial planning.