Green Algorithm and Artificial Intelligence for the Sustainability of Civil Infrastructure in Peru

Magno Chavarry Vallejos C.; Samuel Támara Rodríguez J.; Janet Chavarría Reyes L.; Avelino Valencia Gutiérrez A.; Carol Escobar Serrano J.; Cristina Chiok Guerra A.; Clotilde Panana Holgado E. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2026) · DOI: 10.18687/laccei2026.1.1.699

Resumen

Given Peru's climate vulnerability and the low adoption of sustainability criteria in infrastructure projects (24%), this research evaluates the effectiveness of the "Green Algorithm" approach using Artificial Intelligence (AI). The study analyzes the transition from computational operational efficiency (Green in AI) to environmental benefits in the built environment (Green by AI), employing parametric modeling and resource simulation. The results demonstrate a 35% optimization in processing times, reducing the technical calculation from 142 to 92 hours. In the architectural design, the integration of these tools allowed energy savings of 25% by mitigating the artificial light demand by 40%. Regarding materials, a 20% reduction in the carbon footprint was recorded, reducing emissions from 320 to 256 kg of CO2/m2. The results of the mechanical characterization demonstrate a 2.3% improvement in endurance efforts, supported by a 94.5% confidence interval. These indicators confirm the structural integrity of low-carbon composites for application in sustainable building.

Instituciones: Universidad Ricardo Palma; Universidad Nacional Santiago Antúnez de Mayolo