An Urban Tree Planting Service

https://bist.t-ranno.com/energyplus

This study proposes a building-centered tree planting strategy. While previous studies have mainly focused on what trees to plant and where to place them, this study examines which buildings should be prioritized to maximize energy savings. To this end, the Tree-Based Cooling Potential Index (TBCPI) was developed by integrating building physical characteristics, energy-use characteristics, and the surrounding urban environment.

To enhance practical applicability in real urban contexts, an LLM-based multi-agent system was also implemented. The system prioritizes candidate buildings, automatically generates energy simulation input files for selected buildings, and calibrates simulation results using actual energy consumption data to quantitatively assess the cooling energy-saving effects of tree planting.

This study 1) reinterprets urban tree planting from a building-centered perspective, 2) presents a quantitative criterion for identifying priority buildings through the TBCPI, and 3) demonstrates the potential of an LLM-based agent system as an automated service applicable at the urban scale.

The service is available at the link below.

https://bist.t-ranno.com/energyplus