Smart Energy Buildings Integration

We would like to think that the idea behind this is to help users make informed decisions about energy modeling and LEED/BREEAM certification. This will lead to more accurate energy simulations.

An optimal design and management of buildings have in fact to consider multiple, and usually competitive, objectives such as energy efficiency, internal comfort, users’ preferences, safety, and reduction of financial costs and environmental impacts. This implies operating following a “data-driven approach” within a continuous feedback loop between design and analysis, trial and error, based on technical simulations of aspects such as daylight, sunshine, thermal exposure, airflow, turbulence, wind, space syntax, traffic flow, etc.

BIM utilization as an energy assessment

Indeed, model-based design such as #BIM entails the creation of a digital representation system that allows rapid analysis and comparison of design alternatives, communication and visualization of information, easy alteration, and management of changes.

Data mining-based energy modeling could help project teams discover useful patterns to improve the efficiency of a building AI (Architectural Intelligence).

Specific tools have been developed with a focus on early-stage #design support (Trimble Sefaira, Autodesk Insight, Cove.tool, etc.), often integrated or available as plug-ins for main 3D sketching, massing, and conceptual modeling tools or BIM authoring software such as #Revit, #SketchUp, #Archicad, or #Rhinoceros. For starters, different building concepts for any climate and location, and are specifically intended to be implemented at the concept development stage.