Digital Twin for BUILDING

What are the challenges in maintaining sustainable and CO₂ neutral buildings?

• High energy consumption: how to reduce energy usage while maintaining comfort levels? 
• Inefficient or not suitable HVAC systems. EA-SAS platform enables better management of existing systems based on occupancy, weather conditions, and other factors.
• Manual Operation and Lack of Integration: Many buildings still rely on the manual operation of systems, which is time-consuming, inefficient, and prone to errors. 
• Lack of Energy Performance tracking: Without benchmarking, it is challenging to evaluate a building's energy performance and compare it to industry standards.

How does it work? 

Building Digital Twin utilizes pre-trained AI algorithms to minimize energy consumption for heating, hot water, air-conditioning, and ventilation. It integrates with building management systems (BMS) and collects data from third-party smart energy meters. 

Hourly Energy Demand modelling is performed and Optimum Real-time HVAC equipment control is based on forecasted demand.

A controlled fresh air supply ensures energy savings and human well-being by maintaining optimal temperature, humidity, and CO₂ levels. Control set points are calculated for optimal control and can be sent to responsible personnel or sent directly through BMS. 

Users can easily monitor the real-time operation of building systems, building CO₂ footprint, energy, and CO₂ savings, and display information on external devices in the building. 

Pre-trained algorithms are prepared for:

• Commercial
• Residential
• Public Buildings