Checklist for the Use of AI in Building Management

You want to save energy as efficiently as possible, without initial investment and with a monthly notice period? We explain here which requirements you have to fulfill to use DABBEL AI software solution

To understand why sustainability in the building is “must-have”, you can check our first part of the series here.

Efficient building management – Easier than you think

It is often assumed that sustainable and efficient building management is associated with high costs and is time-consuming. High investment costs, long project duration and uncertain results often prevent such projects from being implemented across the entire real estate portfolio. VINCI Facilities Deutschland and DABBEL prove that it can be easier with AI-based software that makes building operations up to 40% more efficient. The following checklist shows that only a few conditions need to be fulfilled in order to use the software.

Checklist:

The requirements for a quick implementation of the software of DABBEL are listed below: 

• Commercial Commercial buildings above 5,000 m2 – offices, hotels, schools, shopping centers, …
• A building management system (BMS) in use, irrespective of the manufacturer 
• Ideally BACnet/IP as the main communication protocol. (If other protocols are in use, a conversion is possible with additional hardware).
• Internet access to the building network/BMS (for connecting a VPN tunnel)

Implementation explained in four simple steps 

If you fulfill the mentioned requirements above and decide to use the DABBEL software in your building, this is the next steps.

Step 1 : Information about the building/ quoting preparation

DABBEL needs the following information from you:

• Address and building area (m²)
• Annual energy consumption in kWh
• Energy costs (e.g. per kWh)
• Main communication protocol of the BMS 

Step 2 : Connection & Scan:

DABBEL establishes a VPN connection with the data communication protocol of the buildings and scans the building network remotely to identify the relevant objects (sensors and actuators) of the HVAC devices to be controlled. 

Step 3 : Self-learning phase & calibration:

Within a week, the software goes through a self-learning phase and creates a thermal model for the specific building.

Step 4 :  Go-Live:

The DABBEL AI BMS predicts and controls the HVAC systems(“model predictive control”).

All steps can be implemented remotely, without additional hardware and without upfront costs.

Example of a successful implementation

DABBEL and VINCI Facilities Germany have already been able to reduce CO₂ emissions from buildings by an average of 30% in several joint projects. In June 2020, a high school in Bergneustadt was connected to DABBEL’s software in a collaborative project. Various aspects and interests had to be taken into account in this project. Energy and CO₂ emissions needed to be reduced without limiting the user’s comfort.

In the building, which was built and modernized in 2008 respectively, with a total area of 8,521 m², the existing building control system (heating & ventilation) was connected to the software from DABBEL. The connection to the BMS was established by means of VPN tunnel. After a few weeks, the first results could already be proven in the reporting. After a detailed validation, energy and CO₂ savings of 28% were recorded.

You can read more about the successful case here:

Christian Ochßner, Building Services Department Manager at VINCI Facilities Germany: 

If you have any questions about these steps or need assistance, please contact Mr. Hahn, Mr. Ochßner or the following e-mail address: info@dabbel.eu

Watch this video to see the implementation of the successful project with VINCI Facilities Germany and DABBEL