Proptech start-up from Düsseldorf Dabble uses AI to drive energy efficiency savings in commercial buildings.
It has developed cloud-based, self-learning building management software that connects to existing building management systems (BMS) and takes control of heating and cooling systems in a way that is more dynamic than legacy systems based on fixed setpoint resets.
Dabbel says the AI takes into account factors such as building orientation and thermal insulation, and reviews calibration decisions every five minutes – meaning it can dynamically respond to changes in outdoor and indoor conditions.
Founded in 2018, the startup claims that this approach to layering AI-powered predictive modeling on top of legacy BMS to power the next generation of building automation can generate substantial energy savings – with energy savings of up to 40%.
“Every five minutes, Dabbel reviews its decisions based on all available data,” explains CEO and co-founder Abel Samaniego. “With each iteration, Dabbel improves or adjusts its decisions based on the current conditions inside and outside the building. It does this by using cognitive artificial intelligence to drive a Model-Based Predictive Control (MPC) system … that can dynamically adjust all HVAC setpoints based on current / future conditions. “
Essentially, the machine learning system predicts in advance the adjustments needed to adapt to future conditions – energy savings versus a preset BMS that would keep the boilers burning longer.
The added root for owners (or tenants) of commercial buildings is that Dabbel keeps these energy savings under control without the need to replace and replace legacy systems – nor install many IoT devices or sensor hardware to create a ‘smart’ one. create indoor environment; the AI integrates with (and automatically calibrates) existing heating, ventilation and air conditioning (HVAC) systems.
All it takes is Dabbel’s SaaS – and less than a week to deploy the system (it also says the installation can be done remotely).
“There are no restrictions in terms of heating and cooling systems,” confirms Samaniego, who has a background in industrial engineering and several years of experience in automating high-tech factories in Germany. “We need a building with a building management system and ideally a BACnet communication protocol.”
The average reductions achieved so far on the approximately 250,000 m² space where AI is responsible for building management systems are slightly more modest, but still impressive at 27%. (He says the maximum savings at some “peak times” is 42%.)
The advertised savings are not limited to a single location or building / customer type, according to Dabbel, who says they have been “validated in different use cases and regions in Europe, the US, China and Australia”.
The first clients are facility managers of large commercial buildings – Commerzbank clearly sees potential, having incubated the startup through its early investment arm – and several schools.
Another 1,000,000 m² are in the contract or offer phase – scheduled for installation “in the next six months”.
Dabbel sees its technology as useful for other types of educational institutions and even other use cases. (It also plays with adding predictive maintenance functionality to extend the software’s usefulness by providing the ability to warn building owners of potential outages in advance.)
And while policymakers around the world are turning their attention to achieving the very large reductions in carbon emissions needed to achieve ambitious climate goals, the energy efficiency of buildings should certainly not be overlooked.
“The time for passive responses to addressing the crucial issue of carbon emission reduction is over,” Samaniego said in a statement. “That’s why we decided to take matters into our own hands and develop a solution that actively replaces a flawed human-based decision-making process with an autonomous one that operates with surgical precision and will only improve with each iteration thanks to artificial intelligence. . “
If the idea of connecting your building’s heating / cooling to a cloud-based AI sounds a bit risky for internet security reasons, Dabbel points out that it connects to the BMS network – not the company’s (separate) IT network / building.
It also notes that it uses one-way communication through a VPN tunnel – “creating an end-to-end encrypted connection under high market standards,” as Samaniego puts it.
The startup has just completed a € 3.6 million (~ $ 4.4 million) pre-Series A funding round led by Target Global, along with main incubator (Commerzbank’s early investment arm), SeedX, plus some strategic angel investors.
Dr. Ricardo Schaefer, partner at Target Global, added in a statement, “We are excited to partner with the Dabbel team as they provide their customers with a tangible and frictionless way to significantly reduce their carbon footprint and thus close the gap. seal. between passive measurement and active remediation. ”