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June 2019
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Introducing Autonomous AI to HVAC:

The Future of Building Automation
Jean-Simon Venne
Jean-Simon Venne
Chief Technology Officer & Co-Founder
BrainBox AI
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It is expected that 10 million self-driving cars will be on the road in the U.S. alone by 2020, according to Research and Markets. What’s more, marketing firm ABI projects that eight million driverless cars will be added to the road in 2025. Innovation in the transportation sector has been progressing rapidly, in part, thanks to the agile start-up world and fast-moving giants, such as Tesla and Google.

And yet, as the transportation industry is evolving dramatically, other aspects of our day-to-day experience remain relatively unchanged. We have not seen revolutionary innovations similar to the ones seen in the transportation sector in the built environment or real estate sector for some time.

This, despite the fact that people will continue to move to cities, we will continue to build more buildings, and our buildings will continue to use a lot of energy. 

Could autonomous buildings, whether in commercial retail spaces, hotels, schools or office buildings, play an important role in our ability to slow down climate change?

How will AI command and control be introduced to HVAC in order to facilitate this change?

AI for HVAC

HVAC structures are still designed as fixed systems, or programmed for a fairly static environment, even though the weather and seasons are fluid and dynamic. This static organisation is costly, both for business – since inefficient systems can contribute to higher energy bills and maintenance costs – and the environment. In fact, HVAC systems account for 51% of the total energy usage in commercial buildings. Inefficient and poorly managed systems are also responsible for occupant discomfort and a major contributor to rising levels of greenhouse gases.

As the first ever start-up to enable building automation control with artificial intelligence, BrainBox AI offers an autonomous AI technology for HVAC, placing it at the forefront of the autonomous building movement.

BrainBox AI uses deep learning, cloud-based computing, algorithms and a proprietary process to support a 24/7 self-operating building that requires no human intervention and enables maximum energy efficiency. Pre-commercialization tests have demonstrated that BrainBox AI enables a 25-35% reduction in total energy costs in less than three months, with low to no CAPEX needed from property owners. It also improves occupant comfort by 60% and decreases the carbon footprint of a building by 20-40%.

Using Haystack to deliver Autonomous Buildings

BrainBox AI optimizes a building’s existing HVAC system by analyzing information from a multitude of internal and external data points, combining time series data with deep learning engines and deriving high-quality predictions for each zone of the building. Its technology enables it to make exceptionally accurate predictions about the built environment, empowering the deployment of algorithms to drive the HVAC system in real time. The combination of highly precise AI predictions, as well as advanced algorithms (that are based on the knowledge of mechanical engineers and control experts), delivers continuous commissioning at a fraction of the cost of manual, human interventions.

The result is a 24/7 self-operating building that requires no human intervention and functions at optimal efficiency and ensures maximum comfort.

CatNet Systems As part of its technology development process, BrainBox AI is partnering with the National Renewable Energy Laboratory (NREL), an organization funded by the United States Department of Energy that focuses on the development of creative answers to today’s energy challenges. To effectively map out a building’s HVAC control points and ensure all data labels used follow Haystack conventions, NREL and BrainBox AI are working together for the development of an automapping AI tool which is being referred to as Autobots. This new AI tool should accelerate the deployment time of the solution throughout buildings, reducing the onboarding time and generating a clean dataset from day one.

What this all means for the future of HVAC control

Over the last couple of years, we’ve witnessed an explosion in the market of analytics solutions (FDD, EIS, EMIS, etc.) using AI, and other data analysis techniques, to generate insights for building managers. This technology wave pushed data handling and formatting to the forefront, and it became a trending topic of interest. Thanks to the Haystack initiative, we are now making good progress on that front. The same data is currently being utilized for many new purposes, moving from the sharing of insights to enabling AI to operate a building’s HVAC system in real time. This is the first step towards a real autonomous building. As the car industry advances from the GPS to the self-driving car, our industry is starting to shift as well. It is evolving from a fix control sequence to an autonomous control sequence, thus dynamically changing the control sequence code every minute and learning as it evolves in time without any human intervention.

Are you ready to let AI deliver the hidden value in your dataset?

To learn more about how BrainBox AI is introducing artificial intelligence to HVAC, please visit www.brainboxai.com

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