EMAIL INTERVIEW – Ken Sinclair and Jean-Simon Venne

Jean-Simon Venne, Founder, BrainBox AI

Sinclair:  Tell us about your journey through technology? What made you found BrainBox AI?

Venne:  My journey into HVAC technology began while working on energy efficiency projects throughout North America and Europe. During this stage of my life, I dealt with technology in a plethora of buildings. These were buildings of different sizes and purpose, anything from hotels all the way to data centers. It quickly became apparent to me that continuous commissioning approaches would generate consistent energy savings but would require extensive amounts of both financial and human capital. With this in mind, I set out to find a way to engineer an AI base commissioning approach to deliver a new longer-lasting HVAC solution which would make efficient use of building tech to maximize savings while minimizing occupant discomfort. The final product of this journey was BrainBox AI, a solution that is both inexpensive and requires little human capital.

Sinclair:  How does your product work?

Venne:  BrainBox AI is the first autonomous AI technology for HVAC; it is redefining building automation and is at the forefront of the green building revolution. BrainBox AI’s technology reduces energy consumption by 25-35%, decreases a building’s carbon footprint by 20-40% as well as improves occupant comfort by an average of 60%. Using advanced predictive control strategies with machine learning techniques, BrainBox AI has developed an Artificial Intelligence approach tailored to every building’s specific needs at any time throughout the year.

More specifically, BrainBox AI’s artificial intelligence engine, together with its proprietary process, allows a building to move from reactive to pre-emptive operations management in three steps:

STEP 1 - Our solution identifies and catalogues your building’s specific operating behavior and energy flow by gathering data from both internal and external sources. It then creates a building energy profile for making informed predictions about future energy flow. BrainBox AI collects hundreds of thousands of real-time data points, such as outside temperature, sun/cloud positioning, fan speed, duct pressure, heater status, humidity levels, occupant density and many more.

STEP 2 - Using over 25 customized algorithms working in real-time, our AI engine instructs your existing HVAC system on how to operate more intelligently and efficiently. This process is similar to an aircraft on autopilot.

STEP 3 - Our solution continually amalgamates and analyzes all generated data to further optimize operational efficiency and discover other unique insights. To improve operational efficiency, BrainBox AI works to answer questions, including Which HVAC units have the fewest mechanical issues? How are changes in occupancy levels affecting energy consumption? Which HVAC units are the most energy-efficient in cold or humid climates?

Sinclair:   What are the primary differences between automated and artificial intelligence?

Venne:  Artificial Intelligence includes learning, reasoning and decision-making processes, while automated intelligence chooses a predefined action based on a control loop or a sequence designed and hard-coded by mechanical and controls engineers. Imagine a child who learns how to walk on solid ground and one day visits the beach where there is sand. After a while, the child will be able to adapt their steps and learn how to walk on the sand. An artificial intelligence agent would be able to develop a similar approach to learning, while an automated intelligence system will keep “falling”, because “sandy beach” is not included as one of its predefined inputs, there is no learning process, and it cannot take a different decision than the ones that it has already been programmed for. As we move forward and introduce renewable energy sources into our buildings as well as our increased desire to provide comfort for an increasingly demanding occupancy, there is a paramount need for self-adapting, autonomous and evolving buildings that maximize comfort while reducing its energy consumption and carbon footprint.

Sinclair:  What are the challenges that BrainBox AI faces in integrating Artificial Intelligence into HVAC Technology?

Venne:  The main challenge faced when integrating AI into HVAC Technology is to leverage existing building HVAC equipment and sensors to their highest capabilities. This is a highly relevant challenge for us as BrainBox AI focuses on utilizing the tools/sensors already in place within buildings for its data gathering and monitoring processes. For example, on occasion, certain sensors in the building, such as thermostats, might be incorrectly calibrated or not operational. Likewise, when HVAC equipment, such as boilers and ventilation systems, operates at reduced efficiency due to years of use, we must revise our control strategy in order to get the most out of them.

[an error occurred while processing this directive] Sinclair:  Clearly, facility management technology is changing at a very rapid pace, according to you, what are three primary concerns that HVAC contractors/technician should be aware of and dealing within their business right now?

Venne:

1. The need for HVAC control systems to be adaptive. The building structure is designed to last for at least 100 years. Buildings are remodeled closer to every 5 to 10 years. With new tenants and sometimes new purposes, comes new demands. The original building design may not always be accommodating, and updates to the system are necessary and can be costly if they need to be done by an engineering firm every time. Investing in self-adaptive systems will address this concern.
2. Automatic fault detection and diagnostics platforms are significantly increasing in popularity. In buildings, even in an ideal (nearly unrealistic) case where there are no defective sensors, HVAC equipment could fail and detecting these failures is critical. More importantly, being able to detect failures before they occur in order to apply preventative maintenance and reduce operational downtime is essential.
3. The Internet of Things (IoT) and the data privacy/security concerns that come with it. Automated intelligence and artificial intelligence solutions are based on data collected by sensors installed in the controlled system. IoT devices increase the amount of information that is available and improve the general performance of the control system. These data sources are also essential in supporting AI decision-making, internal controls, and ensuring occupant comfort. BrainBox AI helps significantly appease these privacy concerns by keeping all data local.

Sinclair:   Can you discuss an interesting case study when BrainBox AI’s platform has benefitted a business?

Venne:  In 2018, BrainBox AI was installed in two company-owned retail stores in the Greater Montreal area. This company needed a low CapEx solution to optimize the HVAC system in both stores, as each facility has different operating hours, are located in a different urban environment and experience very unique occupancy levels throughout the day. Following the BrainBox AI algorithm deployment, these commercial venues saw overall energy savings of 28% and 31% respectively.

Sinclair:  What do you think the high-performance building industry will look like for the HVAC contractor/technician in the next five years? Next 10 years?

Venne:  The job of a building engineer/technician will be evolving over the course of the next 5 years. With the introduction of AI technologies to the built environment, building engineers/technicians will no longer have to focus on mundane tasks (as the AI will take care of that for them). Giving them the opportunity to work on addressing more impactful issues and adopting the role of AI coach. In addition, building engineers/technicians will continue to be involved in adopting technologies to support greener and more sustainable buildings.