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EMAIL INTERVIEW – Ken Sinclair and Ricardo Moromisato
Ricardo Moromisato, AScT, CEM
Implementing a Building Analytics Solution
It’s great to learn – and
pass on the lessons – from those organizations that have been
Sinclair: What do you think is the biggest hurdle to overcome when implementing a building analytics solution?
Moromisato: Based on the hundreds of analytic
implementations to date, the biggest hurdle is, arguably, “change
management”. Yes, there are technology challenges – dealing with system
integration issues, handling data quality problems and deciphering
Building Automation Systems (BAS) with different naming convention
standards (or no standards at all!) to name a few. But in our
multi-disciplinary field, and as problem solvers, we delight to bring
forth and implement new solutions to these technical problems. Change
management, however, involves several levels of organizational
leadership coming together to agree on the role of analytics in
building energy management. Even when leaders are aligned strategically
to become analytic-driven, this may not be the case when it comes to
execution. Unfortunately, as we see often, not sorting this out early
limits how organizations benefit from building analytics – regardless
of the chosen platform. On the other hand, it’s great to learn – and
pass on the lessons – from those organizations that have been
Sinclair: What does “analytic-driven” mean to facility and energy management?
Moromisato: Analytic-driven may be a paradigm shift
for facility teams. It may represent a move from being reactive –
acting on what’s urgent today – to being proactive – acting on what’s
important for the wellbeing of the building and its occupants – today
and into the future. In our article, What Does it Take to Become
Analytic-Driven? we identify three key ingredients, technology,
resources and culture. As a service provider, we could just emphasize
technology, but not bringing up the other two would be a disservice.
While resources refer to time, people and finances, culture speaks of
organizational attitudes and behaviour. Those involved in facility and
energy management need to be empowered to follow proactive
methodologies, engaging daily with the building analytics platform,
reviewing system performance reports to plan preventative maintenance,
and taking action from fault-detection and diagnostics insights to
prevent full-blown equipment failures or wasted energy resources.
Sinclair: How does CopperTree help organizations be successful in their quest to be more “analytic-driven”?
Moromisato: At CopperTree, our commitment as a
trusted source of expertise in building analytics and energy management
is foundational. From there, our solid team of experts in our customer
success and application engineering groups, are always ready to share
their years of experience in the industry by providing valuable
technical and business insights. Moreover, given the proliferation of
cloud applications and the myriad of solutions available today, the
need to educate, clarify concepts and provide evaluation criteria is
ever more important. To this end, we developed a fundamental series on
building analytics to help bring clarity to our space while answering
essential questions such as, What is Fault Detection and Diagnostics?
and What is an Energy Information System? A couple of practical
articles present a framework on How to evaluate the different Automated
Fault Detection and Diagnostics technologies, and How to evaluate the
different Energy Information Systems. A new application series
currently in development will tackle further building analytics
concepts while offering practical how-to advice. Be sure to check out
our CopperTree Insights for more resources.
Sinclair: Besides CopperTree’s commitment to being a trusted source of expertise, are there other ways you seek to empower success?
Moromisato: Absolutely. We also endeavour to be
relevant and innovative. To stay relevant, not only in terms of
technological advancement – which is a must for us – but also in terms
of being current with the times and circumstances. For instance, the
current pandemic and unprecedented measures have undoubtedly affected
all of us in one way or another, regardless of where we are in the
world. Recognizing that COVID-19 brings a new set of challenges on how
we interact with the built environment, CopperTree has created a Health
Compliance Analytics package to help our clients ensure their buildings
are being brought back online – after extended vacancy periods – safely
Innovation is one of our core values. However, unless we are continually improving our products and services, adding value to our clients, we can’t say we are being innovative. Recognizing that the process of innovation requires multi-disciplinary expertise, CopperTree has engaged in multi-year partnerships with leading research institutions. One such collaboration is with Carleton University’s Building Research Centre working on multiple initiatives focused on data-driven methodologies for Fault Detection and Diagnostics (FDD) as well as predictive modelling using an array of Machine Learning (ML) algorithms. And with the Building Technology and Urban Systems Division at the Lawrence Berkeley National Laboratory in California, our focus has been on Automated System Optimization (ASO). Eventually, these efforts would lead to new functionality that enhances our analytics offering and directly benefits our end users.
Sinclair: You speak of predictive modelling, machine learning and automated system optimization – terms that have been trending upwards for quite some time now. What is their relevance in our world of facility and energy management?
Moromisato: In reality, none of these topics are new. They have all been around for quite some time. What is different today is perhaps the advancement of cloud computing and how this is facilitating access to data and applications like never before. We do recognize there is a level of confusion out there in terms of what all this means to facility and energy management. For this reason, as part of the fundamental series, we have added a couple of articles to help shed some light in this area: Artificial Intelligence, Machine Learning, Predictive Analytics, Deep Learning… What’s the Difference?, and How can Predictive Analytics Help Save Energy and Improve Occupant Comfort? As for Automated System Optimization, CopperTree will be presenting this very topic at the 2020 Building Commissioning Association Virtual Annual Conference.
About the Author
Ricardo Moromisato is an engineering technologist with over 25 years of experience in building controls and energy management. After several years immersed in Building Automation Systems with a leading controls integrator, he joined a small team focusing on building data acquisition and energy analytics – a path that led to the formation of CopperTree Analytics.
As a Business Intelligence Analyst, Ricardo has a unique role working alongside business development, product management and application engineering teams engaged in innovative solutions for performance analytics, energy monitoring and fault detection and diagnostics in one comprehensive platform. Presently, he is excited about the strategic partnerships with research institutions applying Predictive Modelling, Machine Learning, and Automated System Optimization.
A member of ASTTBC and the Association
of Energy Engineers, Ricardo received his training in Electronics
Engineering Technology – specializing in Process Automation and
Instrumentation – at the British Columbia Institute of Technology in
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