Sustainable buildings need to be smarter buildings
Sustainable buildings need to be smarter buildings
The value of designing and constructing more sustainable buildings is no longer in question. Every sector faces the challenge of reducing net emissions and playing a role in decarbonizing the economy.
Companies involved in managing real-estate assets, and companies with large physical footprints, increasingly measure their building emissions and seek to reduce them as a matter of policy.
Adding to this is the growing evidence that more sustainable buildings can have a higher value. Research done by the Building Research Establishment (BRE) on the value of BREEAM certified buildings have shown they can command a rental premium of up to 19.7 percent, and an increased sale value of up to 14.7 percent relative to non-certified buildings in the same location.
These figures closely match work done by the U.S. Green Building Council (USGBC) in California, which calculated a net additional value of an office warehouse following a substantial "green" makeover to be 20.7 percent, with a 16-month return on the investment made.
So this is a good start. But even these examples are just a crude beginning to how the way we think about buildings is changing, and must continue to change.
In most cases today, even the greenest, most sustainable buildings are still effectively "dumb" infrastructure. Internal systems are stand-alone, siloed. Data is not captured, integrated, persisted and used dynamically with real intelligence.
Where systems claim intelligence, they are invariably hard-wired and rules-based. For too many, "autonomy" simply means remote controlled or programmable.
The world of IoT (the Internet of Things) is already colliding with the world of sustainable infrastructure, but even here those three letters don't necessarily represent magic fairy-dust. Point solutions operating in siloes are still the norm, with many IoT solution providers adopting a simplistic device to gateway to cloud model that is not always optimum.
In many ways a commercial building represents a microcosm of a city, with similar challenges around disparate systems and data. A suitably large commercial building is a system-of-systems. Heating, cooling, ventilation, lighting, security, fire systems, elevators, room booking systems, access control — generally, there is very little interaction between these systems despite their impact on each other's operations.
They don't share data. They don't share infrastructure. Worse, very few of these systems take any meaningful account of the factor that most impacts on their efficiency — people.
Seeing in systems
The first mistake many developers and operators make is to approach each operational requirement as a standalone problem requiring a standalone technology solution. Each is considered, specified and procured separately.
Such point solutions may look superficially attractive and even cost-effective on their own. In fact, once you start to combine two or more point solutions, the combined costs quickly start to exceed the cost of an integrated, platform-based approach.
At the same time, the problems of disparate data and uncoordinated systems get worse. There are ways to partially integrate systems and data post-hoc, but they are suboptimal and add cost and complexity.
With my Living PlanIT hat on, for example, we approach the problem from a different direction to most. We start with the concept of a software driven, shared network, shared infrastructure, shared data space, shared sensor platform operating on a very stripped down and efficient set of infrastructure.
While this represents the ideal, when retrofitting into existing buildings and infrastructure we adapt to the systems in place and integrate them, improving interoperability and data sharing. This is done through the use of an open, scalable platform approach to smart infrastructure — an open architecture solution, scalable over time to include additional smart infrastructure functionality sharing a common infrastructure.
Such an infrastructure platform should not lock a developer/operator into proprietary standards, but should be built and run on open industry standards and allow infrastructure developers and operators to integrate multiple services and infrastructure data into a shared repository of accessible data.
This is my first key point: Smart buildings avoid silos and embrace integrated data and systems by design, not post-hoc.
Another key challenge is the proliferation of entirely cloud-based solutions.
The amount of data already available from urban infrastructure, if only people were capturing and using it effectively, is large and growing. Simply streaming data to the cloud for analysis doesn't scale and is suboptimal for a number of reasons:
- Bandwidth. The sheer amount of data is growing. Raw, real-time, time series data requires a lot of bandwidth and this issue is getting worse and not better. Streaming raw data to the Cloud simply won't scale up to city-level projects. Intelligence at the edge of the network, analysing data close to where it is gathered and streaming the results, the meta-data, saves significant bandwidth.
- Speed. You cannot achieve the speeds necessary for real-time data processing and control via the cloud. While this may not matter for many functions, it is becoming increasingly important as key control functionality for industrial and urban infrastructure moves into the world of IoT. Time lags in data transfer and processing leads to this being inevitably historic in nature, rather than obtaining the significant benefits of being able to react in near-real-time. Edge analytics and control is only way to achieve genuinely real-time functionality.
- Resilience. Smart infrastructure is increasingly connected, and this brings resilience challenges if intelligence is exclusively hosted in the cloud. If a building loses access to key analytics and control functions when it loses connectivity, even temporarily, it isn't truly smart. Buildings should be connected and autonomous, with the intelligence necessary for day to day control activities embedded within infrastructure at the edge of the network. This allows autonomy in operations regardless of connectivity.
- Security. No system is infallible. There are many ways to enhance the underlying security of data held within any IT system, but the more data is moved or duplicated unnecessarily the more vulnerable it becomes. For example raw camera data inevitably contains personal information such as people's faces. Performing video analytics at the edge of the network, even in-camera, allows the relevant meta-data or insights (such as anonymous people counting and flow analysis) to be streamed to cloud instead. This is inherently more secure.
Distributed intelligence, embedded in infrastructure and managing data as close to the edge of the network as is appropriate for that function, is the only way to manage truly smart and resilient infrastructure at scale. Data can be aggregated in the cloud, where higher level analytics can be run with access to wider data context, but real-time control should be distributed.
Smarter buildings are more sustainable in a number of ways. By understanding how the people within a building move through and use the space, building systems can learn to not just react, but anticipate.
By connecting, integrating and sharing the data from cameras and PIR sensors for example, and persisting it, heating and cooling systems can predict when rooms will be in use and when they may be crowded. This allows the system to smooth out the heating or ventilation requirements and reduce costs.
As the use of a building changes, like when a tenant company moves out of the top two floors and a new company with different working practices moves in, no one needs to reprogram the building systems. They will learn automatically.
Because the HVAC systems have access to camera and PIR data, they can learn the new work patterns that might require a different heating pattern to optimize efficiency, and change accordingly. The elevator system that previously optimized the pre-positioning of elevators at particular times of the day to maximize efficiency can now learn that the use of the top two floors have changed, and so the elevator system reacts autonomously.
The building becomes a self-optimizing system. And a truly smart building does not expect the people who use it to adapt to the building, but the building to adapt to the people.
So we return to the value proposition for smart, sustainable buildings. There are essentially three drivers for improving the way we design, build and run infrastructure: economic; sustainability; and social.
Smart buildings have lower net operating costs. Heating and lighting are more efficient and improve with time as the building adapts. Internal workflows are easier to optimize through better understanding of flows and systems.
Already we are seeing forward thinking utility companies thinking about customized tariffs based on the fine-grained data available for such buildings, and insurance companies considering the impact of better data on how they calculate, and price, insurance risk.
Smart buildings are more sustainable as they take into account multiple variables such as the people within and the weather without. Instead of a static approach to sustainability based on design, as is often the case today, they can enable a dynamic approach based on performance and actual operations.
And smart buildings, done well, are nicer places to live and work. By reacting to the needs of the people within them; by increasingly measuring more holistic variables than just energy use — such as light levels, humidity and internal air quality. This makes people happier and has the potential to increase productivity.
Ultimately, smart and sustainable buildings will have a higher net value than their dumber neighbors. We need sustainable buildings. And if we want sustainable buildings, we need smart buildings.