Leveraging Data for a Smart Building

What is a smart building? 

A smart building uses technology and real-time data to optimize operations and enable efficient and economical use of energy while creating a safe and comfortable environment for occupants. 

Smart building goals

Goals for smart buildings include:

1. Energy and money savings
2. CO2 emission reduction
3. Building maintenance improvements
4. Occupant comfort, health, and safety
5. Tenant retention
6. Increased property valuation

Smart building goal 1: energy and money savings

Buildings are among the largest consumers of energy. In fact, buildings account for more than 70% of electricity use in the United States. One of our customers shared with us that they found the estimated energy cost of running a high rise is upwards of $50 per minute.

Smart building goal 2: Reduce CO2 emissions

With all that energy consumption, buildings are also one of the largest sources of greenhouse gas emissions. Reducing carbon emissions is top of mind for many governments from the city level to the national level which is why the Paris Agreement was established in 2015 at the UN Climate Change Conference. 

International cooperation is required to reach the agreement’s overall goal to limit global warming to no more than 1.5 degrees Celsius. The first step to reach that goal is to reduce emissions by 45% in 2030 and reach net zero by 2050. 

What is net zero?

Net zero means that greenhouse gas emissions are cut to as close to zero as possible, with any remaining emissions offset by removing an equivalent amount of greenhouse gasses from the atmosphere.

Cities are under to pressure to meet net zero goals

Today, cities occupy 3% of the Earth’s land, but account for two thirds of the world’s energy demand and 70% of CO2 emissions. This large carbon footprint of cities impacts air quality which in turn impacts the health and well-being of citizens. 

The impact of cities is enormous. But so are the opportunities. 

New York City legislation with a goal to achieve net zero emissions

Cities, including the largest city in the United States, are creating their own pathways to address climate change. Local Law 97 is New York City legislation created to drive deep emission cuts from buildings. It’s the most ambitious building emissions legislation enacted by any city in the world. 

The law requires large buildings of over 25,000 square feet in the city to meet energy efficiency guidelines and limit carbon emissions starting in 2024 or pay an annual fine. The amount of the fine increases over time and can be significant. The ultimate goal is a drive toward net zero emissions by 2050.

Smart building goal 3: building maintenance improvements

Maintenance costs are a huge part of a building’s operating budget. In fact they can account for roughly the same percentage of expenditure as energy expenses. Using data to improve building maintenance might add years to the life of the building’s operational technology.

Usually building maintenance is a combination of the following 3 approaches: 

• Reactive maintenance
  • Corrective action is performed only after equipment falters or fails completely. Sometimes this can’t be avoided.
• Preventative maintenance
  • Performing regular, prescheduled maintenance checks and repairs — whether they are needed or not. 
• Predictive maintenance
  • Maintenance is based on data rather than a predetermined schedule. This is where smart building technologies can be the most helpful.

Example: air filter maintenance

To understand the difference in these types of maintenance it’s helpful to look at an example such as this one about heating ventilation and air conditioning (HVAC) filters. 

Filters are used in HVAC applications to remove airborne particles such as dust and pollen for occupant health and wellness. The airborne contaminants accumulate in the filter and can clog and even eventually block the filter. A clogged air filter can adversely affect the performance of the HVAC system and may cause damage to HVAC components. 

Let’s look at how the three types of air filter maintenance play out in practice.

• Reactive maintenance would happen after damage had occurred. 
  • For example, after the air conditioning stops working, the repair team pinpoints a frozen evaporator coil caused by a blocked air filter.   
    • Cost would include not only a new filter, but the cost of repair, plus the expense of downtime. 
• Preventive maintenance would replace the air filter on a schedule. 
  • For example every 60 days or as recommended by the manufacturer. 
    • Budget would be fixed and, ideally, reactive maintenance could be reduced, or even eliminated.
• Predictive maintenance could identify a need for maintenance due to a change in air pressure or flow rate drop.
  • In a building with low occupancy, a filter change may need to happen less frequently. Or a building exposed to a lot of airborne dust might need to have a filter changed more frequently. 
    • Ideally, reactive maintenance could be reduced or eliminated and it might save money and/or enable a healthier environment for the occupants.

Smart building goal 4: occupant comfort, health and safety

Building owners and managers want to provide the maximum amount of occupant comfort and safety for the minimum amount of cost. A smart building can incorporate occupancy, weather and historical values to control heating and air conditioning in order to maintain a comfortable temperature (often prescribed in the lease or even by law). 

Safety requirements also include air quality, fire prevention, and even elevator safety. For example, a smart building can often predict a power loss before it happens and recall elevators to the nearest floor and open doors. 

Smart building goal 5: tenant retention

A landlord that delivers on all goals 1 to 4 is sure to attract and retain the best tenants. This is important because whenever a tenant leaves a property, finding another qualified tenant costs money. 

Smart building goal 6: increased property valuation

Commercial buildings are valued based on their future income. With a growing preference for sustainable technology, a smart building could be considered more valuable. Sustainable buildings often have an easier time finding financing and have a larger market of buyers when they sell. Furthermore, since many occupants have their own carbon neutral goals, sustainable buildings might command a rental premium which can impact valuation. 

For example, LEED (Leadership in Energy and Environmental Design) is the most widely used green building rating system in the world. They provide a framework for healthy, efficient, and cost-saving green buildings. Buildings that are LEED certified can command a 21.4% higher average market sales price per square foot over non-LEED buildings. In addition, they have consistently achieved higher rents than non-LEED counterparts, averaging 11.1% higher rent than non-LEED certified buildings.

Data, the key to reaching smart building goals

The key to reaching all of a smart building’s goals is to first acquire and understand the data from a building’s operational technology (OT). Every building has control systems throughout, each generating data and most of them running independently. For example, a building’s operational systems can include:

• Electricity
• Gas
• HVAC controls
• CO2 monitoring
• Water
• Elevator and escalator controls
• Occupancy
• Steam
• Security systems
• Fire

In addition, data can be collected by any number of IoT sensors. To get a handle on all the data, many building owners are creating a data lake. 

What is a data lake? 

Imagine each OT system creating data that flows like water into a lake overseen and maintained by the building owner. That’s the concept of a data lake. It’s a centralized repository that allows all data to be stored at scale. The data can be stored on-site or in the cloud with providers like Amazon Web Services (AWS). 

Once the data is collected, dashboards and real-time analytics can paint a full picture of the building. Machine learning can be employed to guide decisions and predict outcomes for cost savings and energy efficiency.

Collecting the data 

Critical to any smart building solution is data, and critical to data collection is a gateway. A gateway is a bridge between your on-site devices and off-site compute and data storage infrastructure. 

Smart building gateway requirements include:

• Compact size with multiple mounting options to fit in a variety of locations, including equipment rooms, closets or cabinets
• Reliable operation, even when unattended for long periods
• Many industrial I/O options to connect to a variety of inputs including legacy equipment
• Ability to withstand temperature variability as many mechanical rooms are vented to the outdoors
• Multiple LAN ports to keep cloud-destined data separate from the building network

Building dashboards and analytics

After building data is collected, software goes to work to make that data powerful. Dashboards from smart building applications can combine the data from disparate operational technologies and properties to present building owners and operators with a single pane of glass for their entire portfolio. Real-time visualization facilitates anomaly detection and correlations can be made between weather, occupancy and HVAC. Automated reporting can present actionable insights to the C-suite including daily energy savings and carbon emissions. 

For example, Prescriptive Data makes smart building and decarbonization  solutions. They enable property owners and managers to visualize and control their entire portfolio of buildings from a single pane of glass. That means they can easily navigate between buildings and their data.

With Nantum OS by Prescriptive Data, building managers have access to customizable building dashboards where they can view all data from building management systems, sensors, OT, and operational KPIs. Real-time data delivery and AI-powered analysis allows them to identify anomalies immediately and react accordingly.

Machine learning and artificial intelligence in a smart building

Artificial intelligence (AI) and machine learning can take building data further by automating operational technology more strategically to use the least amount of energy for the maximum amount of indoor comfort. 

Some examples of AI and machine learning in a smart building include: 

• Occupancy and weather factored into the HVAC system to ramp up or ramp down based on the data. Having this degree of control over an HVAC system can mean energy and money savings – all while maintaining a comfortable environment for occupants. 
• CO2 levels monitored in real time and if they are in line with building guidelines, the system can automatically reduce the outside air intake. If the levels near the limit, additional outside air can be brought in. 
• Occupancy levels tracked down to floors, regions and rooms to adjust lighting and HVAC throughout the course of the day. 
• Heating demand shifted to off-peak times. Many municipalities charge a premium during peak hours. For example, during the winter in New York City, the Con Edison Steam District increases steam peak demand charges by a factor of 10. Shifting demand to off-peak times can save buildings thousands of dollars in monthly steam costs.
• Text messages, emails or any variety of notification alerts sent for data thresholds based on data type or even time and day of the week. 

Make your smart building possible

Whether you own or manage a high-rise commercial building or a small warehouse, just about any building size can benefit from smart building technology. It all starts with the data. If you’d like to learn how to get started, check out our IoT gateways and connect with our team.