7 Benefits of a Smart Building Monitoring System
An automatic sprinkler system is an excellent example of a basic building monitoring system in...
The benefits Internet of Things (IoT) technology offers to built environments are immense. Some of these—like reduced energy consumption, better environmental conditions, and higher lease rates—are well-known. But one of the most important benefits of IoT is less frequently discussed: predictive maintenance.
In a smart building, predictive building maintenance significantly reduces the cost of managing real estate assets and improves the tenant experience. A 2017 study found that predictive maintenance reduced downtime by 35 percent, unplanned outages by 70 percent, and costs by 25 percent. This innovative data-driven approach transforms the upkeep of buildings and blurs the lines between the physical and digital worlds.
In a smart building, predictive maintenance prevents malfunctions and keeps small issues from becoming big problems. This relies on data.
Unifying building systems and adding analytics to your building automation system (BAS) is a powerful way to get the data you need and use it in the best way possible. Sensor and equipment data is continuously relayed to the analytics software, which then uses machine learning algorithms to determine what that data means. As the analytics software learns how your building functions, it makes more accurate predictions about the implications of real-time information based on its knowledge of historical data. Those forecasts are what drive predictive maintenance; you no longer react to problems after they happen, you prevent them from happening in the first place.
Facility managers and building owners often use service level agreements (SLAs) to ensure vendors do what they say they will. But the SLA is only as good as the system maintenance a vendor uses. In a smart building, a predictive maintenance approach benefits building owners, facility managers, and the service providers themselves.
The smart technologies that drive predictive maintenance fundamentally transform the relationship between stakeholders by offering greater transparency, accountability, and a better way to achieve goals.
Until recently, smart buildings and predictive maintenance were only considered cost-effective in bigger structures or those that require stringent monitoring for health or safety reasons, such as hospitals or pharmaceutical manufacturing plants. But as technology advances, the price of smart systems continues to fall. Today, low-cost IoT sensors make smart buildings more attainable than ever before.
In addition to the impact on maintenance, growing environmental concerns, new tenant needs, and changing economic conditions make smart technologies a wise choice. But the vast array of sensor options can make choosing the components of a smart building system overwhelming. It is essential to know what to look for to make the best decisions.
IoT sensors should:
Some of the most exciting types of sensing networks use what’s referred to as virtual sensors. These use a “digital twin” of a building to mirror the structure and offer an interface between digital and physical realms. Virtual sensors have a number of advantages over physical sensors:
Eventually, most smart sensing equipment will have virtual capabilities, improving forecasting and reducing the cost of maintenance even further.
Predictive maintenance requires a centralized strategy and a flexible architecture that enables all building systems to work together. But there is no one way to create a smart building.
Your contractor must make building systems, IoT sensors, and analytics software operate in harmony in a way that makes sense for your property and your tenants. A contractor with deep domain expertise who specializes in open communication protocols will ensure that all system components are selected based on your needs and that you are never limited to a single vendor. With this approach, you realize the full benefits of a data-driven, future-focused solution and can implement an effective predictive maintenance approach.
Laura draws on her experience in commercial real estate to cover trends in occupancy, indoor air quality and operational efficiency.