Turning building data into real value

Many modern buildings contain dozens of separate digital systems — lighting, HVAC, elevators, security, and energy management. What problems does this create for building owners and operators?

Dr. Cao Yong
Chief Intelligent Control Expert
China Academy of Building Research

Today, many buildings are equipped with dozens of intelligent systems from different vendors. These systems often use different data protocols and operate independently, creating isolation and fragmentation in management.

This leads to several problems for building owners and operators. For example, when a system reports an issue, it can be difficult to identify the root cause. Administrators often have to check equipment piece by piece and review system data manually. In addition, because subsystems from different vendors use separate interfaces, maintenance and upgrades often require coordination with multiple suppliers, increasing workload and cost.

These disconnected systems also degrade the daily user experience. Occupants may need to swipe cards at multiple points, from entering the parking garage to accessing elevators and offices. At the same time, fragmentation limits more advanced functions, such as automatically adjusting lighting and temperature based on user needs.

Your organization has worked with Huawei on the development of BuildingHarmony. Why do buildings need a unified operating system, and how could it change the way building systems interact with one another?

Our goal in developing BuildingHarmony with Huawei is to create a native, open, and unified digital foundation for the construction industry, and to support its broader digital transformation.

A unified operating system (OS) for buildings offers three main benefits. First, it addresses the long-standing issue of isolated systems operating independently. This simplifies management and reduces maintenance costs. Second, a unified OS enables centralized monitoring and management of energy consumption, improving efficiency and sustainability. Third, an open and unified OS helps prevent vendor lock-in and promotes greater openness across the industry.

More broadly, the OS reshapes how building systems interact. With a unified communications protocol, equipment can exchange data seamlessly. This reduces manual workload in operations and maintenance, and enables coordinated, automated responses across systems—for example, adjusting lighting, HVAC, and security when people enter or leave a building.

System upgrades and new functions can be deployed more easily, similar to installing apps on a mobile device. Overall, this approach improves both operational efficiency and system security by reducing the risks associated with isolated systems.

What role can smart buildings play in helping cities reduce energy use and carbon emissions?

Nearly 50% of energy-related carbon emissions in China come from buildings and construction activities. Smart buildings and campuses can support emissions reduction in three main ways.

First, they enable end-to-end energy optimization. Rather than relying on isolated measures such as efficient lighting or reduced air conditioning, smart buildings are designed for sustainability from the outset. This includes optimized systems and materials during design and construction, followed by AI-driven management during operations, which can reduce energy use by more than 20%.

Second, they improve the use of clean energy. Buildings can shift from being pure energy consumers to partially self-sufficient energy units, using approaches such as load balancing and energy storage to better match supply and demand.

Third, smart buildings enable more precise management of emissions at the city level, helping policymakers avoid one-size-fits-all approaches.

Building Information Modeling (BIM) is widely used during building design and construction. How can BIM data continue to create value after a building is completed, particularly in areas such as operations, maintenance, and energy efficiency?

Many organizations use BIM primarily during design and construction, and stop using the data once a project is completed. In fact, a building information model is a core digital asset that can continue to create value for decades.

During operations, the model provides a detailed view of the building’s structure, systems, and equipment, allowing administrators to monitor performance without relying on drawings or physical inspection. This significantly improves efficiency.

During maintenance, BIM can track equipment status and maintenance cycles, and support predictive maintenance based on operational data. This reduces emergency repairs, lowers costs, and minimizes downtime.

In terms of energy efficiency, BIM can integrate and analyze building data to identify opportunities for savings. Digital twins built on BIM models can also simulate operational strategies, enabling system-level optimization.

Smart buildings rely on large amounts of data from sensors and equipment. What are the biggest challenges in turning that data into practical insights for building operators?

Smart buildings generate large volumes of data, but two main challenges limit its practical use.

The first is fragmentation. Data from different vendor systems is often hard to integrate. Even when data is aggregated on a single platform, it may remain siloed, making it difficult to analyze relationships between people, equipment, spaces, and energy use. Fragmented data cannot deliver meaningful value.

The second challenge is implementation. Many systems focus on data visualization and post-event analysis, but do not translate insights into actionable solutions. Without execution, data remains theoretical.

A project in Qingdao, China illustrates this issue. In its early stages, the site deployed a large number of sensors, but the systems operated independently. Data was displayed on dashboards, but not used to address operational challenges.

To resolve this, we integrated data from all systems using BuildingHarmony and developed applications based on real operational needs, such as energy prediction and intelligent control. This allowed the system to identify inefficiencies and automatically optimize equipment performance. As a result, the project reduced energy consumption by more than 15%.

You have worked extensively on smart energy systems and digital infrastructure for buildings and campuses. What would you say are the most important technologies or approaches shaping this field today?

The most important approach is to build a unified system that combines a strong digital foundation, enhanced core capabilities, and scenario-specific applications.

Several key technologies support this:

First, unified and open IoT operating systems. Platforms such as BuildingHarmony use common protocols and data models to connect previously isolated systems, enabling data exchange and supporting intelligent applications.

Second, digital twin technology. Across the building lifecycle, digital twins enable simulation, visualization, and optimization of energy use and system performance.

Third, integrated energy management across generation, grids, loads, and storage. This allows centralized scheduling and dynamic optimization of energy use, improving efficiency while reducing emissions and costs.

Fourth, data-driven, scenario-based applications. These create closed-loop systems in which data insights lead to decisions, automated actions, and continuous feedback, ensuring that technology delivers real operational value.

Looking ahead, what will distinguish truly intelligent buildings from the "smart buildings" we see today? What might that look like in a real building?

Today, many so-called smart buildings rely on isolated, automated systems that must still be manually activated and adjusted.

In the future, truly intelligent buildings will function as adaptive environments that can sense, respond, and evolve. Systems will proactively adjust to user needs and create value without manual intervention.

This will be enabled by a unified digital foundation that allows systems to operate together seamlessly. For example, when a meeting is scheduled, the building could automatically prepare the room—reserving it, adjusting lighting and temperature, and activating equipment.

The underlying logic will shift from fixed rules to data-driven learning. For instance, intelligent university buildings could predict weather conditions and occupancy levels, adjusting classroom environments accordingly. When spaces are unused, they can automatically enter low-power modes to reduce energy consumption.

Intelligence will no longer be defined by the number of devices or features, but by the value created over time. The focus will shift from hardware to long-term operational performance. Security will also evolve. Instead of relying on post-event responses, intelligent systems will enable real-time risk prediction and automated emergency coordination. In the event of a fire, for example, elevators, ventilation, and safety systems could respond automatically within seconds, improving safety outcomes.