Automation is not enough: Buildings need AI-powered intelligence

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Buildings have been some of the most voracious users of IoT devices. Smart buildings, in particular, use Connected devices Measuring everything from temperature, lighting, air quality, noise, vibration, occupancy levels and power consumption – just to name a few.

Building automation is getting big and expanding, with more than 6 million commercial buildings deployed in the United States alone and an estimated 2.2 billion connected devices scattered. The global market for building automation systems in 2022 will reach about $80 billion.

This type of automation depends on Fleets of IoT devices. Many conditional reflexes are automated; If a fire is detected, alarms are triggered automatically, often with voice instructions, and fire departments are notified. This was true before the Internet of Things; Now the fire alarms are connected via the internet and secondarily via cellular connection.

The value of the Internet of Things, in building automation specifically, is realized in two main areas:

  • The data generated by the internal devices and how it is analyzed and utilized.
  • Procedures and management performed by building automation systems

Rich, continuous streams of data provide valuable insights into construction processes, but there is a catch: Large fleets of devices create large amounts of data that humans alone cannot properly analyze and understand. To realize the potential revenue from deploying these sensors (and cameras), artificial intelligence (AI), and machine learning (ML) Required to continuously monitor and evaluate data flows.

Automation can’t do this job alone

Until 2020, the focus on smart building systems, including building automation, has been the responsibility of facilities management. Next, the focus shifted to employee health and ESG . InitiativesIn addition to facilities management. This demand opened up the capabilities offered by machine learning.

An AI system can monitor air quality and find correlations with occupancy limits, for example. It can also learn how to reallocate meeting rooms and cubicles, related to occupancy and ventilation, with the goal of increasing physical distance between employees and improving air quality, to reduce the chance of employee illness.

AI can also help analyze water supply usage and water temperature to warn when there is an increased risk of Legionella and other harmful pathogens. Legionella grows in certain temperatures of warm water.

The importance of new AI-enabled capabilities does not rule out traditional functions such as tracking and managing energy consumption. Through the AI-driven platform, the building can turn off unused areas and experiment with different window shading settings at different times, to reduce energy use. Experiment and learn as you go. This is a fundamental problem and it will become even more important in 2022 because of energy prices.

AI can also play a role in cleaning efficiency, determining which desks have been used and which toilets have seen increased use. In the era of COVID-19, facility managers focus on hygiene.
AI can greatly enhance systems that support physical security as well. Once the system learns what constitutes normal access and movement behavior, it can identify the anomaly and alert security. Other AI-powered applications can detect duresses, abandoned objects, identify weapons, identify shots fired — and implement emergency shutdowns.

An intelligent infectious disease control system can learn to take advantage of data on local infection rates. AI systems can do things people can’t, like stare at a wall for 20 years and look for signs of change in concrete that could herald imminent structural collapse.

Artificial intelligence application for smart buildings

The standard starting point for a new AI-driven system is of course teaching it. This process begins with a base of data that represents the facts that the system will encounter. Many will find, however, that good basic training data for smart building systems is lacking. The answer could be to generate training data by performing “experiments” in the physical building.

In energy consumption, for example, you can train a system by experimentally adjusting the window shades and the air conditioner based on the time of day and office occupancy, to lower AC bills without causing a manual override. Such a system could rely on temperature sensors and occupancy readings, as well as detecting sunlight.

There are basic best practices to follow. Be scientific and rigorous when collecting baseline fact data sets and collect data from multiple sources to increase confidence that your samples are representative.

AI-driven systems can learn from occupancy patterns in specific office areas and help reduce human error in space planning. Upgrading the space is expensive, and maintaining flexibility is vital. It is clear that space use and occupancy has become a health issue during the pandemic. Employees now may prefer meeting for conversation and coffee on an outdoor balcony or patio, rather than in a small break room.

Where artificial intelligence-based building management is headed

AI-powered systems can recommend changes to facilities management and allow building management to be more predictable. When it comes to interaction, it enables a more effective response to sudden challenges as well. recent example; Prior to 2020, identifying employees with overheating (fever) and reducing the possibility of infection was nothing, but addressing this issue is within current capabilities.

It takes careful thought and the dedication of time, to get the ground truth right. Many commercial buildings have a digital twin; A virtual replica delivered by the architect to the building owner or manager. As a starting point, the digital twin may be a test ground for AI-driven facility management and smart building management.

We anticipate that IT, facilities management, human resources, and security will become more integrated and the use of artificial intelligence will increase. There are a range of potential benefits from joining their information silos to create data flows for AI applications.

The importance of healthy workplaces, physical security, and energy conservation makes it imperative to go beyond simple automation and develop operating systems that are built on artificial intelligence and powered by strong, up-to-date data. Any of these applications supports a strong business case; Taken together, they make a compelling argument that facilities management should consider AI-driven applications to power smart buildings and make smart buildings. smartest buildings.

William Coyle de Grouchy is the founder and CEO of Information Network.

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