Making smart buildings even smarter with Artificial Intelligence

May 9, 2019

Building technology is the largest consumer of energy after transport and power generation. Heating, cooling and lighting in residential and office buildings make up about 40 percent of the energy consumed in a building. Smart buildings are key in a world where ongoing urbanization will force building owners to strive for more efficiency and sustainability. Artificial Intelligence (AI) has the potential to enhance commercial building automation by sensing and analyzing information about where and how people use the space, while maintaining highest standards for privacy and data security. Intelligent Building Control systems to residential and non-residential buildings, can create energy savings of up to 50 percent.

Artificial Intelligence puts the ‘smart’ in smart buildings

Artificial intelligence (AI) is poised to fundamentally change the way we use technology to solve challenging problems. From the potential of self-driving cars to virtual assistants like Apple’s Siri or Amazon’s Alexa, we are already starting to see a glimpse of what the future holds. While it is still early on for many consumer AI applications, AI is being deployed for a range of business applications that have the potential to be big revenue generators and money savers.

IoT by increasing the intelligence of sensor solutions used in:

  • Heating, ventilation and air conditioning (HVAC)
  • Gas and water supply systems
  • Temperature sensors
  • Humidity sensors
  • Air quality sensors
  • Vibration sensors
  • Early problem detection
  • Variable air volume systems

AI continues to infiltrate the market, below are ways in which it can be used to make buildings smarter.

1. Predictive Energy Optimization
When it comes to reducing energy consumption, buildings are reliant on after-the-fact reporting, essentially analyzing what energy was used and then implementing a change in the hope that less energy will be used next time. AI and predictive analytics are disrupting this in favor of a moe proactive approach.

Controlling room temperature within a building is like controlling speed when riding a bicycle. Many forces change the speed of a bicycle when it is in motion.

In the case of a heating and cooling (HVAC) system, there are numerous thermal loads that influence the temperature of a space. To cool a room, the system blows cold air into the space to decrease the temperature.

However, other thermal loads such as human activity, solar radiation, and heat from electronics increase room temperature. When these loads add up to zero, the room temperature is fixed.

AI-based energy management platforms can identify the “uphills” and “downhills” for building operations by applying AI in the form of machine learning to advanced models of a building’s thermal characteristics.

It will identify when it makes sense to precool the building to avoid energy use during hours when energy is at the highest price (the uphill), or when to decrease cooling due to periods of inactivity within a building based on historical usage patterns (the downhill).

2. Preventative Maintenance and Fault Detection
In addition to optimizing day-to-day operations, AI and machine learning can be relied upon for fault detection. AI techniques are well-suited in learning the relationship between input and output variables using only data, without mathematical models. This technology can excel at analyzing data from various systems and IoT devices within a building to identify anomalies and inconsistencies. After identifying these symptoms, AI can be used to target a diagnosis.

In an ideal world, data anomalies would be automatically detected by AI-algorithms, and then immediately triaged and to identify the root cause. However, within a building there is a deeper issue of resource constraint. There are often a lot more subtle and qualitative aspects to detection issues that require a person to filter.

3. Improving Tenant Comfort
Using AI to optimize building operations and prevent faults will inherently create a more comfortable environment for tenants. Exploring the relationship between comfort, direct tenant feedback, and AI is perhaps one of the more recent developments in smart buildings.  Companies are actively racing to find the best ways to personalize comfort for individuals within a shared workplace. While there is no clear-cut path to how this will develop in the future, it is certain that humans act as the ultimate sensor within a building.

Thus, integration of mobile apps – and perhaps wearables – will likely have a large role in the way tenants interact with buildings.

The future of AI in buildings is bright but human expertise will always be needed to properly utilize and direct the technology.

The building space has been traditionally slow to adopt new technologies but embracing AI-based solutions is inevitable as it capitalizes on the boom in the adoption of IoT-driven devices within facilities.

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