How do Smart Buildings Save Energy?

A network of sensors, connected devices and interlinked systems allow vast amounts of data about a smart building to be collected; in turn, this presents improved insight for people running the building, meaning actionable decisions can then be made. Historically, energy and money have been wasted through thoughtless actions such as leaving all the lights on in a building when no one is present, having the heating on when it isn’t required or leaving devices switched on 24/7. A smart building is a living asset that helps prevent these simplistic energy-wasting actions and more sophisticated ones.

Sensors can detect that no one is present, and it is outside of working hours; therefore, they can turn off all unnecessary devices and services, which, as a standalone action, can save a vast amount of energy. However, incorporating IoT where everything has an internet connection allows assets to communicate with external sensors and systems, e.g., the heating and HVAC system can react to changing weather conditions ensuring the temperature is always right for building occupants, but that energy wastage is kept to a minimum. Smart windows can automatically open when the temperature reaches a certain level, improving ventilation and reducing the amount of time HVAC is needed. Smart blackout blinds can also be used in areas that attract a lot of sun, again helping to keep the building cool without just relying on HVAC. Daylight sensors can also be used to dim down the artificial lighting in areas where there is a lot of natural light, reacting dynamically and further saving energy. All of these actions remove the human decision-making process, making actionable, efficient decisions that benefit the health of the building, environment and the occupants. Of course, occupants can also interact and control these elements, but it is designed so that they don’t have to even think about them; it provides the optimal environment to allow them to excel in tasks.

More sophisticated actions can also be completed based on the storage of data, patterns, and preferences. Artificial Intelligence (AI) and Machine Learning (ML) are increasingly being used to understand behaviour and optimised the environment. E.g., on average, the preferences of one area of the office might be that they prefer the temperature to be warmer, but the other side prefer a cooler working environment, the building system can learn this and adapt to it, adjusting the temperate in different spaces to suit occupants but reducing overall energy wastage by only activating when the temperature hits a certain threshold.

A user-friendly dashboard that presents this data for Facility Managers allows them to understand the health of their building and identify issues ahead of time. E.g., it may show that there has been a power surge and identify the device that caused this; the Facility Manager can then go and investigate further. This may show that a component within the air conditioning unit is faulty and needs replacing; preventative maintenance can take place quickly and efficiently, which avoids waiting until it breaks and employees plugging in high energy fans until it is fixed. However, the main benefits of preventative maintenance are productivity rates, occupant happiness and cost savings - downtime, outages or things not working is avoided.

Autonomous buildings are the goal for many people and businesses; some bigger companies have achieved this, and it is possible, but issues around interoperability, lack of education and disparate systems are hindering the mass adoption of smart buildings. Buildings that automatically react and operate independently without the need for human intervention can save vast amounts of energy through the more sophisticated data analysis discussed above, but even a simplistic intelligent building can begin to save energy, having sensors installed that track occupancy, temperature, light level, air quality etc. are easy to install in both new builds and retrofits and contribute to the need for net-zero carbon buildings. For example, a sensor that turns the lights off when no one is present is a very simplistic first step to achieving some energy savings by utilising smart technology.

Cities cover 3% of the earth's land surface, yet they are responsible for more than 70% of all carbon emissions (World Economic Forum 2021). The government's new target will see the UK aim to cut CO2 emissions by 68% by 2030 (City AM 2020). Therefore, small collective efforts can go a long way.