New technology and advances in AI will increase efficiency and quality of life in workspaces of the future
As organisations around the world grapple with finding the right balance between remote-work and return-to-office, the office itself is undergoing tectonic shifts with new technologies driving the design, and employee experience. According to business analytics and global market intelligenceplatformCB Insights, the office building of 2030 will draw on new tech, sensors, and advances in AI to increase efficiency while also improving occupants’ quality of life. And the building management role of the future will be much more defined by familiarity with and adoption of newer tech and business models.
Local and regional regulations for energy efficiency and Green-House-Gas (GHG) emission reductions will drive initial uptake of new energy-efficient tech, while new business models for office buildings (like virtual power plants) will accelerate adoption of this tech. Meanwhile, digitisation in energy management will spread to other aspects of the building, culminating in the creation of digital twins that can increase building operation efficiency and sustainability. A digital twin is a virtual representation of a real object or set of objects, constructed with plenty of real-world data collected from IoT sensors.
Digital Twins to create sustainable office space
The proliferation of IoT devices has allowed building managers to monitor facilities tasks on a more granular level. These devices help increase the efficiency and sustainability of buildings by decreasing waste and resources, as well as the number of workers needed for facilities management. Using these devices, building managers can increasingly rely on digital twins – models that unify these connected devices to give an accurate and holistic depiction of an object or process. Interest in the area has skyrocketed as the value of digital twins becomes more apparent to operators.
After an initial model is created, digital twins undergo simulations to provide performance feedback under various scenarios, without having to test the actual system. The insights gained from digital twins are used to improve the real object, and new data is then fed into the digital twin model. For example, a manager overseeing an office building’s HVAC (heating, ventilation, air-conditioning) system may want to know how much energy savings they’ll see by upgrading to a new heat pump. IoT sensors are already in place to monitor room conditions like temperature and humidity, as well as the energy consumption of the current HVAC system. Using IoT data and some 3D modelling, the building manager can construct a digital twin of the office building and run heat pump simulations on the digital twins to determine the potential benefits of installing heat pump tech. But it doesn’t stop there.
Occupancy data collected by an AI-assisted camera setup can also be fed into the digital twin, and more simulations can be run to optimise which rooms are heated and cooled based on how many people are in the building that day. These simulations also indicate which rooms may require more maintenance than others. Digital twins have far more inputs than a standard simulation, and can be updated in real time – leading to a positive feedback loop of real-world improvements and more accurate modelling.
The early movers
IBM and GE were early players in the digital twin space. IBM, for instance, created the IBM Digital Twin Exchange where companies can maintain and sell their own set of digital twin objects. In addition, Microsoft offers its Azure Digital Twins platform. However, these companies have largely focused their digital twin strategy on the industrial setting. The majority of commercial building-focused digital twin companies are still early-stage, but growing interest in all things virtual – including the metaverse, which could reshape how and where work takes place – may change this.
As companies digitise the office workplace, there is an opportunity to augment the digital workplace with real-world feedback from IoT sensors. This sensor data could be fed into a digital twin model that would improve real-world operations. For instance, WRLD offers digital twins for retail and office spaces where managers can optimise space and resource usage and improve company productivity. The company partnered with NETSOL Technologies after the Covid-19 outbreak in 2020 to develop a digital twin platform for hybrid workplaces. This digital twin allows remote employees to better engage with the office and its occupants. Animated Insights integrates existing building data and IoT sensors into a digital twin model called pebble. The company also connects building managers with contracts to maintain building components. It recently raised a $3M angel round from TBD Angels.
Creating 3D office models
Some companies are using advances in sensor technology to help build out the digital twin model. Kaarta has developed lidar sensors that can be used to create 3D models of indoor and outdoor spaces. These sensors map out an area in real time and can be used to quickly generate a spatial model for digital twins. Kaarta was recently granted a key patent for a method of making a 3D map of an environment using simultaneous localisation and mapping (SLAM) devices and sensors. Water usage in office buildings can be significant – large commercial buildings average 22,000 gallons per day, or more than 73x the amount for residential water usage. Apana deploys IoT sensors to continuously monitor water usage in commercial and industrial buildings, detecting where spikes in water usage occur so they can be quickly addressed.
Office in the metaverse
Interest in the metaverse, along with falling costs of sensor tech and increasing costs of facilities management, will drive adoption of digital twins, pioneered by tech companies that already have stakes in the metaverse. Growth in the number of 5G-connected devices will further bolster digital twin adoption. Digital twins, along with the IoT sensors that make up the backbone of the model, will drastically reduce the amount of human input needed in office building facilities management.
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