Smart Buildings: Here’s How You Can Advance Your Digital Twin Maturity

Introduction

As the world becomes increasingly energy-conscious, the concept of smart buildings is gathering momentum after an underwhelming start. It is estimated that the global market for smart buildings will reach $176.9 billion by 2030. Smart buildings leverage an array of advanced technologies like digital twins and integrated systems like building automation systems to optimize energy usage, curtail carbon footprint, and enhance overall efficiency.

Read on as we dive into the significance of digital twins in the realm of smart buildings and understand the various stages of digital twin maturity.

Smart Buildings and Digital Twins – A Match Made in Heaven

Across the globe, high energy prices and the operational costs of running any business have diluted profit margins. While there is also the moral imperative to be sustainable, energy efficiency is becoming an absolute necessity. Such efficiency is only possible when businesses can know in real-time how their systems and utilities are functioning. Such real-time insight paves the way for higher efficiency and transparency at every phase of the building lifecycle, right from planning new construction, optimizing daily operations, or retrofitting existing buildings.

As carbon-neutral efforts surge in popularity, Digital Twins allow for the creation of an end-to-end virtual model of assets, processes, or services, enabling data-driven decision-making in smart buildings. By creating virtual representations of physical sensors, HVAC systems, lighting devices, thermostats, and more, Digital Twins pave the way for real-time performance intelligence and health analytics.

Built on the foundation of data, analytics, knowledge, and modeling, Digital Twins help smart building owners detect patterns, analyze problems, and give warnings in advance. Using Digital Twins in smart buildings, organizations can:

• Create an exact virtual replica of building automation systems and simulate behavior to gauge its real-life functioning.
• Track assets across their lifecycle, from initial concept design and engineering to full functionality.
• Monitor and optimize usage of building management systems to reduce environmental waste and encourage sustainability.
• Get a complete view of buildings, including how they operate, and drive efforts to continually optimize them.
• Accurately predict when and for how much time a system will be in use and plan for optimal scheduling of maintenance and/or replacement.

Propelling the Digital Twin Maturity Journey

Many businesses today are looking to implement Digital Twin technology to transform their buildings into smart buildings but don’t know where to start. The first step to the successful adoption of Digital Twins is to understand the maturity journey. Like any modern-day technology, Digital Twins pass through a maturity cycle and evolve as it moves along. From learning from behavioral data to ultimately delivering powerful predictive and autonomous capabilities, here’s looking at the 4 R’s of the Digital Twin maturity journey:

1. Representation Digital Twin: Organizations who embark on the Digital Twin journey often begin at the representation stage. Creating a 3D/VR/AR representation of any physical object virtually enables them to easily visualize complex smart building systems and plan for efficient and optimal usage of resources and assets – both pre- and during commissioning.For example, organizations can use Digital Twin technology to assess the effectiveness of their HVAC systems, optimize usage during low-occupancy periods, and save on energy and carbon emissions
2. Replication Digital Twin: Organizations in the replication stage can create a digital replica of physical objects in a virtual environment. This allows them to quickly assemble, inspect, and navigate products virtually while also enabling faster and more economical reviews of product design.For instance, they can conduct remote evaluations of workstations and take steps to improve ergonomics, lighting, and energy and reduce carbon footprint.
3. Reality Digital Twin: Organizations at the next stage of the Digital Twin journey have virtual devices that work independently. By mirroring the behavior and characteristics of their physical counterparts, these reality Digital Twins monitor, analyze, and simulate the performance of smart building components without any direct human intervention.For instance, they can analyze historical security data to identify patterns, anomalies, and potential issues and alert teams for quick remediation.
4. Relational Digital Twin: The highest level of Digital Twin maturity enables autonomy, empowering systems to self-adjust to ambient conditions. Through continuous learning, autonomous closed-loop systems can sense, comprehend, and act on real-time data and take necessary action.For example, when combined with the power of Artificial Intelligence (AI), Digital Twins can spot anomalous behavior in sensors and take action to prevent an outage or avoid equipment shutdown.

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