AI in the Built and Body Corporate Environment

Artificial Intelligence (AI) is revolutionising the way we live and work, and its impact is being felt across industries and sectors, including the built environment and strata management. This article will explore how AI is being used in the built environment, the benefits it offers, and the challenges and opportunities it presents for building owners, managers, and occupiers.

The evolution from traditional pen-and-ink designs to cutting-edge technologies like Building Information Modelling (BIM) and digital twins epitomises the dynamic shift in the design and construction sector. BIM, serving as the informational backbone, paves the way for digital twin technology, catalysed by AI, enabling real-time scrutiny and analysis of physical assets. This symbiosis empowers optimisation across design, construction, and operational phases, fostering innovation and sustainability within the built environment.

AI-powered tools now allow strata managers and lawyers to easily access base building data. This data is necessary for remediation works, warrant of fitness, and end-of-life capital works replacement. With AI-powered tools, strata managers can simply ask a chatbot to “list the model numbers and location of all submersible pumps”. As legislative building quality reform sweeps the country, the next generation strata manager will be interfacing with these AI powered tools.

A digital twin powered by AI can be created, which is an exact virtual replica of the physical asset, connected to the smart technology installed in the building, such as access control, solenoids, pumps, temperature sensors, etc. The digital twin can provide real-time monitoring and analysis of the physical asset, allowing strata managers to detect issues before complaints are received.

A scope of repair works can be generated, providing a detailed description of the repair and maintenance activities required, including the specific areas of the building or infrastructure that need attention, the materials and components that need to be repaired or replaced, and the estimated cost and timeline for the work.

AI-powered predictive maintenance systems coupled with the Internet of Things (IoT) can monitor and analyse data from various building equipment and systems to predict maintenance needs. By detecting anomalies and patterns, AI algorithms can identify potential failures or issues before they occur, enabling proactive maintenance, optimising the lifespan of equipment, and reducing downtime and complaints.

AI can process and analyse large amounts of data collected from building systems, sensors, and IoT devices. This data can provide valuable insights to building managers and owners, enabling data-driven decision-making. AI algorithms can identify trends, patterns, and opportunities for optimisation, leading to improved operational efficiency and cost savings. Residents can use this information to plan the optimum time to visit the gym or pool.

Mobile 3D LiDAR Technology is already being used by drones to inspect and map the external building. This technology is also used to inform the digital twin after construction, overlaying the as-built with as-designed. The insurance industry implemented this technology to inspect the buildings prior to offering a policy and after a claim has been lodged. SLAM (Simultaneous Localisation and Mapping) provides a handheld inspection and mapping tool available to measure and produce 2D and 3D drawings of rooms, on each floor level, including identifying and tagging any equipment. An efficient solution for strata buildings without their base building data.

As we navigate the landscape of AI in the built environment, it becomes evident that the fusion of technology with physical infrastructure holds unparalleled promise. AI not only streamlines data accessibility for strata managers and legal professionals but also elevates building management through digital twins. These virtual replicas, fortified by AI capabilities, usher in a new era of predictive maintenance, energy efficiency, and security. Proactive insights derived from AI-powered systems not only enhance decision- making for building managers but also empower residents to optimise their usage of shared amenities.

The integration of Mobile 3D LiDAR Technology, coupled with drone inspections and SLAM, further propels the built environment into a realm where digital and physical dimensions seamlessly coalesce. The insurance industry’s embrace of these innovations for pre-policy inspections and post-claim evaluations illustrates the pragmatic applications of AI in risk assessment and management.

In essence, as AI continues to weave itself into the fabric of the built environment, the potential for innovation and efficiency amplifies. Challenges undoubtedly exist, but with a concerted effort towards responsible implementation and continual adaptation, the built environment stands poised for a future where intelligence augments infrastructure, and where data-driven decisions steer us toward sustainable and resilient urban landscapes.

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