Built Environment

Social issues such as labor shortages are becoming more apparent, making it urgent to utilize digital technology to transform workflows and work styles. In particular, there has been increasing demand for spatial digitalization to manage buildings and streamline renovation processes across various fields. When digitalizing buildings, offices, factories, and other spaces, it is necessary to measure dimensions and create floor plans, which often involves manual work. However, measuring all dimensions and generating floor plans or 3D models manually takes a significant amount of time. Moreover, overlooked measurements often require additional site visits, further delaying the process. Recently, spatial digitalization using sensors such as cameras has been introduced to address these challenges. By sensing spaces and generating point clouds, which are then converted into 3D models, efficiency can be improved. However, existing methods still present issues. Creating point clouds with desktop devices is costly and time-consuming. When using general mobile devices, the accuracy is low and results depend heavily on the operator. Furthermore, transforming point clouds into 3D models often requires extensive manual work and considerable time. This method addresses these challenges. Using low-cost mobile devices, anyone can quickly and accurately acquire point clouds, which can then be automatically transformed into 3D models within just a few hours.

Concrete production is a major contributor to carbon emissions due to its high cement content and intensive resource use. In Singapore, the challenge is amplified by reliance on imported materials and increasing pressure to meet Green Mark and national decarbonisation targets, while maintaining cost and performance requirements. Biochar Concrete integrates biochar, a carbon-negative material derived from biomass into conventional concrete mixes. Biochar permanently sequesters carbon and enhances the concrete’s microstructure, while remaining compatible with existing batching and construction processes. By reducing embodied carbon and reliance on high-carbon cement, Biochar Concrete enables more resource-efficient and sustainable construction without compromising durability or performance. This scalable solution supports Singapore’s Green Building goals and advances the transition towards a low-carbon built environment. The technology is suitable for collaboration with concrete producers, precast manufacturers, construction and engineering firms, property developers, research institutions, biomass suppliers, and government for R&D collaboration, licensing, IP acquisition and test-bedding. 

Conventional building central cooling plants, comprising water-cooled chillers, air handling units (AHUs), cooling towers, and pumps, often suffer fouling issues caused by accumulation of suspended solids in the micron range, such as rust and corrosion scale, as well as dissolved minerals within the chilled water closed loop system. Over time, these impurities clog strainers and nozzles, foul heat exchangers, and impair heat transfer efficiency, resulting in turbid water and reduced cooling performance. In condenser water open loop systems, untreated or ineffectively treated water further cause abrasion and leakage in condenser copper tubes, leading to system downtime and costly maintenance. To address these challenges, this invention introduces an effective and energy-efficient cleaning and filtration system that continuously filters blackish and rusty chilled water, returning cleaner and clearer water to the chilled water closed loop system. By leveraging existing water pressure without requiring an external pump or additional electricity, the system restores water clarity and operational efficiency, leading to: Reduced cooling energy consumption Enhanced occupant comfort and wellbeing Significant reduction in water usage for system cleaning Lower operational costs, carbon footprint, and emissions Alignment with the “Go 25°C” National Movement led by the Singapore Green Building Council (SGBC) The technology owner seeks collaboration with building owners, facility managers, main contractors, chiller and cooling tower manufacturers and suppliers, and energy service companies (ESCOs) to explore integration in new developments and retrofit applications.

Buildings and photovoltaic (PV) systems face two major challenges: excessive heat gain and frequent surface soiling. In tropical climates, solar heat through glass façades can account for up to 40% of total cooling demand, while dust accumulation on PV panels can lower efficiency by 5–30% within months. These issues increase energy use, maintenance frequency, and operational costs. This technology introduces a multifunctional multilayer coating that integrates self-cleaning, infrared (IR) heat rejection, and high optical transparency in a single, durable formulation. Unlike conventional coatings that require multiple layers for different functions, this innovation achieves comparable or superior performance in an integrated multilayer design—simplifying application and lowering cost. The photocatalytic self-cleaning surface decomposes organic contaminants and enables natural washing by rain, reducing cleaning needs. Simultaneously, the IR-reflective layer rejects near-infrared heat while maintaining over ~80% visible light transmittance, cutting cooling energy use by ~10–15% without compromising daylight. Compact, scalable, and retrofit-friendly, this coating offers a cost-effective solution for building operators and solar installers aiming to enhance energy efficiency, reduce maintenance, and improve sustainability performance. The technology owner is seeking industry partners in solar panel manufacturing, green building projects, and glass applications for licensing

The Integrated Smart Infrastructure Management Platform is an AI-powered software solution that functions as the digital command center for smart buildings and large-scale facilities. It connects and manages diverse IoT devices and subsystems, including HVAC, lighting, security, and energy, within a unified digital environment. Through real-time data integration, AI-driven predictive analytics, and cross-system automation, the platform enables seamless monitoring and intelligent control of infrastructure operations. It addresses key challenges such as data silos, delayed responses, high energy consumption, and inefficient maintenance, helping organizations enhance operational resilience and sustainability. Designed for complex operational environments such as campuses, data centers, hospitals, and industrial parks, the platform transforms fragmented systems into a cohesive, adaptive, and energy-efficient ecosystem that empowers facility managers to make faster, data-driven decisions. Ideal collaboration partners include property developers, public infrastructure operators, system integrators, and smart building solution providers who are seeking to localize or enhance their digital operations capabilities. 

This technology leveraged multiple advanced components to deliver an immersive, data-driven BI (Business Intelligence) dashboard for smart building management. 3D visualization and integration formed the dashboard’s intuitive interface, utilizing a photorealistic 3D-scanned building. Technologies such as laser scanning and photogrammetry were used to create the digital twin. This 3D model was then integrated with real-time IoT data using Building Information Modeling (BIM) principles, enabling visualization of sensor data directly within the digital replica of the building. An IoT sensor network and data acquisition system played a crucial role, with various sensors deployed to monitor building performance, energy usage (including non-invasive water and power monitoring), and environmental conditions. These sensors transmitted data wirelessly,  using protocols such as MQTT and LoRaWAN to an IoT platform. For data processing and storage, an edge IoT platform served as the backbone for collecting, processing, and managing large volumes of real-time sensor data. Built-in rule engines enabled data enrichment and automated alerting. Finally, immersive dashboard development frameworks were pivotal in creating interactive user experience. Web-based 3D visualization libraries rendered the building model and integrated dynamic data overlays. While BI tools such as Tableau or Power BI may have supported traditional dashboard components, custom immersive development provided a more intuitive 3D environment for navigation and data exploration.

This AI-driven platform revolutionizes how construction and infrastructure projects are managed by transforming vast, unstructured project data into actionable intelligence. Built upon a large language model (LLM) trained on domain-specific data including regulatory requirements, contract documents, project schedules, communication logs, digital drawings, and specifications, the technology provides real-time insights and foresight across project lifecycles. It detects risks, predicts cost and schedule deviations, and highlights potential regulatory non-compliance before they escalate into major issues. By integrating across existing tools and data sources such as Microsoft Teams, WhatsApp, SharePoint, and email systems, the AI engine enables project stakeholders to make informed decisions through a single intelligent interface. Ideal collaboration partners include real estate developers, construction contractors, architecture and engineering consultants, and AI software integrators seeking to augment project performance through predictive analytics and knowledge automation.

Every high-rise building construction requires the installation and maintenance of temporary support system, like falsework and scaffolds, to ensure work can be carried out effectively and safely. Due to the long project and deployment periods, these tall falsework systems might be subjected to various dynamic mechanical impacts, such as prolonged vibration from machineries and piling works overloading, which might lead in displacement and tilting of such structure which are not visible. Overtime, this affects the structural integrity of the support system, potentially result in buckling or catastrophic failure. The technology owner has developed a patented IOT-based solution for providing immediate visibility on the status of the temporary support system by measuring the load and inclination of vertical members in addition to detection uneven load distributions. This enables the solution to detect early and prevent potential overloading and deviations, which can lead to buckling and collapse. Upon detection of abnormalities, the solution transmits critical data instantly to the cloud platform, enabling the safety team to take precautions to ensure that the support frames remain secure for upcoming site work. The battery-based solution is easy to install and is designed for outdoor, rugged construction sites to ensure continuous operation.

In today’s rapidly evolving business landscape, digital transformation has become a strategic imperative for companies across industries. At the core of this transformation lies Artificial Intelligence (AI)—a technology that is increasingly recognized as a key enabler of innovation, operational efficiency, and competitive advantage. However, despite its transformative potential, AI adoption remains a challenge for many organizations. High development costs, specialized expertise requirements, and complex deployment pipelines often limit AI accessibility to large enterprises with dedicated AI engineering teams. Vision-based AI models, in particular, require extensive training, fine-tuning, and maintenance. Even after initial deployment, continuous retraining are necessary to ensure consistent performance, resulting in substantial costs and resource demands. To overcome these challenges, the technology owner has developed a suite of pre-trained, customisable, and continuously learning AI models that enable rapid deployment for automated visual inspection. Delivered through a modular AI platform, the solution empowers customers to build, customise, deploy and scale AI inspection solutions cost-effectively, without requiring deep AI expertise. The AI models can process both video footage and static images from conventional camera systems, transforming them into intelligent, AI-powered inspection tools adaptable to diverse use cases. The technology is available for R&D collaboration, licensing, and test-bedding with industry partners, including system integrators, manufacturers, and inspection service providers.