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Traditionally, the construction industry has managed information flow through documents and drawings from the design phase to building maintenance, but this information has often been fragmented and not centrally organized. With the rise of digital technology, Building Information Modelling (BIM) has become more widely used, enabling comprehensive management of building lifecycles. However, generation of Digital Twins remains a complex task. The process requires expensive 3D scanning equipment, specialized software, and skilled personnel to process the data. Many companies struggle to fully utilize advanced 3D technologies like BIM and Digital Twins due to these barriers. The technology owner has developed an AI powered 3D spatial platform solution that simplifies the creation of Digital Twins and integrates AI technologies to enhance on-site operations. Through the integration of proprietary AI algorithms, it enables the smart generation of the Digital Twins from either their proprietary or third-party scanning solutions and unlocks various AI capabilities utilising the 3D model that even less experienced team members are able to fully leverage on, driving operational efficiency. With the "Conversational AI" capability, it enables the documentation of drawings and reports within the 3D spatial model for easy referencing to facilitate problem-solving through dialogue. The "Asset Detection AI" and “Anomaly Detection AI” capabilities not only automatically detect and map fixed assets onto the Digital Twin and provide an automated ledger generation from it, but also have the function to identify issues (such as cracks or rust) and pinpoint them accurately within the model for prompt action. This solution employs its proprietary imaging devices or compatible third-party scanning solutions for point cloud data acquisition, which is then processed through proprietary AI technology within the digital platform solution to generate the Digital Twin, simplifying the construction process. The key features include: Automated alignment of point clouds (creating a unified point cloud dataset) Automatic overlay of spherical images onto the mesh generated from the unified point cloud Segmentation and categorization of objects using point cloud recognition Automatic generation of BIM data from recognized point clouds 3D viewer accessible via web browser for easy visualization Once the 3D spatial model is generated within the 3D viewer platform, the below AI-powered features can be utilised, with further expansions expected in the future: Conversational AI capabilities using internal document data (leveraging Retrieval-Augmented Generation (RAG)) Visual anomaly detection for rust, cracks, smoke, water leaks, and other infrastructure issues Automated ledger generation for detected assets On-demand automatic masking to protect privacy (e.g., sensitive labels, personnel) Simulation and interference checking for object relocation within the Digital Twin Conversational AI Functionality The multimodal AI, which integrates 3D, imagery, and natural language, extends beyond simple question-answering to more advanced applications. For instance, it can reduce the time spent on document creation by automating report template generation. Furthermore, by recognizing images and point clouds and providing related information (such as hazardous areas), the AI can assist in identifying potential issues that might otherwise go unnoticed through conversational prompts. Anomaly Detection AI Functionality For rust detection, the AI can assess the severity of anomalies using characteristics like color, texture, and shape. For crack detection, the AI can evaluate the length, width, and depth of continuous cracks through advanced image recognition and depth estimation, providing accurate severity assessments. By integrating these detection capabilities with the Digital Twin, anomalies can be managed and tracked over time. Moreover, the Conversational AI feature can notify relevant stakeholders when an anomaly reaches a critical level, allowing for proactive management. The AI can also automatically generate reports summarizing detected anomalies, streamlining any maintenance reporting process. The company is seeking collaborative partners like facilities and infrastructure owners who wish to further develop or empower business operations with AI capabilities to optimize their maintenance workflow and operational capabilities. The technology solution easily generates 3D spatial via its own or third-party scanning solutions and is easily accessible via a web platform. With the integration of various state-of-the-art AI software algorithms, it enables interaction of the 3D space, thereby unlocking its full functionalities to non-expertise personnel for other business optimisation. Its proprietary anomaly detection AI empowers enterprises to accurately track and prioritise abnormalities on their equipment, enhancing maintenance operations and reducing unexpected downtime. 3D Spatial Platform, Rust Inspection, Crack Inspection, Anomaly Detection, Facilities Management Infocomm, Artificial Intelligence, Green Building, Sensor, Network, Building Control & Optimisation, Smart Cities

The increasing complexity of plant and factory operations, coupled with growing demands for energy and carbon management, has created an urgent need for integrated solutions. These solutions must not only manage assets and optimize production processes but also measure and reduce carbon emissions, driven by mounting government pressure to achieve smart and green manufacturing with low carbon output. This technology is tailored for manufacturing plants and energy-intensive industries such as oil and gas, petrochemicals, chemicals, and pharmaceuticals - sectors facing significant challenges to lower operational costs, boost production efficiency, and meet carbon neutrality goals. By leveraging 3D visualization, operational simulation, real-time data collection, and big data analytics, this technology reconstructs the entire production and operational processes through a digital twin. It integrates and replicates data from system upgrades, engineering construction, production activities, and process principles. The implementation includes the digital delivery of engineering assets, the creation of a digital twin model based on operational mechanics and historical data, and the seamless integration of operational management with energy and carbon management systems through real-time data access. This technology ultimately establishes a cloud-based digital twin platform that enables comprehensive asset management, production workflow optimization, and precise monitoring of energy consumption and carbon emissions, paving the way for developing low-carbon, smart plants. The technology owner is seeking collaboration with industrial manufacturers, plant operators, energy management companies, engineering design firms, IoT sensor and software providers to co-develop and implement this technology in practical applications, delivering tailored solutions to meet the unique needs of diverse clients. Core Technology: Builds on a comprehensive digital twin platform Integrates cutting-edge 3D visualization tools Features simulation engines for operational mechanism Utilises big data analytics Real-time data acquisition systems Key Components: 3D visualization engine Digital delivery system Digital operations and maintenance system Process simulation and optimization system Energy and carbon management system Primary Functions: Digital reconstruction of factory production and operational workflows Enable precise monitoring, predictive maintenance, and optimized energy and carbon management Target Industries: Oil & gas, petrochemicals, chemicals, steel, pharmaceuticals, and other energy-intensive sectors Export-driven industries requiring carbon emission reporting Transformative Solutions: Engineering digital delivery Factory digital operations and maintenance Real-time production process optimization Energy and carbon management platforms Real-time carbon accounting systems Key Applications: Digital Delivery and Asset Management: End-to-end digital delivery, preservation, and management of factory assets Production Optimization: Enhance production efficiency, streamline processes, and reduce operational costs Predictive Maintenance: Anticipate equipment failures, minimize downtime, and extend machinery lifespan Energy and Carbon Management: Reduce energy consumption and track carbon emissions with real-time data analytics This technology offers significant advancements over existing solutions through its BS architecture, which eliminates the need for software installation, enhancing both accessibility and user-friendliness. The platform supports multiple business models and software formats, enabling real-time data integration and carbon accounting in compliance with international standards.  BS architecture that requires no software installation Compatible with multiple business models and software formats Real-time data integration and carbon accounting capabilities Open software environment with rapid response capabilities Digital Twin, Low-carbon, Smart Factory, 3D Visualization, Operational Simulation, Big Data Analytics, Asset Management, Production Optimization, Energy Management Infocomm, Artificial Intelligence, Energy, Sensor, Network, Power Conversion, Power Quality & Energy Management, Manufacturing, Chemical Processes

The technology redefines equipment monitoring and maintenance with its novel approach and sets itself apart from conventional solutions. Unlike traditional predictive maintenance methods that rely on pre-installed expensive sensors, this solution leverages a robust analysis of existing data, integrating AI and machine learning, to provide accurate health assessments and predictions. Conventional systems often struggle with managing and classifying large volumes of alarm data, leading to delayed response and overlooked issues. In contrast, this system excels in managing large volumes of alarm data, classifying faults and critical alerts, and monitoring emerging trends to address potential issues. The technology also has the capacity to automate the identification of Standard Operating Procedures (SOPs) and to utilize sophisticated AI agents to orchestrate real-time, factory-wide monitoring. This approach addresses several key pain points in the equipment maintenance industry and helps in achieving higher equipment uptimes (Overall Equipment Efficiency, OEE). By focusing on data-driven insights rather than additional sensors, this technology also offers a more cost-effective and flexible approach to equipment health management, ensuring comprehensive and proactive maintenance strategies. Unsupervised Machine Learning: The solution excels at identifying patterns and anomalies without pre-labeled data, enabling it to analyze and generate insights even without extensive historical data, making it highly adaptable to new situations. Data Integration: The platform can seamlessly integrate with any data set, independent of OEM support, ensuring comprehensive monitoring and analysis without requiring prior data preparation or understanding. Health Index for Equipment: The solution offers a detailed health index for machinery, providing clear and actionable assessments that inform maintenance decisions and optimize operational efficiency. Predictive Maintenance Capability: Equipped with predictive maintenance functionalities, the solution analyzes data trends to forecast potential issues, helping to prevent equipment failures, reduce downtime, and enhance productivity. Integrated MLops Platform: The solution includes an MLops framework that manages and monitors machine learning models, ensuring efficient operation, continuous improvement, and scalability of its machine learning components. Semiconductor and Advanced Manufacturing: This solution is ideal for the semiconductor industry and other advanced manufacturing sectors, where precision and reliability are critical. Its advanced monitoring and predictive capabilities ensure equipment operates within optimal parameters, minimizing defects and inefficiencies. By processing large volumes of data in real-time, the system enhances quality control, reduces waste, and improves production yields. Predictive Maintenance: The solution revolutionizes predictive maintenance across industries by using data analysis and machine learning to anticipate equipment failures before they occur. This proactive approach enables timely interventions, reducing unexpected breakdowns and extending machinery lifespan. By forecasting issues based on real-time and historical data, the system helps avoid costly downtime and maintains continuous production. N+1 Standby Reduction: In N+1 manufacturing environments, the solution optimizes energy consumption by minimizing the need for standby equipment. Traditionally, equipment must be kept on standby, leading to unnecessary energy use and higher costs. The solution provides real-time insights into equipment health, allowing for more efficient standby management. This reduces energy consumption and operational costs, contributing to substantial energy savings and a lower environmental impact. No Need for Equipment Sensoring: This solution bypasses the need for extensive sensor networks, reducing costs and logistical challenges associated with sensor installation and maintenance. Minimal Dependence on Large Data Sets: It does not rely on large volumes of historical data, making it more adaptable and less data-intensive, which reduces the time and resources needed for data gathering and processing. Actionable Intelligence On-Site: The solution provides localized insights directly at the equipment site, enabling faster response times and immediate adjustments without the need for centralized data processing. Data-Driven Insights Without Negative Data Reliance: Focused on current operational data rather than past failures, the solution promotes proactive maintenance strategies, optimizing real-time performance. Utilizes Unsupervised Deep Learning: Advanced unsupervised deep learning techniques allow the system to detect complex, previously unknown issues without needing predefined labels or categories. Improves Accuracy Over Time with Reinforcement Learning: Incorporating reinforcement learning, the solution continuously enhances its accuracy and predictive capabilities as it processes more data, leading to greater precision over time. Infocomm, Artificial Intelligence

Insomnia, particularly when caused by stress or anxiety, poses a significant challenge for many individuals. Traditional treatments, including sleeping pills, can be effective but often come with potential side effects and long-term dependency concerns. Addressing this issue, an innovative sleep patch has been developed to offer a non-invasive, drug-free solution for improving sleep hygiene. This sleep patch is designed to tackle common sleep problems such as insomnia and irregular sleep patterns, particularly those triggered by stress and anxiety. Unlike conventional medications, the patch leverages natural products to promote relaxation and support continuous sleep without the adverse effects associated with long-term drug use. Clinical research, including stress experiments and polysomnography studies, has demonstrated the patch’s ability to induce sleep for over 12 hours by alleviating stress. This makes it an ideal choice for individuals seeking a safe, effective alternative to conventional sleep aids. The technology owner is looking for collaboration with local research institutions and universities to validate the effectiveness and safety of the product through comprehensive research and clinical trials. 1) Sleep and Stress Relief Mechanism Functionality: This sleep aid is based on stress relief mechanism. In a stress relief test, the autonomic nerve stress index decreased by 40% after using the sleep patch. Similarly, the brain stress index experienced a 25% reduction.   2) Non-invasive Transdermal Delivery System Form Factor: Unlike oral medications, this patch delivers sleep-enhancing compounds directly through the skin, enabling prolonged sleep duration and improved sleep quality. This method minimizes the risk of digestive side effects and enhances the bioavailability of the active ingredients. 3)  Natural Substances and Safety Safety: Formulated with natural substances verified for safety by to the Korean Food Pharmacopoeia standards. 4)  Proven Effectiveness Scientific Validation: The product's efficacy is backed by in vitro studies and animal experiments, demonstrating significant improvements in sleep parameters. Preliminary Clinical Study: A preliminary clinical trial using polysomnography showed a 57% reduction in sleep onset time and a 20% increase in total sleep duration, contributing to better overall sleep hygiene. The potential applications are divided into categories in addressing specific sleep and stress-related needs across various demographics: Sleep-Related Applications 1. Jetlag Relief Target Group: Frequent travelers and business professionals. Application: Helps adjust sleep cycles when crossing time zones, minimizing the impact of jetlag and improving overall travel comfort. 2. Shift Workers Target Group: Night shift workers, healthcare professionals, and emergency responders. Application: Assists in regulating sleep for those with irregular work hours, ensuring they can achieve restorative sleep during the day or between shifts. 3. Elderly Care Target Group: Older adults in home care or assisted living facilities. Application: Supports better sleep patterns in the elderly, who may struggle with insomnia or frequent nighttime awakenings. Stress and Mental Health Applications 1. Stress Management Target Group: High-stress professionals, caregivers, and individuals in demanding roles. Application: Integrates into daily routines to alleviate stress and promote relaxation, leading to improved sleep and overall mental well-being. 2. Mental Health Support Target Group: Patients with anxiety, depression, or other mental health conditions. Application: Offers a non-invasive, natural aid to improve sleep quality, which is often disrupted in individuals facing mental health challenges. 3. Corporate Wellness Programs Target Group: Employees in high-pressure work environments. Application: Included in corporate wellness initiatives to reduce stress, enhance sleep, and ultimately boost productivity and job satisfaction. Safe and Non-Depressant: Unlike traditional melatonin and serotonin patches, this sleep patch addresses and minimizes the risk of depressive symptoms, making it a safer option for individuals with mood concerns or those who have experienced adverse effects from melatonin. Versatile and Accessible: The patch is suitable for both short-term and long-term sleep issues and can be conveniently purchased over-the-counter. Effective for Diverse Needs: Ideal for various applications, including managing jetlag for travellers, supporting shift workers, and improving sleep in elderly care. It is designed to cater to a broad range of users looking for a non-pharmaceutical sleep solution. Ease of Use: The transdermal delivery system provides a straightforward and non-invasive alternative to oral sleep aids. Insomnia, Sleep, Transdermal Devliery Material, Stress Relief, Natural Substances Personal Care, Wellness & Spa, Nutrition & Health Supplements, Healthcare, Pharmaceuticals & Therapeutics

Indoor vertical farming is pivotal for addressing future food challenges, particularly in arable land-scarce countries. One common method is hydroponics, which uses mineral and nutrient solutions in a water-based platform to grow crops. To optimize the crop yield and to reduce the man work hours required, it is important to automate crop health monitoring and replenishing of specific nutrients. Currently, these tasks are labour-intensive and subjective. While some imaging techniques exist for detecting plant stress and chlorophyll monitoring, a complete system covering all aspects is still lacking. For nutrient analysis, tools like pH and electroconductivity meters can only detect a change in the nutrient composition to start a feedback loop but are unable to determine the specific nutrient component or deficiency level. This technology is a comprehensive quantitative monitoring system integrating imaging spectroscopy and laser-based elemental spectroscopy to quickly identify the crop growth stages, alert crop stresses (tested on several lettuce species) and quantify specific nutrient levels in the nutrient supply. This allows for reduced man work hours and improvement of crop yield. Complete crop health monitoring through combined leaf, root, and nutrient supply monitoring, with automated replenishment Real-time in-situ component wise nutrient monitoring capability with high sensitivity (in ppb levels) enabling automated selective nutrient replenishing Non-invasive and non-contact, no sample preparation required Modular sub-systems allowing for easy integration with existing systems Machine learning capability for improved spectral library creation, enabling rapid and efficient monitoring   Applications validated at lab scale: Automated hydroponic crop monitoring in large indoor agricultural farms Inline, real-time nutrient monitoring of nutrient solutions Other applications tested at experimental POC scale and shown to be more rapid and accurate than existing methods: Real-time water quality monitoring Post-harvest quality determination of crops Trace elemental detection in body fluid   Offers full-spectrum monitrong for both crop health and nutrient supply, covering both leaf and root systems Enables automated, real-time nutrient replenishment with precise, component-wise monitoring at ppb sensitivity levels Features modular subsystems and easy integration with existing setups, supported by specific spectral libraries and machine learning for efficient monitoring and classification   Hydroponics, Nutrient Monitoring, Non-destructive Monitoring, Urban Farming, Indoor Farming, Spectroscopy, Imaging Life Sciences, Agriculture & Aquaculture, Foods, Quality & Safety, Environment, Clean Air & Water, Sensor, Network, Monitoring & Quality Control Systems

Access to clean and safe drinking water is essential for health, yet millions of people worldwide still lack this necessity. According to the World Health Organization (WHO), over 2 billion people globally use drinking water sources contaminated with feces, leading to severe health consequences. Unsafe water, along with inadequate sanitation and hygiene, is estimated to cause 485,000 diarrheal deaths each year. Water purification technologies face significant challenges, especially in decentralized systems lacking the efficiencies of large-scale operations. They often have a substantial carbon footprint due to energy-intensive processes and reliance on chemicals. Existing portable devices primarily use filtration and have a limited lifetime on-site, with little opportunity for cleaning to restore its performance.  Developed by a research team, this technology effectively addresses the above challenges by employing electrochemical methods that generates strong oxidizing agents to kill micro-organisms present in raw water and potentially degrade organic pollutants that conventional portable reactors cannot remove via filtration. Due to its working mechanism, the device is self-cleaning and does not need regeneration. By harnessing solar energy and activated carbon, this chemical-free purification approach is not only environmentally friendly but also perfectly suited for deployment in remote areas, developing countries, and disaster-stricken zones where traditional water treatment infrastructure is lacking. The technology owner is looking for collaborations with local SMEs to co-develop scaled systems and deploy it through disaster relief organizations, government agencies and non-profit organizations in selected developing countries.  Power Source: Solar-powered, enabling operation in off-grid and remote areas, resulting in reduction of operational costs and ensures continuous, sustainable water purification Electrochemical Reactor: Anode: Mixed Metal Oxide (MMO) anode which generates strong oxidizing agents to degrade certain recalcitrant pollutants Cathode: Activated Carbon, enhancing contaminant removal through absorption and electrochemical processes Chemical-Free Operation: Eliminating the need for chemicals, making it more sustainable, safer and more cost effective Contaminant Removal: Organic Contaminants: The technology can effectively remove organic pollutants, with 65% of an initial 50 ppm phenol concentration being removed within 60 minutes proven in a prototype system. Coliform Reduction: Electrochemical treatment rapidly reduces coliform levels to meet water reuse guidelines of less than 10 CFU/100 mL in just 3 minutes. Biochemical Oxygen Demand (BOD₅): The system is capable of bringing BOD₅ levels within guideline standards in as little as 15 minutes. Water Treatment: Provides clean water in areas without conventional water treatment infrastructure  Humanitarian Aid: Supports disaster relief and NGOs in emergencies like natural disasters and refugee camps. Rural Development: Serves remote and rural areas, especially in developing countries without centralize facilities. Mobile units: Portable purification for troops in harsh or remote environments, ideal for off-grid communities, emergency preparedness and mobile operations needing reliable water purification. Sustainable Power Source: Solar-powered, reducing reliance on external energy sources and ensuring operation in off- grid locations Chemical-Free Operation: utilizes electrochemical methods, environmentally friendly Effective Contaminant Removal: Capable of degrading recalcitrant pollutants and organic compounds Environment, Clean Air & Water, Sanitisation

Due to the rising demand for industrial automation, autonomous robotic technology is gaining traction across various industries optimising processes and increasing operational efficiency. For these autonomous robots to execute their task with precision, they are required to be constantly aware of their surroundings to response adequately and quickly. Technologies developed from off-the-shelf components (e.g. camera-based perception) faces integration issues while industries with weak or no connectivity to the Global Navigation Satellite System (GNSS) are unable to utilise them. Developed by a Singapore-based startup, the proposed technology herein encompasses a modularised sensor hardware and edge AI software within a compact form factor, addressing fundamental 3D vision problems such as localisation positioning and obstacle detection. This solution can be easily customised, integrated and deployed in GPS-denied or GPD-obstructed areas while maintaining accuracy and reliability in navigation, tracking and monitoring of fleet, autonomous vehicles, etc. The technology solution has engaged with numerous proof-of-concept (POC) projects, including one notable engagement within the defence industry for a drone integration. The technology owner is looking for collaborative partners, such as manufacturers and system integrators within the automation space, who wishes to further enhance their robot’s perception capabilities. This technology solution is a compact device comprising of dual stereo cameras and integrated sensors with sufficient onboard processing power (4 TOPS) embedding state-of-the-art edge AI software for their visual positioning system. The solution is: Compact and lightweight (credit card size form factor) Rated IP67 Cost-effective Easy to integrate with open and interoperable architecture Usability in limited or no GNSS signal areas, as well as areas with differing lighting conditions The solution can be customised for easy integration for numerous robotic systems to enable functions such as: 3D localised positioning and depth perception Customised visual-inertial navigation Object and space detection Occupancy mapping Map building Edge AI classification This 3D vision solution can be deployed within robotic technologies across various industries that are more position-dependent, faces numerous interference and experiences limited network coverage such as: Indoor drones and legged or wheeled robots in industries including construction, warehouse, robotics, mining, etc Warehouse robotics and autonomous forklift Autonomous mining and human operated vehicles for collision avoidance Robotics solutions in defence, especially drones but also ground vehicles Defence adjacent industries such as first responders: fire fighters, police and K9 dog units The computer vision market is valued at US$11.94 billion in 2015 and is expected to be valued at US$17.38 billion by 2023, exhibiting a CAGR of 7.80% within the forecasted period. The 3D vision solution offers a modular approach (with hardware and software) which addresses integration and development issues for position-dependent robotics or vehicles, saving resources and time. This visual positioning system enables the deployment of any perception-based robots to execute reliable and accurate navigation within areas of weak or no connectivity. Virtual Positioning System, Computer Vision, Obstabcle Avoidance, Stereo Camera, Occupany Map, Edge AI, Camera-Based Perception Electronics, Sensors & Instrumentation, Infocomm, Video/Image Analysis & Computer Vision, Robotics & Automation

As global temperatures rise, governments are setting eco-friendly building standards to address concerns about energy consumption and carbon emissions. Improving energy efficiency in buildings, especially in hot climates where cooling demands increase energy use, has become a major challenge. This has driven the need for sustainable and energy-efficient building materials. Aerogels are among the most promising insulation materials due to their large specific surface area (500-1200 m²/g), high porosity (80-99.8%), and ultra-low density (around 0.003 g/cm³). They are amorphous, chemically inert, non-flammable, and exhibit extremely low thermal conductivity (0.01-0.03 W/(m·K)). Silica aerogel (SA) is particularly notable for having the lowest thermal conductivity, making it ideal for building insulation. The technology owner has developed an advanced insulation coating that incorporating in-house fabricated silica aerogel (SA) powders to enhance both thermal and acoustic insulation in buildings. This technology also works with silica aerogel powders purchased externally. Incorporating 20 vol% SA into paint and plaster formulations can reduce surface temperatures by up to 12°C and chamber temperatures by up to 3.3°C, helping to lower air conditioning use and save energy. The coating also improves acoustic insulation, offering a dual benefit. By meeting the growing demand for greener building solutions, this technology offers a competitive edge in reducing energy consumption and improving overall comfort and building performance.   The technology owner is seeking industrial partners for test-bedding and is also open to licensing opportunities for commercialization, especially with construction companies, building material manufacturers, and developers focused on sustainable and energy-efficient construction. This technology leverages the exceptional properties of silica aerogel (SA) to represent a significant advancement over current state-of-the-art building insulation materials, making it ideal for sustainable construction. Key features include: Silica aerogel has the lowest thermal conductivity of any solid insulation, outperforming even still air SA has an amorphous structure made of over 90% air, making it the world’s lightest solid material and breathable, enabling fresh air circulation Incorporating SA into building materials significantly reduces k-value, achieving high efficiency with thinner coatings or plasters while maintaining excellent energy efficience Adding SA to plaster enhances its thermal insulation properties in high-temperature environments (45°C), with a temperature reduction of up to 3.3°C Concrete cubes coated with 5 mm thick SA plaster show superior noise insulation, achieving a noise reduction of up to 19.6 dB Enhances both thermal and acoustic insulation, contributing to energy-efficient and comfortable woking and living spaces This technology is highly suited for the construction and building materials industry, with a focus on enhancing energy efficiency and sustainability in both new buildings and retrofitting projects. Its primary application is to improve thermal and acoustic insulation in residential, commercial, and industrial buildings. By incorporating silica aerogel into paints and plasters, it significantly reduces the need for heating and cooling, lowering energy consumption - particularly valuable for green building initiatives and sustainability certifications. The technology also improves soundproofing, making it ideal for noise-sensitive environments like hospitals, schools, and office spaces. Additionally, its high-temperature resistance makes it suitable for industrial insulation applications including furnaces and pipelines. Potential solutions that can be co-developed from this technology include but are not limited to: Thermal insulation paints Insulating plasters Prefabricated insulating panels Lightweight insulating concrete blocks In 2022, the global market for building insulation materials, including thermal insulation, was valued at approximately USD 26 billion and is expected to exceed USD 37 billion by 2027, with a compound annual growth rate (CAGR) of around 7%. The growing demand for advanced insulating materials like silica aerogel is driven by stringent energy efficiency regulations, increasing awareness of environmental sustainability, and the rising trend of green building certifications. Exceptional Thermal Insulation: Leverages silica aerogel’s extremely low thermal conductivity, enabling thinner and lighter insulation layers without compromising energy efficiency Enhanced Acoustic Insulation: Provides noise reduction, ideal for environments where soundproofing is essential Thin and Lightweight: Delivers high-performance insulation with significantly reduced thickness and weight, optimizing space and reducing material usage compared to traditional materials like fiberglass and polystyrene High Safety and Durability: Non-flammable and highly stable under extreme temperatures, offering better safety than traditional insulation materials Sustainability: Contributes to long-term energy savings, space optimization, and overall building performance, providing both environmental and economic benefits for sustainable construction Silica aerogel, insulation paint, insulation plaster, thermal insulation, acoustic insulation Chemicals, Coatings & Paints, Green Building, Heating, Ventilation & Air-conditioning, Sustainability, Sustainable Living

In the construction sector, manual inspections have traditionally been the primary method for detecting water seepage surface defects, a mandatory requirement for construction projects. However, these inspections often suffer from the inherent subjectivity of human judgment, leading to potential inconsistencies and inaccuracies. To overcome these limitations, a handheld water seepage detection system was developed and rigorously tested in collaboration with the Building and Construction Authority (BCA). This innovative system is designed as a portable, intelligent alternative to traditional methods, aiming to enhance the objectivity and reliability of water seepage detection. The system utilizes advanced Long-Wave Infrared (LWIR) thermal sensing technology to accurately detect temperature variations indicative of water seepage. Unlike manual inspections, which can be prone to error, this system offers precise differentiation between genuine water seepage defects and common artifacts found on construction sites, such as glue and paint. By minimizing false alarms, it provides a more dependable and efficient approach to identifying and addressing water-related issues. This advancement not only improves the accuracy of inspections but also ensures that potential water damage is detected early, reducing the risk of costly repairs and enhancing the overall integrity of construction projects.     1. The system uses a high-resolution OEM 640 x 512 Long-Wave Infrared (LWIR) thermal camera, accurately capturing subtle temperature variations, ideal for detecting water seepage. 2. An integrated HD RGB camera with an Infrared (IR) illuminator enables clear imaging in both normal and low-light conditions. This dual-sensor setup enhances inspection reliability by providing both thermal and visible-light data. 3. The system runs on a 10AH Lithium Polymer (LiPO) battery, offering long-lasting power for extended use. The battery is easily removable, allowing for quick replacement and minimizing downtime during field inspections. 4. Featuring an ARM-based single-board computer with 32GB SSD storage and 8GB DDR RAM, the system provides robust data processing. A 5-inch touch screen offers a user-friendly interface for real-time data management and image viewing. 5. The system includes Application Software with advanced image processing algorithms to enhance detection accuracy by reducing noise and emphasizing temperature contrasts.   The smart imaging-based water seepage detection system is highly effective for detecting water seepage in both completed and under-construction buildings, especially in areas with restricted access. It is particularly valuable for enclosed spaces, such as private residential buildings with hidden plumbing behind false panels, where traditional water tightness tests are less comprehensive due to accessibility limitations. The technology owner is seeking collaboration with companies in the building & construction and environmental services industries. An alternative technology to manual water seepage monitoring. Utilizes advanced LWIR thermal imaging and algorithms to precisely detect true water seepage, minimizing false positives. Enables non-invasive inspections, reducing the need for destructive testing and enhancing worker safety. Greater Efficiency by offering real-time data processing with immediate results, reducing inspection time. Portable design with easily replaceable battery allows for continuous use, optimizing field operations and increase productivity Able to detect water on surfaces of concrete and plastic material at distance of up to 3m. This is extremely helpful when the presence of water is unable to be verified by visual or touch. Equipped with automatic data logging function for future reference and traceability. Building Construction Authority, Long-Wave Infrared (LWIR), Water Seepage Infocomm, Video/Image Processing, Manufacturing, Surface Finishing & Modification, Environment, Clean Air & Water, Sensor, Network, Monitoring & Quality Control Systems