TECH OFFERS

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

In healthcare, accurately assessing pain is critical, yet it remains a significant challenge, particularly for patients unable to effectively communicate their discomfort. This includes individuals with cognitive impairments, critical care patients, and pre-verbal children. Traditional pain assessment methods rely heavily on verbal communication or subjective observer-based pain assessment, which can lead to missed or poorly managed pain, resulting in either under-treatment or over-analgesia treatment. To address this issue, this advanced AI-based solution automates the process of estimating pain intensity by analyzing facial expressions captured in video data. The technology is a deep learning system consisting of facial landmarks (specific points on a person's face, such as the corners of the eyes, nose, mouth, and other prominent facial features) extraction, 3D normalization and Spatial-Temporal Attention Long Short-Term Memory (STA-LSTM) model. These facial landmarks provide critical information about facial expressions, allowing the system to accurately assess pain levels. By integrating this technology into clinical settings, healthcare providers can significantly enhance patient care, reduce the burden on staff, and improve overall pain management practices. This solution not only ensures timely and appropriate intervention but also protects patient privacy by using non-identifiable facial landmarks, making it a powerful tool for modern healthcare environments. The technology is an advanced AI-based software algorithm designed for automated pain detection using facial expressions. It offers the following features: Automated Pain Detection: Utilizes a deep learning model that seamlessly integrates facial landmark extraction and analysis to estimate pain intensity levels without the need for human intervention. Real-Time Monitoring: Continuously tracks and assesses pain levels from video footage, providing instant feedback and visual representation of pain level distribution over time. AI-Driven Analysis: Powered by a Spatial-Temporal Attention Long Short-Term Memory (STA-LSTM) network, the system excels in identifying and analyzing specific facial expressions related to pain, ensuring high accuracy in pain detection. Privacy Protection: The system exclusively uses non-identifiable data by extracting and processing facial landmarks, ensuring patient privacy while maintaining the integrity of pain analysis. High Accuracy: Achieves a training accuracy of 98% and a validation accuracy of 92.2%, supported by robust data processing techniques, including 3D normalization of facial landmarks and strategic data balancing. This technology is highly suited for hospitals, nursing homes, and healthcare facilities that manage patients who are non-communicative, cognitively impaired, or otherwise unable to express their pain effectively. It is also valuable for telemedicine platforms, rehabilitation centers, and home care services, where remote patient monitoring is critical. Furthermore, the system can be seamlessly integrated into surgical and critical care units to provide real-time pain assessment. Its ability to integrate with existing infrastructure, such as CCTV systems, makes it a cost-effective, easily adoptable solution that enhances pain management across various healthcare settings. This system offers secure, non-invasive, objective and real-time pain assessment by analyzing non-identifiable facial landmarks, ensuring patient privacy and compliance with data protection regulations. Objective and Continuous Pain Assessment: Provides real-time, objective monitoring, reducing reliance on subjective assessments. Improved Patient Outcomes: Ensures timely and appropriate pain management, preventing under- or over-analgesia treatment. Privacy Protection: Uses facial landmarks for analysis, maintaining patient anonymity. Eases Healthcare Providers' Burden: Automates pain monitoring, allowing staff to focus on other critical tasks. Cost-Effective Integration: Easily integrates with existing infrastructure, offering a scalable solution. Broad Applicability: Suitable for diverse healthcare environments, including hospitals, nursing homes, and telemedicine. Facial Recognition, Pain Detection, Facial Landmarks, STA-LSTM, Healthcare, Cognitive Impairments Infocomm, Artificial Intelligence, Healthcare, Diagnostics, Medical Devices, Telehealth, Medical Software & Imaging, Healthcare ICT

With the global trend of industrial automation, robotic arm technology is being developed and integrated to existing business workflow, increasing labour productivity and operational efficiency. However, current end effectors attached to robotic arm excels in automation tasks of handling homogeneous robust objects but fall short in handling irregular, fragile objects. Current robotic grippers (end effector) lack the finesse and limberness required, limiting their usage in particular areas such as agriculture, F&B, pharmaceutical and logistics. The technology solution developed is a smart soft robotic gripper as a modular end effector that addresses the challenge of handling objects with varying sizes, shapes, and weights, an issue unsolved by traditional robotic grippers. This innovative gripper tool mimics the flexibility and versatility of biological structures like tendrils, enabling an extra dimension of growth and twining capabilities. By wrapping itself securely around objects, the gripper manipulates items gently, minimizing the risk of crushing or damaging them. Its integrated sensors provide real-time contact feedback capabilities, enabling precise monitoring and adaptive control by the robotic system. The technology owner is seeking collaborative partners, such as system integrators or end-users, who are in need and keen to integrate a versatile, adaptive, and gentle handling solution that can operate efficiently in environments where object fragility or irregularity is a key concern. The smart soft robotic gripper module comprises of three key components: flexible fingers, actuation system and sensor integration. A novel concept is introduced for a flexible finger, utilizing a single tendon within a flexible body to perform three-dimensional bending and twisting motions. This design enhances the gripper’s adaptability, allowing it to handle objects with various shapes, sizes, and weights, with current payload exceeding 10kg. The integration of vision and haptic sensors further refines its capabilities to provide gentle and precise manipulation of delicate items. Additionally, the sensor integration supports potential applications in sensor fusion and IoT systems, expanding its utility across advanced automation environments like smart farms and smart factories. With its modular design, it enables customisation and scalability to integrate into existing robotic systems. Handling of Food (urban farming, food and beverages) The gripper solution can gently handle delicate crops like bunches of vegetables and irregularly shaped fruits, which can facilitate automated harvesting or processing with minimal damage. Its adaptability makes it potentially suitable for smart farms where precision and adaptability are essential. A pilot test for harvesting automation is currently being conducted in an urban farming application. Smart Factories (warehousing, manufacturing) The gripper solution is able to handle a variety of fragile and odd-shaped product, providing flexibility to environments of heterogenous items. The technology also enables safe handling of items, promoting industrial automation of delicate assemblies and improving assembly precision. Pharmaceuticals (medical device, procedures) The gripper tool can handle sensitive medical devices and products to minimise or prevent damaging during handling. The tool is able to provide additional assistance to medical personnel for more delicate medical procedures, reducing discomfort while increasing precision. The smart soft robotic gripper is bio-inspired and mimics natural organism, like octopus arms, to enhance navigation and interaction with their surroundings. This results in an extra dimension of flexibility and versatility to handle intrinsic nonlinearity of soft, delicate, heterogenous materials. The integrated sensors enable situational awareness capabilities, providing adaptability and enhancing precision. Lastly, the modular design provides customisability to specific use-cases, with the gripper being able to be scaled to suit the operational needs. Soft Gripper, Smart Gripper, End Effector, Soft Robotic Gripper Electronics, Actuators, Manufacturing, Assembly, Automation & Robotics, Foods, Processes

Vision-based Artificial Intelligence (AI) models require substantial time to train, fine-tune and deploy in production. After production, this process is still required when performance degrades and re-training on a new dataset becomes necessary; this maintenance process exists throughout the model's lifetime to ensure optimal performance. Rather than embarking on the time-consuming and painful process of collecting/acquiring data to train and tune the AI model, many organisations have turned to the use of pre-trained models to accelerate the AI model development process. This technology consists of a suite of pre-trained models that are intended to detect food, human behaviours, facial features and count people. These AI models are operable on video footage and static images obtained from cameras. Models are tuned and trained on various use-cases and are accessible via API calls or embedded within software as a Software Development Kit (SDK) library. These models can be deployed as AI as a Service on Microservices platform providing customer data protection with blockchain technology. With customer protection enhanced with blockchain technology, AI Model performance can further be enhanced to meet customer requirement.   The technology consists of a suite of pre-trained AI models that provide high accuracy (over 80%) and can be further customised to improve accuracy and adapted to different use-case scenarios. Models can be integrated in the following ways:  Installed library package embedded within software on-device/on-premise HTTP-based Application Programming Interface (API) calls with video/image data to cloud-installed library package The following are the features for various AI models: Abnormal Behaviour Recognition Continuous monitoring and detection of abnormal human behaviours e.g. fighting, loitering Event Detection Recognises a variety of subjects and events e.g. sports day, graduation, wedding, festival, Christmas, from video footage Optimised for lightweight compute capability (Intel OpenVino) Food (Fresh and Packaged) Recognition Real-time detection of fresh and packaged foods Detects abnormal fresh food or defective packaged food Classifies food types e.g. lotus, spinach, cucumber, radish etc. Optimised for low compute capability Privacy-Preserving Person Recognition Privacy preserved people detection, counting and human activity recognition Images are blurred to preserve private information that can lead to personal identification (irreversible) Optimised for lightweight edge computing Free (Empty) Space Recognition Semantic segmentation to identify empty spaces Customisable for any free-space detection scenario High accuracy in night scenes Safety Monitoring Object detection with prohibited and allowed zones (e.g. person or forklift) Detects and identifies safety risks associated with safety distances Enables audible alarm systems of abnormal situations Wellbeing and Safety Detection Automatically detects and classifies nudity images from images  Enables alerts to be delivered to parent/caregiver's device Customisable to detect new categories of inappropriate content This technology offer comprises a suite of AI models for the following applications: Abnormal Behaviour Recognition Public areas or areas where social order needs to be maintained e.g. food & beverage, entertainment establishments Event Detection Automatic creation and/or organisation of media content i.e. photo classification Automated adjustment of device hardware parameters e.g. audio, colour, brightness when displaying specific types of content e.g. sports Food (Fresh and Packaged) Recognition Food stock level detection, food inventory management Automatic detection of fresh/packaged goods within a constrained area Privacy-Preserving Person Recognition Privacy protection of visual information, in high traffic areas, without deterioration of video quality Free (Empty) Space Recognition Vehicle position localisation on roads Navigation (free-space localisation) in partial/fully self-driving automotive vehicles Identification of free storage spaces in the logistics industry Safety Monitoring Automated compliance checks Workplace safety analysis and tracking Wellbeing and Safety Detection  Parental control in browsers, smartphones or other image storage devices e.g. Network Attached Storage (NAS), Solid State Drives (SSD) AI Models were rigorously tested in the fields of different scenarios. The microservice platform where AI Model ingest the visual data streams offers a secure customer data protection and privacy using blockchain technology. Making this Microservice platform capable of tracking customer’s data usage and thus ensure privacy when AI model operating on the platform are simultaneously improved using unique customer data captured on customer’s premise. Accelerate AI development - eliminate the need for dataset creation, annotation, tuning and testing Customisable AI models - fine-tuned to environment and condition Operational support to continuously improve AI accuracy from newly collected data   event detection, abnormal human behaviour recognition, safety monitoring, food package detection, food freshness, nudity detection, empty space Infocomm, Video/Image Analysis & Computer Vision, Video/Image Processing, Artificial Intelligence

Eldercare centres have a unique structure due to the several variables & constraints regarding the elder and service type. Unlike the other item or passenger transportation problems, the eldercare industry does not have a standard approach to match the number of elders and vehicle capacity because some elders are transported by a wheelchair which covers approximately two seats, whereas the others may be ambulant. In addition, for some cases, such as an elder with dementia, a caregiver may accompany the elder, making the capacity-elder match more complicated & dynamic per vehicle trip. Considering this capacity utilization problem in the eldercare & healthcare industry, this technology was developed, which is a routing algorithm that optimally matches the number of elders and vehicle capacity to minimize the number of vehicles deployed per trip while maximizing vehicle utilization by providing the minimum travel distance and travel time. As a result, eldercare service providers will provide faster services to customers and reduce their outsourced vehicle costs. The routing optimization model was designed to improve the transportation service quality eldercare centers by focusing on: Optimal elder routing & sequence per vehicle trip Database structure to eliminate manual workload Optimal vehicle scheduling Operational KPIs structuring The algorithm is able to be integrated as a microservice under a platform interface whereby all applications are accessed & monitored by the end-user. The capacitated vehicle routing problem with time windows (CVRPTW) has a wide range of applications where each customer service should start at a specified time window. In this technology,  CVRPTW was adapted into eldercare transportation cases considering the particular specifications such as elder type as ambulant, with wheelchair, service type as daycare or rehab and caregiver accompaniment. As a result of the model, approximately a 20% improvement was observed in travel distance and travel time per vehicle trip for some centers. Routing optimization of elderly to and from eldercare homes. Data Bridge Market Research analyses that the elderly care market which was USD$832.8 billion in 2021, would rocket up to USD$1,268.43 billion by 2029, and is expected to undergo a CAGR of 5.40% during the forecast period 2022 to 2029. High customization for the eldercare sector: No requirement for further customization, time and resource-saving Niche product: Low level of competition, similar algorithms need to be customized first for the specific considerations of the eldercare industry Optimal output: Proof of the model reliability, safe to implement Integrability: Flexible to interact with other applications Infocomm, Artificial Intelligence

A Digital Twin is a digital representation of a physical object or system, often used in various industries for simulation, analysis, and monitoring. In the built environment, which encompasses everything from buildings and infrastructure to urban planning, Digital Twins have a wide range of potential applications that can significantly enhance efficiency, sustainability, and overall quality of life. Digital twins have emerged as a transformative concept in the built environment, revolutionizing how buildings, infrastructure, and cities are designed, constructed, and managed. This innovative technology leverages the power of digital simulations and real-time data to create virtual replicas of physical assets, offering numerous benefits across various sectors within the built environment. The technology owner is seeking co-development partnerships with building owners, facity management companies, smart city or urban planners to adopt their digital twin technology in achieving their sustainability objectives. Digital twin model development & data gap report This stage involves the creation of a baseline digital twin of the proposed facility. Measured performance data input This involves gathering measured data from various sources. This would be the building BMS system and/or any other source of live or streaming operation data. Model calibration This includes the testing of the model with logic checks and balances to verify the basic inputs. Actual building experience and monitored data will be used to make any final adjustments and calibration so that the virtual model outputs align closely to reality. Analysis & diagnosis Once the baseline model is complete and confidence exists as to its validity from the calibration accuracy (over 95% accuracy), the model can be used to run “what-if” scenarios for the future. Retro commissioning (RCx) i.e. change in operations without any additional investment options will be analysed. Corrective action The team will develop a set of bespoke/customized alarms, alerts and control rules to continuously optimize building energy performance using real-time data. Deployment A workshop will be conducted to make the participating stakeholders aware of the digital twin process. Required software access as well as the user guides will be shared during the deployment. Monitoring The final stage will be the monitoring of the digital twin post-implementation. Some key potential applications for Digital Twins in the built environment: Architectural and Urban Planning: Digital Twins can be used to create virtual models of cities, allowing urban planners and architects to simulate and visualize different design scenarios. Energy Efficiency and Sustainability: Digital Twins can be used to model and simulate a building's energy consumption and environmental impact. Facility Management: Once a building is operational, Digital Twins can be used for ongoing facility management. Smart Cities: Digital Twins can serve as the backbone of smart city initiatives. By creating digital replicas of urban infrastructure and systems, city authorities can monitor traffic flow, manage waste collection, and respond to emergencies more effectively. Real Estate Development: Developers can use Digital Twins to create virtual walkthroughs of properties, allowing potential buyers or tenants to explore spaces before they are built. The Digital Twin industry is growing phenomenally, the Digital Twin Market size is expected to reach 63.5 Bil USD by 2027. The number of cases using digital twins for implementation is likely to go up to 23% in 2024 from 10% in 2021. The opportunities to use a digital twin in a built environment are quite a few: Building Performance Optimization: Digital Twins allow for continuous monitoring of a building's performance, including energy consumption, HVAC systems, and structural integrity. Sustainable Building Practices: With increasing emphasis on sustainability, Digital Twins can facilitate the design and monitoring of green and sustainable buildings. Urban Planning and Smart Cities: Digital Twins extend beyond individual buildings to entire urban environments. Cities can create virtual replicas of their infrastructure to optimize traffic flow, manage resources efficiently, and improve the overall quality of life for residents. Real Estate and Property Management: Property owners and managers can use Digital Twins to enhance tenant experiences, monitor building health, and predict maintenance needs. Facility Maintenance and Operations: Digital Twins provide real-time insights into the condition of assets within a facility. Data-Driven Decision-Making: The wealth of data generated by Digital Twins allows for data-driven decision-making at all stages of a building's lifecycle. Integration with IoT and AI: The combination of Digital Twins with the Internet of Things (IoT) and Artificial Intelligence (AI) technologies further enhances their capabilities. Improved Design and Simulation: Architects and engineers can use Digital Twins to experiment with different design concepts and test how they perform in various conditions. This allows for better optimization of building systems, materials, and energy usage, resulting in structures that are more sustainable and resilient. Real-Time Monitoring and Maintenance: Once a building is operational, the Digital Twin continues to add value by collecting and analyzing real-time data from sensors and IoT devices. Energy Efficiency: Digital Twins can optimize energy usage by analyzing data from sensors that monitor temperature, humidity, occupancy, and more. Cost Savings: By preventing errors, reducing downtime, and improving energy efficiency, Digital Twins can generate substantial cost savings over the entire lifecycle of a building or infrastructure project. Sustainability: Digital Twins enable sustainable design and operation by allowing architects and engineers to assess the environmental impact of their decisions. Risk Management: By simulating different scenarios and continuously monitoring a building's performance, Digital Twins can help identify potential risks and vulnerabilities, allowing for proactive risk management and disaster preparedness. Remote Collaboration: In an increasingly globalized world, Digital Twins facilitate collaboration among teams located in different parts of the world. Data-Driven Insights: Digital Twins generate vast amounts of data, which can be leveraged for data-driven insights and machine learning applications. Green Building, Sensor, Network, Building Control & Optimisation