TECHINNOVATION TECH OFFERS

Maintaining stable blood glucose levels is central to achieving a healthier lifestyle and preventing metabolic disorders such as diabetes. Even for non-diabetic individuals, daily fluctuations in glucose can affect energy levels, focus, sleep quality, and long-term metabolic health. As awareness grows around personalized health tracking, consumers are increasingly seeking simple, non-invasive ways to understand how diet, exercise, and stress influence their glucose patterns. BGEM meets this need through a smartphone app that estimates blood glucose levels non-invasively using data from smartwatches, fitness trackers, and smart rings. By leveraging the photoplethysmography (PPG) sensors that users already wear, the app provides on-demand insights into glucose fluctuations without the need for finger pricks or patches. Powered by advanced algorithms in the cloud, the system translates wearable sensor data into personalized glucose trend information, allowing users to visualize how daily habits influence their metabolic responses. This empowers individuals to make informed lifestyle adjustments, supporting better nutrition choices, improved fitness outcomes, and early awareness of potential glucose irregularities. Unlike conventional continuous glucose monitors that rely on invasive sensors, this technology is completely non-invasive, affordable, and accessible, making proactive glucose monitoring possible for a broader health-conscious population. This solution is designed for consumers who want to take greater control of their wellness journey through meaningful, data-driven insights. The technology owner is seeking collaborations with hardware manufacturers for integration, wearable brands for product development, distributors and IHLs for expanding research. 

Wound healing is a complex process and is associated with multi-stage cell/tissue transformations. The entire wound healing process is generally complete around 20 days after skin injuries. Unfortunately, impaired wound healing, which usually occurs as a result of infection or the pathological status of the patients, i.e., diabetes, obesity, cancer, and in particular, severe inflammation, leads to excess exudate production and tissue ulcers, causing prolonged health problems and economic burdens for patients. This technology introduces a sterilized nanoemulgels xanthones (XTs-NE-Gs) which are compounds from mangosteen peel dispersed in a gel base. The methodology involves using a high pressure homogenization technique without the addition of organic solvents in the formulation to produce sterilized XTs-nanoemulsion (NE) concentrate. After blending sterilized XTs-NE concentrate and the sterilized gel, a sterilized XTs-NE-G was obtained.   The concentrate has proven effective enhancement activities on the proliferation and migration rates of skin cells. It also promoted re-epithelialization, collagen deposition and inflammation suppression in mice models. Xanthones has proven strong anti-oxidant, anti-inflammatory and anti-bacterial properties. The nanoemulgel technology can overcome the typical problems from the addition of some solubilizers to enhance solubility of XTs in the products, in particular, alcohol that cause burn sensation on the open wounds.  Importantly, the obtained product from this technology could be sterilized and thus safe for wound healing purpose. The technology owner is seeking collaborations for clinical trials to obtain information for supporting product safety and efficacy and manufacturers for scale up. 

Lignin polymer composites represent a class of sustainable materials that combine eco-friendliness, cost-effectiveness, mechanical reinforcement, with intrinsic functional properties such as UV protection, antioxidant activity, barrier performance, and antimicrobial effects. While conventional production methods often rely on solvents or require separate lignin modification steps—leading to higher costs and loss of functionalities—this technology introduces a one-step process to efficiently produce lignin biopolymer composites by efficiently blending lignin and essential oils into a polymer. The technology works by directly dissolving lignin in essential oils and then feeding this solution, along with a biopolymer like PLA, PBS, PBAT, or PP, into a twin-screw extruder. This method ensures an even dispersion of the mixture throughout the material without the need for additional solvents or complex pre-processing. The resulting material has enhanced properties, including antimicrobial, UV-resistant, and antioxidant capabilities, as well as controlled release of active ingredients. The final materials can be manufactured into various products, including 3D printing filaments, films, or molded items. The technology owner is seeking collaborations with partners in Singapore, particularly those involved in medical materials (e.g., wound dressings), active food packaging, biodegradable agricultural films, and 3D printing materials, to co-develop innovative solutions that support a circular economy.

All-solid-state lithium batteries are emerging as the next frontier in energy storage, offering higher safety and energy density than conventional lithium-ion systems. A key challenge in their development lies in producing high-purity lithium sulfide (Li₂S)—a critical precursor for sulfide solid electrolytes such as Li₁₀GeP₂S₁₂. Conventional synthesis methods typically require high temperatures and complex purification, resulting in high costs and limited scalability. This technology presents a novel low-temperature chemical synthesis process for producing battery-grade Li₂S under mild reaction conditions (below 100 °C). Using a solution-based approach with organic solvents, surfactants, and catalysts, the process achieves precise control over Li₂S particle size (50 nm–1 µm) and crystallinity. The resulting material exhibits high purity (up to 99.5% - 99.9%), high yield (85% - 90%) and improved ionic conductivity when incorporated into solid electrolytes. The simplified synthesis eliminates post-annealing and purification steps, reducing production cost and energy use while enabling scalable mass production. There is also no need for dry-room or toxic-gas facility, drastically reducing costs for CAPEX and OPEX.  The technology owner is looking for R&D collaboration with battery manufacturers, material suppliers, and R&D institutions who are developing next-generation all-solid-state batteries.

AI-assisted Mechanical Computer-Aided Machining (AMCAM) is a hands-on educational platform designed to teach students the principles and real-world applications of AI agentic agency within CNC machining. Built upon an AI agentic agency blueprint, AMCAM provides a new learning environment that integrates CNC milling operations with a suite of intelligent, autonomous AI agents. The system features five specialised AI agents functioning as digital co-workers, modeling collaborative decision-making between humans and AI in modern manufacturing contexts. Through this setup, students not only gain practical CNC machining experience but also engage with a full AI decision loop. They can observe how AI agents communicate, reason, and act both independently and collectively. Beyond education, AMCAM also serves as a sandbox for SMEs and MNCs to co-develop pilot projects, in alignment with Singapore’s Smart Industry Readiness Index (SIRI). It supports the Industry Transformation Maps (ITMs), advancing national strategies to modernise the precision engineering and manufacturing sectors, while driving workforce transformation and enterprise growth. Key focus areas include deploying AI for predictive maintenance, quality control, supply chain optimisation, and energy efficiency. Other applications include digital twins, machine learning algorithms, and smart sensors to accelerate industry transformation.

Falls are a leading cause of injury and hospitalization among the elderly, often resulting in loss of independence and increased healthcare costs. Traditional walking aids provide basic support but lack the capability to proactively detect and prevent falls. This AI-Assisted Walking Cane is an innovative mobility aid developed to improve the safety and independence of elderly users and individuals with mobility challenges. By enabling real-time monitoring and intervention, it effectively bridges a critical gap in traditional walking aids and helps reduce the risk of falls. The primary target users are elderly individuals, patients undergoing physical rehabilitation, and people with neurological or musculoskeletal conditions that impact mobility. The technology owner seeks collaboration with partners across the healthcare, technology, and manufacturing sectors to support the product’s development, testing, and commercialization. Ideal partners include medical institutions and rehabilitation centres to provide clinical validation, user trials, and professional feedback; deep-tech companies with AI and data analytics expertise to develop and optimize algorithms for gait analysis and fall detection; assistive device manufacturers for prototyping, large-scale production, and quality assurance; institutes of higher learning for joint research in biomechanics, sensor technologies, and future applications; and eldercare service providers or community health organizations to facilitate pilot testing and deployment in real-world care settings.

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.