TECH OFFERS

The conventional DC brushless motors face the challenge of reduced output when their size is reduced to achieve a smaller product, as well as the difficulty of precise control according to the load. A unique solution to these problems would be the use of compact, high-power DC brushless motors with vector control technology. These current issues contributed to the product developers in the creation of more compact and lightweight products that offer improved performance and increased functionality by responding to load-specific characteristics. With vector control technology, these motors provide precise control over motor speed and torque, resulting in enhanced efficiency and reduced energy consumption. The benefits of using these motors include improved product design, increased functionality, and greater efficiency The technology offer comprises of two portions of the motor internal structural design and the use of vector control technology to maximize the performance of the overall system.  These unique motors control system offers a reliable and effective solution to the challenges faced by conventional DC brushless motors. The technology owner is keen to do R&D collaboration and licensing out the know-how to a variety of applications such as robotics, electric vehicles, and industrial automation systems.    The main features of the technology offer are: 1. Compact and lightweight: The motor's compactness and high-power output are achieved by improving the space factor using split iron core structure Ability to achieve about 40% reduction in physical size of motor while maintain the power output Weight of the motor can achieve reduction of about 25% Output power increased by upto 60% compared to the similar-sized motors 2. Precision drive control according to load fluctuations by vector control: The motor can be controlled to the optimum speed and torque according to the load by monitoring the motor load from the individual current values across the three phases. Optimum drive control can achieve 10% increase in working speed and 15% increase in workload 3. Environmental resistance performance: Waterproof and dustproof performance equivalent to IP56, making it suitable for machine tools and equipment used outdoors. The technology offer can be customised and adopted in various application that uses compact brushless DC motors, such as: Personal Mobility: Electric bicycles Electric kickboards Electric baby car Material Handling: Automatic guided vehicles (AGV) Electric power-assisted trolleys Personal and Commercial Automation: Electric doors Platform screen doors Electric garage gates Non-residential automatic doors Electric reels for fishing Automatic cleaning robots Electric massage chairs Industrial and Manufacturing: Machine tools (drill press, NC lathe, screw fastener, drill machine) Power tools The split stator core structure of the motor allows it to be smaller and lighter without compromising its ability to handle increased power output. This feature enables products that use the motor to maintain their performance while becoming more compact and lightweight. Alternatively, the motor can be used to enhance the product's performance without increasing its size. Furthermore, the motor's high-function control system allows it to adjust its performance based on the load. For instance, it can control the number of revolutions or stop according to the load. This capability enables the addition of new product features, which can lead to increased functionality and versatility. Additionally, the motor's robustness against water and dust makes it suitable for products used in harsh environments, such as outdoor settings. This feature enhances the durability and reliability of the product and extends its lifespan. The technology owner is keen to do R&D collaboration and licensing out the know-how to a variety of applications developers such as robotics, electric vehicles, and industrial automation systems.    brushless DC motor, compact motor, vector control, load detection, split stator core, waterproof motor, dustproof motor, power tools Electronics, Actuators, Power Management

Monitoring of contaminants in fluids often require capital-intensive machinery and sampling comes at a hefty price tag. With the advent of tightening regulations across various industries including environmental and food industries, there is a need for a more cost-effective and efficient method to meet the growing demands and regulatory requirements in the market. Molecular Imprinted Polymers or MIPs are one such sensor technology that can potentially address this challenge. MIPs are synthetic materials that are designed to recognize and selectively bind to specific molecules, similar to the way antibodies recognize and bind to antigens. MIPs can be engineered to bind to a wide range of analytes, including organic and inorganic molecules, peptides, proteins, and even whole cells. The unique feature of MIPs is that they possess high selectivity and sensitivity for the target molecules, making them ideal candidates for designing high-performance sensors. This technology relates to a cost-effective online monitoring system using MIPs technology to detect trace levels of chemical and biological contaminants on-site in the fluid phase with low interference, high accuracy, and sensitivity. The automated real-time monitoring system requires little supervision and can be easily operated. The robust sensor is designed for long-term operation and requires minimum maintenance without compromising the reproducibility and integrity of the data. This technology allows monitoring can be applied in industries such as agriculture, food, chemical processes, environment monitoring and waste management. The technology provider is seeking partners that are interested in co-development, R&D collaborations or licensing. This technology is primarily based on the mass change and energy dissipation from the analyte adsorptions and interactions on the sensor chip, which gives a piezoelectric effect and delivers real-time, high sensitivity, and high selectivity data. The entire sampling and analysing process is automated. Key features include: Shortened analysis time  (<10 mins) compared to conventional sensors (30 - 45 mins) High accuracy, and sensitivity (ppb level detection) Real-time and online monitoring Label-free, non-toxic, and environmentally friendly sensing process Regenerable sensor chips Modular designs Automated system Heavy metal detection Pesticide residue detection Endotoxin detection Wastewater treatment and resource recovery Water quality monitoring in water bodies The manufacturing process and water monitoring regulations are becoming increasingly stringent. The global water quality monitoring market has a CAGR of 6.5% from 2020 to 2027, showing the potential commercial gains from such sensors. As more and more substances are required to be monitored, users can find convenience and cost savings from having a sensor that is able to detect multiple target molecules.  Proprietary algorithm to overcome interferences  Cost-effective (per sample basis: 5 SGD  vs. 15- 25 SGD sensor, MIPS, monitoring, water Foods, Quality & Safety, Environment, Clean Air & Water, Sensor, Network, Monitoring & Quality Control Systems

The sustainable urban farming concept is growing rapidly, and Singapore is progressing well towards it.  The heating, ventilation, and air conditioning (HVAC) system accounts for more than 50% of the total energy used in an indoor agricultural farm, according to data on energy use. Technological advancements can help to address energy reduction and improve the productivity of indoor farms. Low energy-based concepts can be implemented by mainstream farm owners in Singapore to increase farm productivity and serve the increasing market demands directly.  This technology offer is a Low-Energy (Low-E) HVAC system for farming. It can cool, heat, dehumidify and ventilate any indoor space using up to 100% outdoor air exchange. It is able to achieve and maintain the optimum cooling, drying conditions, and sufficient level of carbon dioxide that are needed for farming with lower energy consumption. The operating cost of the Low-E HVAC fitted grow room is 35% to 37% lower than the conventional HVAC system for the same application. The technology owner is keen to do R&D collaboration and test-bedding with potential indoor agricultural farm owners.    The main features of this technology offer are:  35-37% energy reduction compared to conventional system 60% reduction of integrated airborne particle concentration of PM1.0 particulates Combined cooling, dehumidification and fresh air ventilation processes with up to 100% outdoor air exchange Unique Low-Energy (Low-E) HVAC system, eliminates the need to use separate equipment for each process  Using computational fluid dynamics (CFD) method to maintain optimum cooling, drying conditions, and sufficient level of carbon dioxide to resist growth of mould, mildew, and potentially hazardous organisms. Portable, modular, and scalable assembly for different sizes of application   The technology offer can be deployed in the following applications: Urban agriculture – farming and gardening Greenhouses/outdoor enclosed farms Enclosed incubation and isolation area  Medical / scientific laboratory for sample preparation and storage  The system is also scalable and customisable for bigger application areas.       This technology offer is a novel low-E HVAC system with:  100% outdoor air exchange to ensure the undisrupted supply of carbon dioxide and oxygen for plant growth and maturity  40% to 60% drying conditions within the grow room with lower energy consumption compared to the conventional HVAC system. Computational fluid dynamics (CFD) simulation method to ensure uniformity of air distribution. Capable of achieving 35 to 37% lower electricity compared to the conventional HVAC system Portable, modular and flexible setup for both indoor and outdoor growing and can be adjusted even during operation The technology owner is keen to do R&D collaboration and test-bedding with potential indoor agricultural farm owners.  low energy hvac, urban farming, greenhouse, climate control, low operating cost Environment, Clean Air & Water, Mechanical Systems, Green Building, Heating, Ventilation & Air-conditioning, Indoor Environment Quality

The rise in health consciousness has accelerated the development of sports wearable devices. Currently, most common sports wearables are physiological indicators for monitoring vital signs (e.g., heart rate, blood pressure, SpO2, etc.) and metabolites (e.g., glucose, pH, lactic acid, etc.). However, these devices cannot quantitatively analyse the force-generating process. The existing kinematical indicators monitoring posture and motion also have limitations, such as poor wearing comfort, low sensitivity, and weak capacity for real-time data analysis. The technology is an ultra-thin microfiber strain sensor that has superior elasticity, durability, and sensitivity. Using this proprietary technology, the technology owner has developed a comfortable fabric wearable to monitor muscle activities during sports and rehabilitation. By incorporating machine learning algorithms, more than 15 data metrics are being analysed in real-time to accurately characterise sports performance, optimise training standards, and prevent fatigue or injury. This technology is available for licensing and R&D collaborations with partners in the sports, fitness, healthcare, and rehabilitation areas, e.g., sportswear and smart wearable companies, gyms, healthcare providers, sports training institutes, etc. The technology owner has developed a full technology suite for sports monitoring, consisting of the following modules: 1. Wearable Band: Fabric band woven with a microfiber sensor capable of tracking motions, forces, and pressure Lightweight and comfortable band with similar dimensions to a smartwatch (< 35g) Highly stretchable sensor to be stretched to more than 200% of its original length Wireless transmission unit to provide real-time Bluetooth data transmission to the mobile app Utilises a rechargeable battery capable of lasting more than 7 hours upon fully charging 2. Mobile User App: Ready App for Android and Windows PC Home screen with multiple functions: Select the type of training: workout, power, time, etc. Track the history of previous workouts Sensor calibration to ensure accurate tracking and analytics 3. Cloud Server (Al / ML): Derive more than 15 data metrics, e.g., muscle expansion/contraction, speed, power, range of motion, workout consistency, fatigue level, muscle stability, etc. Machine learning algorithms to evaluate the user’s health profile and provide recommendations The potential applications include but are not limited to: Sportswear (sports apparel, smart socks, footwear) Wearable devices (smart watches, smart glasses) Training equipment (gym armbands, intelligent coaching systems) Training institutes (athlete training, sports schools, military) Lightweight and comfortable Washable sensor allows for regular laundering Superior sensing performance (fast and accurate response) In-depth data analysis to characterise sports performance Machine learning to provide intelligent recommendation This technology is available for licensing and R&D collaborations with partners in the sports, fitness, healthcare, and rehabilitation areas, e.g., sportswear and smart wearable companies, gyms, healthcare providers, sports training institutes, etc. Sports Monitoring, Fitness and Healthcare, Microfiber Strain Sensor Materials, Plastics & Elastomers, Electronics, Sensors & Instrumentation, Infocomm, Artificial Intelligence

Recently, the rising adoption of Internet of Things (IoT) devices and portable electronics has made electronic waste (e-waste) pollution worse, especially when small and low-power IoT devices are single-use only. As such, low-cost and environmentally friendly power sources are in high demand. The technology owner has developed an eco-friendly liquid-activated primary battery for single-use and disposable electronic devices. The battery can be activated by any aqueous liquid and is highly customisable to specific requirements (i.e., shape, size, voltage, power) of each application. This thin and flexible battery can be easily integrated into IoT devices, smart sensors, and medical devices, providing a sustainable energy solution for low-power and single-use applications. The technology owner is keen to do R&D collaboration and IP licensing to industrial partners who intend to use liquid-activated batteries to power the devices. The technology is a single-use and non-rechargeable battery that can be instantly activated by any aqueous liquid (e.g., water, fruit juice, soft drink, etc.) as well as all types of body fluids (e.g., blood, saliva, urine, sweat, bile, etc.). The features of this technology are: Customisable shape, size, and power (1.5 to 6.0 V at 4 to 50 mW) Ultra-thin and flexible (<1 mm in thickness) Lightweight (when dry) High energy density (less than 5 mm2 for low-power application: 1.5 V, 2 mAh) Indefinite pre-activation shelf-life (no self-discharge) Non-toxic and biocompatible (safe for human beings) Environmentally friendly (no disposal pollution) This inherently safe and non-toxic battery can be widely applied in MedTech applications, disposable IoT, smart sensors, and low-power electronics. The potential applications include but are not limited to: Medical devices: digital pills, ingestible sensors, smart bandages, wearable biosensors, in-vitro diagnostics (IVDs), body fluid testing, etc. Disposable IoT: Bluetooth Low Energy (BLE) chips, microprocessors, wireless sensors (pH, temperature, humidity), micromotors, LEDs, heaters, etc. Other low-power electronics: smart labels, electronic skin patches, cold chain monitoring, smart packaging, etc. The technology offers the following unique features: Highly customisable for different applications Thin and flexible (adaptable to various designs) Long shelf-life (can be sealed for a very long time) Biocompatible (can be safely consumed) Environmentally friendly and non-toxic The technology owner is keen to do R&D collaboration and IP licensing to industrial partners who intend to use liquid-activated batteries to power the devices.  Primary Battery, Environmentally Friendly, Non-Toxic, MedTech, Disposable IoT Energy, Battery & SuperCapacitor, Healthcare, Medical Devices, Infocomm, Internet of Things

Strength training is beneficial for a person's overall health and wellness. There is increasing demand for strength training used in rehabilitation aimed at restoring the day-to-day functionality of elderly persons. Currently, continual adjustment and improvement to the strength training and rehabilitation plan is carried out using feedback based on visual analysis. This maybe time consuming, and has to be based on the experience of the rehabilitation therapist.  This technology offer is a near-infrared spectroscopy (NIRS) technique used to detect the effectiveness of strength training. By using the technology, muscle oxygen consumption information can be acquired and mapped as a two-dimensional distribution without the need of direct skin contact. As such, it is possible to accurately evaluate the effectiveness of strength training on a site-by-site basis. In-vivo changes in oxygen concentration in muscles during strength training can be determined by detecting changes in oxyhemoglobin and deoxyhemoglobin. In this technology offer, these changes are presented by variations in amplitudes of refracted content of an incidental NIR light directed into the skin. This method of analysing the changes in intramuscular blood flow is effective for understanding the muscle condition during strength training, and hence can be used to determine the effectiveness of the training.  The technology owner is keen to out-license the technology to application developers from the physical training and rehabilitation industry.  This technology offer uses near-infrared spectroscopy (NIRS) to measure hemoglobin changes before and after training to detect effectiveness of physical training. The method:  uses the near-infrared region of the electromagnetic spectrum from 780nm to 2500nm.  does not need to have direct contact with the user's skin captures two-dimensional distribution of muscle oxygen consumption level detects surface scattering and internal scattering components uses precision shutter control technology This technology offer can be adopted in various industry such as: Physical education Training and rehabilitation  Medical and physiological diagnostics and research  This technology offer uses non-contact, near-infrared spectroscopy (NIRS) to measure muscle oxygen consumption in a targeted area of the muscle activity. It has a proprietary method used to trigger the electronic shutter to accurately extract the internal scattering of NIR light.  By displaying the measured oxygen consumption as a two-dimensional distribution, the operator can easily evaluate the effectiveness of muscle exercise over time. This method is efficient and removes the need for the operator to be experienced in visual evaluation of muscle condition; it is expected that this technology can be applied to various fields such as physical training and rehabilitation services. The technology owner is keen to out-license the technology to application developers from the physical training and rehabilitation industry.  physio, sensing technology, exercise, muscle Electronics, Sensors & Instrumentation, Lasers, Optics & Photonics

The solar energy industry is experiencing rapid growth and innovation, and machine learning is playing a key role in driving this trend. Solar energy plays a crucial role in the sustainability initiative providing a clean, renewable, and cost-effective source of power. The adoption of solar energy usage can help to address climate change, improve energy security, and provide access to electricity in remote areas. This growth is fueled by the increasing adoption of machine learning and artificial intelligence technologies, which are helping organisations in the solar energy industry to more accurately predict and optimise the performance of their solar panels. These models can effectively analyse images of solar panels to detect and diagnose issues such as microcracks, “snail trails”, broken glass, hot spots, dust build-up and other defects that may impact their performance. Building and deploying these models can be a complex process, requiring the use of multiple tools and a high level of technical expertise. This technology offer is a customisable end-to-end MLOps platform that is capable of streamlining the process and makes it easier for teams to build custom computer vision models specifically for solar energy monitoring and optimisation. With this platform, teams can quickly and easily convert their data into working models with enterprise-standard practices, ensuring the accuracy and reliability of their solar energy monitoring systems. The technology owner is keen to do R&D collaboration with organisations looking to improve and optimise the overall design and integration of solar energy systems.   The technology offer can help organisations improve the efficiency of solar panel systems by as much as 25%. It consists of the following features:  AI-Assisted Labeling - in-built annotating method with a mixture of contour analysis methods and deep-learning to label datasets with a few clicks per image with pixel-level accuracy. Image Augmentation - allows generation of synthetic variations of datasets directly in the platform to increase robustness. Multi Architecture and GPU Support - supports large data size that may require multiple GPUs to calculate gradients simultaneously.  Model Deployment & Active Learning - can be adopted in models built natively on the platform, on a fully managed GPU environment or edge deployment.  Works on 2D RGB Images (or converted from other spectrums) Supports polygon, bounding box, and mask labels Exportable to major annotation formats e.g. COCO JSON, LabelMe, PascalVOC, COCO MASK, CSV Width-Height, etc Supports model training with State of the Art models such as MaskRCNN, DeepLabV3 with "One-Click Train" feature Evaluation and Report Generation - to generate detailed evaluation result and statistical analysis of the model that can be included as part of the publication or technical specification sheet. The technology offer can be used for a variety of use cases in the solar energy industry, including: Building custom ML model to continuously monitor solar panels to identify and diagnose any issues affecting efficiency, such as power degradation, hotspots, and shading. Developing predictive maintenance models to proactively address potential problems before they occur Analysing images of solar panels to detect cracked cells, microcracks, hot spots, dust build-up, broken glass, and other defects Optimising the placement and orientation of solar panels to maximize energy production Developing a monitoring system to detect when a junction box is faulty, providing alerts to maintenance teams to take action. Addressing the challenge of low power production efficiency caused by “Snail Trails” by automating the detection and remediation of micro-cracks   The technology offer helps a wide range of demographics in helping improve the efficiency of industrial application developers, deep-tech problem solvers, and researchers. It improves the development cycle by enhancing in-house capability to custom-build computer vision models that are robust and production-ready. Using this technology offer, the collaborators can enhance both speed and cost benefits when developing computer vision capabilities. Active learning methods can further increase model accuracy over time. The technology offer is designed to elevate the capabilities of AI companies in the Solar Panel industry by providing cutting-edge integration and advanced technology for image processing by streamlining data analysis, allowing AI algorithms to quickly process and analyse both IR (Infrared Spectrum) and Photovoltaic (PV) images with speed and accuracy. This enhances the accuracy of AI algorithms and reduces the risk of errors, leading to more effective maintenance and optimisation of solar panels. The advanced image processing capabilities of the platform drive innovation in the Solar Panel industry and allow AI companies to develop new and more advanced algorithms, resulting in improved performance, cost savings, and greater efficiency.  The technology owner is keen to do R&D collaboration with organisations looking to improve and optimise the overall design and integration of solar energy systems.  solar panel, energy management, predictive maintenance, machine learning, computer vision, image processing Infocomm, Video/Image Analysis & Computer Vision

Traditional traceability technologies often rely on barcodes, QR codes, and holograms on external packaging. These methods are always more susceptible to both intentional and unintentional removal or tampering. This technology offer is a patented innovation that uses natural food ingredients as a unique bio barcode tag for identification. Tags can be added directly as a powder or liquid to products for batch tagging. The technology helps to prove compliance by offering tamper-proof assurance from raw material and hence improves the supply chain integrity by preventing counterfeiting, product dilution, and cross-contamination; at the same time, the tags protect brand value, and transparency as well as establish brand recognition. The technology provider is interested to do test-bedding with food ingredients companies, FMCG companies, agri-food growers, and trading companies who are concerning traceability in their value chain. The technology covers life science, food technology, and bioinformatics sciences. The properties of the tags are as follows: natural, food-grade and patented DNA-based unique identifier safe-to-eat, tasteless and invisible highly resistant to temperature and chemical conditions in the food processing as lasting as the shelf life of the product to which they are added can be detected through PCR, and obtain the individual traceability reports in 2hours can be integrated into the existing barcode labelling, RFID and blockchain system It ensures forensic traceability resulting in higher standards of food safety, quality control, responding to customer complaints and protecting the company’s reputation. Potential applications of this technology offer include (but are not limited to): -             Food and beverage products (plant-based meat, alcohol, coffee, palm oil, etc.) -             Cosmetics -             Fragrance -             Personal Care -             Pharmaceuticals Compared with existing technology, this patented technology is a food-grade ingredient, applied in minute parts-per-million quantity and can be added to the product without affecting the taste or texture. This gives a tamper-proof solution that could potentially solve the traceability issues and protect the brand reputation as well as the product integrity at the same time. While the ingredient is food-grade and applied in minute parts-per-million quantity; the technology provider continues extensive work with food regulatory experts familiar with Australian, US, Europe, UK and Singapore food regulations ensure the compliance of their products.   The technology provider is interested to do test-bedding with food ingredients companies, FMCG companies, agri-food growers, and trading companies who are concerning traceability in their value chain. Personal Care, Fragrances, Nutrition & Health Supplements, Foods, Ingredients, Quality & Safety, Processes

There is a proliferation of health-tech wearables in recent years as the healthcare paradigm shifts from discrete monitoring in a hospital to continuous monitoring at one’s convenience. However, regular change of batteries and power outlet charging are often the pain points of using these wearables. Moreover, electrical charging points may not be readily available, especially when the user is in an outdoor environment for prolonged periods e.g. field trips that stretch for a few days. For these wearable devices to be powered for uninterrupted usage, there is a need for a constant source of external energy supply. Ambient energy can be harvested from the body's activities and serve as a reliable external energy source for wearables and portable electronic devices. As this energy source is readily available, energy sustainability can be achieved for the electronics and sensors in wearables and portable devices. However, it remains a technological challenge to develop such energy-harvesting devices.  This technology offer is a 2-D non-resonant energy harvesting method using hybrid energy harvesting mechanisms that can harvest energy from body movements. It can also be customised to harvest wave or wind energy, etc.  The technology owner is keen to do R&D collaboration, technology licensing and test-bedding with application developers intending to use motion energy harvesting solution to power devices.  The technology offer is a hybrid energy harvester that has a unique design configuration. It can overcome the following challenges of existing technology: Low, irregular frequency and amplitude generated by body movement, together with the limitation of parasitic damping and harvesting mechanism, often restrict the average output power of an energy harvester to a few microwatts, which is only sufficient to power up devices/wearables with ultra-low power applications. Kinetic motion harvesters are typically designed to harvest energy generated by motion in a specific plane of movement. However, human body movements are not constrained to any fixed planes. Thus, the energy harvested may not have reached optimal levels. The energy harvester, which is of 6cm (L) x 6cm (B) x 4.5 cm (H), is able to generate a power density of 4.8µW/cm3 at acceleration of 1g and frequency of 4Hz. It can be resized and scaled-up according to the application with customisable component selection.  Besides harnessing energy from human body motion to power wearables and portable electronics, the energy harvester could also be customised for the following applications to harness:  Blue energy by placing the energy harvester on a mass of water body to power offshore sensors used for monitoring environmental pollution and natural disaster etc. Ambient energy e.g. wind, to power wireless IoT sensor networks in remote areas, removing the need for regular battery replacement. Kinetic energy from the movement of non-living objects e.g. vehicle or roped elevator This technology offer has the following advantages compared to existing energy harvesters in the market: A hybrid combination of electromagnetic and triboelectric energy harvesting mechanisms allows for more energy to be harvested simultaneously from the same body movements. Increased dimensions of mass movements allow more energy to be tapped from different types of body movements. The design functions at a low-frequency regime (<10Hz) in non-resonant mode to fully harness the energy from human motion. Integrated energy storage and power management circuit allow energy harvested to be stored and managed, thus providing a complete package for product commercialisation. The technology owner is keen to do R&D collaboration, technology licensing and test-bedding with application developers intending to use motion energy harvesting solutions to power devices.  alternative energy, battery alternative, green energy, sustainable energy, renewable energy, blue energy, energy source, energy harvester, energy generator Energy, Battery & SuperCapacitor, Sensor, Network, Power Conversion, Power Quality & Energy Management, Electronics, Power Management, Sustainability, Sustainable Living