innovation marketplace


Discover new technologies by our partners

Leveraging our wide network of partners, we have curated numerous enabling technologies available for licensing and commercialisation across different industries and domains. Enterprises interested in these technology offers and collaborating with partners of complementary technological capabilities can reach out for co-innovation opportunities.

Invisible Product Authentication and Anti-Counterfeit Technology
Active brand protection is important as the globalisation of supply chain and ecommerce growth has made it easier for counterfeit goods to be introduced and sold to unsuspecting customers. This technology provides a simple and cost-effective solution for companies offering business-to-business products in high and low volumes to effectively identify counterfeit goods and safeguard their brand.   Using advanced luminescent nanomaterials, this technology combines the use of such materials with a hardware and software to provide a highly secure product authentication and anti-counterfeit solution. The proprietary nanomaterial can be customised to provide a unique signature and effectively layered overtly (visible) or covertly (invisible) on security elements to be printed on labels, packaging, products and/or embedded into raw materials for extrusion processes. It is compatible with water-based, solvent-based or UV inks to undergo gravure printing, screen-printing and flexographic printing.   The technology owner is interested in new product development collaborations and research and development opportunities, in particular for use in masterbatch and textile fibres.
Autonomous Materials Handling System
This technology offer presents an autonomous materials handling system. The technology could reduce manual labor requirements and increase working efficiency. The solution consists of a Lidar Elevator Stand (LES) system, which will trigger the autonomous actuators (e.g., trolley puller, tray return robots) via the robot command center whenever no goods (e.g., trolley, tray, and stock) is detected in the designated area. Currently, the technology has been demonstrated in autonomous trolley return solutions. Generally, trolley replenishment requires deploying manual labour to monitor the available quantity at the trolley bay and replenishing it by physically operating an electric trolley puller to transport the new stack of trolleys. Therefore, the system was developed to solve the problem by triggering an autonomous trolley puller to replenish the new stack of trolleys whenever the trolley quantity is depleting. The system can be further customized and repositioned based on clients’ requirements.
Universal Serum-Free Growth Media Designed to Support Multiple Cell Types
The current growth media used for cultured meat and biomedical research involves the use of animal-derived ingredients such as Fetal Bovine Serum (FBS). FBS is the liquid fraction harvested from the blood of cow fetuses which largely contributes to the high cost, ethical concerns and food safety aspects in the cultivated meal industry. Other commercial serum ingredients used to support cell growth are equally expensive and tend to have poor batch-to-batch consistency. Serum-free replacements that are alternative to FBS are expensive and they do not perform similarly across the range of different animal cell lines. This technology consists of a serum-free growth media produced under food-safe ISO22000 standards. This serum-free growth media is formulated to allow proliferation of muscle, fat and connective tissue consistently and efficiently, hence eliminating the need of multiple serum-free growth media for different cell types. Food-grade and animal component-free cell adhesion solution has been developed to complement and boost cell attachment and proliferation. It is more cost-efficient than commercially available serum-free replacements. Media development companies, companies and research institutes growing human cells for biomedicine purposes or animal cells for cellular agriculture could benefit from this technology. The company is looking for R&D collaboration with industrial partners who are keen to adopt the solution.
Estimated Time of Completion (ETC) Prediction for Last-Mile Logistics
The proliferation of e-commerce, ride-hailing and food-delivery services have fueled the need for more accurate and reliable estimation of delivery times. The current common estimation of delivery time is based on Estimated Time of Arrival (ETA) which relies on route distance that is calculated between the origin and the desired destination. It only considers the duration from pick up to drop off, and does not consider the additional time needed for preparing and offloading the goods. This technology offer is a Machine Learning (ML) model that is able to calculate the stop duration (job completion duration), which together with the ETA, provides the Estimated Time of Completion (ETC). This ML model is for Singapore use only.
Phytonutrient-based Remedial Fluid for the Management of Hypertrophic and Keloid Scars
After a skin injury or surgery, a scar may form as the wound heals. In this body's repair mechanism, the myofibroblast cells produce new collagens and they form an extracellular matrix (ECM) to repair a wound. Over time, most scars become flat and pale. However, in some abnormal cases, the body produces excessive collagens. The excessive ECM formation and deposition of these scar tissue will result in raised scars such as hypertrophic scar and keloid scar. These raised scars may leave lifelong marks on the skin. Although the raised scars are not dangerous or life-threatening, they create aesthetic concern, restrict physical movement and may also lead to itching, tenderness, pain or even depression and anxiety. The currently available scar removal products such as silicon patches and topical products may cause skin irritation, which has led researchers to look for safer and more effective solutions. The present technology is a series of phytonutrient-based remedial fluids, which can be used as a general topical agent or complemented with a nano sprayer for the management of raised scars. The product developed from this technology is a safe, non-invasive and convenient approach to suppress hypertrophic and keloid scars. The technology provider is looking for collaboration opportunities to co-develop skincare products incorporated with this series of plant-based remedial fluids for scar management, collaborators for conducting clinical studies to evaluate effects of the current prototypes as well as other partnership mode including IP licensing. 
Sub-Skin and Gut Microbiome Health Analysis by Smartphone App
Conventional diagnostic imaging of the skin involves the use of dermatoscopes. Dermatoscopes use skin surface microscopy to examine dermal and sub-dermal tissues to diagnose skin problems. However, these devices can be costly and provide a limited view of the immediate skin surface. This limitation meant that dermatoscopes have to be used in direct contact with the patient's skin. Because of this, they can only be used to image patients in the same physical location as the clinician conducting the examination. The overall result is that only a tiny portion of the global dermatology patient-base can be reached cost-effectively and efficiently. Telemedicine and telehealth network operations are rapidly developing ways to address patients broadly and at lower costs for them and their care providers. Yet, such tools neither deliver desmatoscope-like functionality nor improved it in way that it allows patients' skins to be examined and analysed during an online medical consultation with a general practitioner. In order to facilitate remote skin disease diagnosis, the use of software is required to acquire and share images in real-time and ideally, by the patients themselves. This software enables patients to take their medical sub-skin images with their mobile, tablet or laptop cameras, and securely share it with doctors. Crucially, dermatoscopy images can also be used with the technology to improve diagnostic accuracy. This technology is intended to position itself as a technology which when scaled-up, could allow for products that can enable optical biopsy and phototherapy. 
Real Time, All-day, Stress Monitoring System Using Data Science
There are 30,000 occupational drivers in Singapore, out of which 13,500 are 45 years old and above. The risk of acquiring cardiovascular disease increases with age and is potentially exacerbated by low physical activity and high emotional stress levels, which are two typical characteristics of occupational drivers arising from their work environment. Low level of physical activity and high stress levels have been shown to have significant relationship with heart rate variability, one of the indicators of cardiovascular disease. This technology is developed to help drivers to monitor their stress level, provide them with instantaneous feedback and the necessary alerts for a timely intervention. This technology offer presents a cross-platform AI system that estimates the stress levels continuously in real time, and can be easily integrated with commercially available photoplethysmography (PPG) wearables, e.g., a PPG wristwatch. In addition, this technology can be adapted for the monitoring of workplace stress with the aim of improving overall mental well-being.
Improving Explainable Artificial Intelligence For Degraded Images
One use of AI, including deep learning, is in prediction tasks, such as image scene understanding and medical image diagnosis. As deep learning models are complex, heatmaps are often used to help explain the AI’s prediction by highlighting pixels that were salient to the prediction. While existing heatmaps are effective on clean images, real-world images are frequently degraded or ‘biased’-such as camera blur or colour distortion under low light. Images may also be deliberately blurred for privacy reasons. As the level of image clarity decreases, the performance of the heatmaps decreases. These heatmap explanations of degraded images therefore deviate from both reality and user expectations.  This novel technology-Debiased-CAM-describes a method of training a convolutional neural network (CNN) to produce accurate and relatable heatmaps for degraded images. By pinpointing relevant targets on the images that align with user expectations, Debiased-CAMs increase transparency and user trust in the AI’s predictions.
Enabling Interpretable Sorting Of Items By Multiple Attributes
Lists are an indispensable part of the online experience, often used to show many results, such as products, web pages, and food dishes. These items can be neatly sorted by a desired attribute like price, relevance, or healthiness. Listed items often have multiple attributes. However, instead of being able to sort multiple attributes simultaneously, consumers are currently limited to sorting only one attribute at a time. This makes searching for the desired item tedious and confusing. Imma Sort supports interpretable and multi-attribute sorting. Sorting for two or more attributes is possible. In contrast to existing search technology, Imma Sort trades off the smoothness of the sorted trend for the main attribute to increase ease of prediction for other attributes, by sorting them more approximately. Results for specific attributes can be made smoother by setting higher importance weights.