TECH OFFERS

This technology offer is a Ultrahigh Frequency (UHF) Radio-Frequency Identification (RFID) tag antenna for use on metal structures. 2 versions are available: A compact dual-band version with folded strip structure, with a total size of only 20 mm × 30 mm × 1.5 mm. This tag can be well used in different RFID systems, which work at different UHF bands, such as European and American frequencies. The reading patterns of this tag are with different directions in two bands. A single band version with a total size of only 10 mm × 30 mm × 1.5 mm. This tag can be well used in planar as well as conformal platforms, such as metallic cylinders and bearings. Automated factories should be interested in these tags, and they can use the miniaturized tags with RFID technology to intelligently detect whether the machinery and equipment are running normally.

This technology offer is an integrated, CMOS-compatible, compact device that provides dispersion compensation of dispersion in optical fibers. Dispersion impairments is a well-known problem in the transmission of high-speed data over fiber, that limits both the fiber reaches, or poses lower limits on the power required. The technology developed allows a seamless, very low loss method for compensation of fiber dispersion, providing high magnitudes of dispersion for countering dispersion in optical fibers. Without dispersion compensation, signals are susceptible to degradation from optical fiber dispersion, with the extent of degradation worsening with longer fiber reaches. Without proper dispersion compensation, transmitted data will experience high Bit Error Rates (BER) at the receiver. This technology solves this important problem and increases the fiber reaches which may be served.  

Electron-beam lithography (EBL) is a form of maskless lithography tool that is widely used in nanofabrication due to its rapid-prototyping and high-resolution patterning capabilities. However, the patterning process employing EBL typically suffers from low throughput due to the patterning process of scanning across all designated pixels by a scanning focused electron beam. This technology introduces the use of plasma treatment to increase the patterning throughput for closed polygon structures in EBL process without affecting the resolution of the patterned structures, allowing the patterning efficiency of EBL to be enhanced by 50 times and above. This technology is potentially useful for manufacturers of beam lithography tool such as electron beam lithography (EBL) and focused ion beam lithography (FIB) to develop next generation lithography system for high volume fabrication equipment. In addition, this technology could also be useful in semiconductor and nanophotonic industry for rapid prototyping of photomask and photoreticle in the fabrication process which could help improve the manufacturing cost of photomask fabrication.

Leveraging on big data, businesses in the retail sector can increase their customer-centricity; by measuring customer engagement, footfall, dwell time, age and gender, businesses can gain data-driven insights into various metrics such as sales conversion rate and reveal the underlying relationship between sales, marketing, and in-store traffic. Such insights help to make sense of the reasons some retail stores outperform others and provide a valuable means of optimising marketing, product display and sales strategies. Understanding footfall data and queue times can also help to optimise staff allocation to avoid over or understaffing and enhance the overall customer experience (CX). This solution is a plug-and-play cloud-based solution for retail analytics through human behaviour analysis. The platform works with any Internet Protocol (IP) enabled camera that supports Real-time Streaming Protocol (RTSP) and is able to perform footfall counting, dwell time measurement, and engagement count on video footage that are sent over the Internet to the cloud-based platform, this allows it to readily provide an additional layer of intelligence on existing camera infrastructure and scales to the requirements of the deployment. It provides visualisation over a web dashboard, as downloadable executive reports, or through Application Programming Interfaces (APIs) to enable actionable business intelligence insights.

Due to social stigma surrounding Sexually Transmitted Diseases (STD), cost barriers, and lack of awareness, a large proportion of men suffering from male health issues avoid accessing in-person medical care, instead, many men turn to online sources such as search engines or discussion forums to seek help. This further compounds the problem as this failure to seek medical attention leads to delays in diagnosis and subsequent treatment, while misinformation and misguidance from the general public can be dangerous and life-threatening. This technology aims to address the gap between crowd-sourced diagnosis and primary healthcare practitioners through a fully anonymous, AI-driven mobile application screening tool that covers 90% of genital pathologies e.g. bumps and lesions, and certain disease and viruses, such as syphilis, herpes, Human Papillomavirus (HPV). This technology offer is Artificial Intelligence (AI) enabled mobile application that utilises a Convolutional Neural Network (ConvNet or CNN) deep learning algorithm equipped with custom-built network layers to screen for male health issues, e.g. genital warts, sexually transmitted diseases (STD) etc. Data augmentation techniques and synthetic data generation methods have been used to vary the dataset and increase and sample size for realistic model training and testing. The highly accurate model has an accuracy of 60-90% for most cases of STI/STDs.

The latest Singapore National Population Health Survey has reported a concerning diabetes trend. From 2019-2020, 9.5% of the adults had diabetes, slightly dropping to 8.5% from 2021-2022. About 1 in 12 (8.5%) of residents aged 18 to 74 were diagnosed, with an age-standardised prevalence of 6.8% after accounting for population ageing. Among the diabetes patients, close to 1 in every 5 (18.8%) had undiagnosed diabetes, and 61.3% did not meet glucose control targets. Prediabetes is also prevalent, with 35% progressing to type 2 diabetes within eight years without lifestyle changes. Untreated Type 2 diabetes can lead to severe health issues. Tackling this challenge requires a holistic approach, focusing on awareness, early diagnosis, and lifestyle adjustments for diabetes and prediabetes. Recognising the need for innovation to address this, the technology owner develops a cost-effective and non-invasive AI-powered solution, Blood Glucose Evaluation And Monitoring (BGEM), that detects glucose dysregulation in individuals to monitor and evaluate diabetic risks. BGEM allows users to track their blood glucose levels regularly, identify any adverse trends and patterns, and adopt early intervention and lifestyle changes to prevent or delay the onset of diabetes. Clinically validated in 2022, with a research paper published in October 2023, the technology is open for licensing to senior care/home care providers, telehealth platforms, health wearables companies, and more.

In Singapore, more than 30,000kg of okara are generated from soya milk and tofu production. Due to the high amount of insoluble dietary fiber and a unique, poignant smell of okara, it is often discarded as a waste product. Despite okara's low palatability, it is rich in nutrients. Therefore, the technology owner has developed a cost-effective formulation to include okara in feed for abalone. The formulation can potentially be adapted and customised for other aquatic species. The technology owner is seeking potential partners to license and commercialise the technology.

Many active ingredients in formulated products often suffer from degradation triggered by light, heat, mechanical stress or volatile loss, as well as incompatibility issues with other ingredients or excipients. Encapsulation of actives could be a solution, however existing methods including nanoemulsion, liposomes, nanostructured lipids, spray drying involve undesirable steps that use organic solvents, surfactants, alcohols, non-biodegradable polymers and high shear processes. These undesirable steps render difficulties for economical scale-up.   The technology provider has developed a novel method for producing a biodegradable polymer that is based on green chemistry and easily scalable. Through their simple and novel nanoencapsulation process, the technology allows the encapsulation of most actives at submicron scale to form water-based formulation without the forementioned undesirable steps. This technology presents a low-cost, scalable co-block amphiphilic biodegradable polymer-based nanoencapsulation that is of superior performance and stability due to its polymeric chain entanglement and nano-sized effects.   The technology provider is seeking collaborations with partners, including  actives manufacturers and formulated products owners, who may have interests to adopt this encapsulation technology for hydrophobic actives in applications including insect repellents, pesticides, skincare, aromatherapy products, and pharmaceutical applications.  

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.