Healthcare is moving towards a self-management and prevention model, fuelled by limited healthcare resources, associated rising costs, and greater consumer awareness of health and lifestyle. The recent Covid-19 pandemic has also highlighted the need for homes to facilitate lower acuity care and for patients to be assessed and advised remotely. However, current medical technology is primarily designed for professional use in hospitals and is typically too complex and costly for patients to use at home. An Australian smart wearables startup has developed an innovative medical device platform utilising technology such as proprietary sensors and machine learning algorithms, and chatbots/avatars, and is intuitive to use. The technologies are weaved into a form of comfortable clothes which can be integrated into users’ daily lives for easy monitoring of health status. The technology platform is particularly suited for use in low care settings such as prohabilitation, rehabilitation and patient compliance. The startrup is looking for partners from community hospitals/step-down care, hospitals, pet, space, and defence industries.

The company offers a state-of-the-art hybrid communication technology which combines immersive and collaborative software functionalities. The technology is based on ten years of research around the European crisis management. Its specificity is to display any type of data on a collective visual space to facilitate decision-making.  Complex projects or tasks which requires complementary experts and heterogeneous data for display could be unified through this technology platform. The technology allow teams to simultaneously share and visualize data (e.g., screen sharing, pdf, images) to grasp the big picture as well as highlight and annotate the digital information to ensure a common understanding. 

Non-iterative Simultaneous Localization and Mapping (NI-SLAM) is a patented method for position tracking and environment dense reconstruction, using affordable sensors such as depth camera and inertial sensors. Compared to traditional SLAM methods, the superior real-time processing speed of NI-SLAM is achieved by an innovative method of data registration that performs point-cloud matching in Fourier Domain.

The company has developed a data analytics and machine learning platform technology that could be customised and scaled for specific needs in the utility and industrial asset management space. The company possesses not just technology expertise in data science and machine learning but also domain expertise in the energy and utility sectors. The technology is developed upon an inhouse Internet of Things (IoT) platform that can be deployed in less than 24 hours.  Understanding that each company would have specific requirements, the technology is therefore built with customization. While almost every aspect of the system can be customized, the company primarily offers two types of customization – dashboard customization and algorithmic customization. Dashboard customization is a front-end customization that involves data manipulation for visualization. Algorithmic customization can be machine learning algorithm, mathematical algorithm, or process algorithm. The company does not operate in a “define and build” methodology as they believe in the importance of customer success. They work with customer on the agile methodology and allow customer to modify the project requirements on the get go. The development work does not usually end at the stage, as the company would still work with customer on regular basis to understand how they can be better served. 

An A*STAR spinoff with 5 years and millions invested into R&D, is seeking technology partners for the Eureka Clusters Artificial Intelligence (AI) Joint Innovation Projects. We measure emotions on facial expressions through their algorithm to deliver real time, non-intrusive analytics for various industries. Only one in the world using psychology circumplex model resulting more precise emotion measurements vs 7 basic emotions in the market Enable Real-time processing and analysis for large crowd and individual emotional state. Only individual Single analysis from competitors. Awards winning technology that account for cultural differences with high accuracy especially in Asia emotion Solutions include APIs, SDK, Apps, Cloud platform, Edge/Raspberry Pi Industry verticals used with emotion A.I include: Retail & Hospitality Selves and POS Emotion survey, guest services/butler/concierge measurement. Human Resource Candidate emotion pre-screening analysis and aptitude testing or training Fast-Moving Consumer Goods FMCG Unbiased genuine emotion feedback, Market research and focus group analytics Emotion insight into A/B testing & packaging Healthcare Emotional enabled devices, health companion, remote measurement via telemedicine. Point of interest Emotional insights into visitors in public attractions, reaction to museum artefacts Smart Cities and security Infuse emotion recognition into IoT for Perimeter Security, Access Control, Strategic Sites, Airport Security, Border Control, Sensors & IoTs, Mega Event Security Smart devices / Appliances Humanise devices to be interactive, empathetic and emotion enabled home devices Automotive Fatigue / frustration detection to reduce diver risk, Taxi passenger analysis on in-car ads Education Assist teaching on content receptiveness online, Mood-meter for classrooms or exhibitions.

One of the leading transport & logistics companies with hubs in Singapore is looking for technologies to automate its warehouse kitting process.  In Singapore, its storage consolidation and distribution hubs offer a one-stop logistics solution designed to support a wide spectrum of industries.  The company currently faces the following issues: Turnkey processes consist of multiple manual steps to cater to different customer needs which involve a wide variety of combinations of items for assembly  Each customer’s requirements vary due to different/unique product packaging designs, and there are over 100 combinations of items for assembly Customers also have varying order patterns due to urgency and periodic surges (i.e. product launches). Typical batch of production vary from 3000 to 20,000 pieces per job type with an average around 8,000 pieces per job type. The company is seeking technologies/solutions that can address the following objectives: Reduce production cost Increase workshop capacity (per sqm) Identify work step process of manual activities for process improvement   

Anti-viral technology for packaging would be a significant step forward in increasing consumer confidence when purchasing and handling consumer goods packages. The increasing potential for viral contamination is forcing consumers to be wary of handling products that may have been handled by store personnel or other consumers. Anti-viral packaging technology would allow consumers to confidently choose those products with the least risk of further contamination and eliminate any need for package clean-up when arriving at home.  To offer solutions to consumers’ rising technical and emotional needs, a company is looking for technologies that can be applied to direct food contact packaging, both flexible and rigid, capable of reducing or eliminating viruses and other external pathogens on the packaging surface. 

A company is seeking to develop a new epoxy solder paste, with improved performance compared to conventional solder, for feature size <100µm. This new epoxy solder paste is expected to be implemented in applications such as mini/micro-LED, advanced packages SiP, automotive. While existing conventional solder paste technologies is being used in various applications today, they have limited performance in terms of drop test, die shear and adhesion. It gets more challenging when dealing with very small interconnect applications. For example, tin bismuth (SnBi) alloy has been widely used in low temperature reflow applications, but the brittleness is a concern for reliability. The company is thus seeking potential partners to develop a novel epoxy solder paste, as a joint reinforcement paste, that can improve the performance of small feature size (<100µm) applications. The company is open to various modes of collaboration and would like to partner with technology owners that are open to develop their existing technologies based on their requirements.