Some applications where a mobile robot or a handheld tool is moved through a large workspace require sub-cm positioning or localisation accuracy, which cannot be achieved with conventional methods based on LiDAR, ultrasound or ultra wideband (UWB). While motion capture systems and robotic total stations could achieve the required accuracy, their integration is often not feasible due to high cost (starting over 15k USD), deployment effort and difficulty of use, especially in field and ad-hoc applications. The technology offer is a system that can bridge this gap and is easy to integrate and set up, highly automatic and affordable.

Our technology makes it possible to build intelligent personal assistants for online information processing. The intelligent personal assistants can search, extract, structure and monitor the information in online networks and media. The technology also allows to detect target patterns in electronic communication networks providing an increase in the efficiency and in the comfort level of the end users and corporate employees.

Accurate, photoplethysmography (PPG)-based vital signs measurements can be done using smart hearables. Our approach uses proprietary algorithms and multiple photodiode/sensor pairs to effectively remove motion artifacts. As such, accurate bio-signals can be obtained dynamically under motion, and in a continuous real-time manner. By removing the motion noise instead of using accelerometer-based compensation techniques, we can preserve very detailed raw information that can in turn be used to compute other bio-signals including, respiratory rate (RR), heart rate variability (HRV), and R-R interval (RRI). With these parameters, sleep apnea detection can be done using our smart hearables, in a non-invasive, continuous real-time manner. Upon detecting sleep apnea episodes in users, the smart hearable can issue an audible instruction to wake them up, thus allowing the user to readjust their sleep posture. This can potentially be a useful home-based sleep apnea monitoring tool.

The capsule endoscope (CE) has revolutionised gastrointestinal (GI) tract inspection. Traditional endoscopy requires a camera on the end of a cable to be inserted into the patient, with understandable anxiety prior to the procedure, additional risk during the procedure, and considerable discomfort both during and after the procedure. In contrast, CEs are pill-like miniature cameras, taken orally like any pill medication in an easy and angst-free manner, prior to travelling through the body and imaging the GI tract with minimal discomfort. Using these images, clinicians can make routine diagnoses of a range of diseases, including bowel cancer, Crohn’s Disease and ulcerative colitis, to name a few. However, CEs travel through the digestive system in a passive manner. This limits the utility of the device in terms of speed, positioning and overall control. Therefore, a capsule endoscope capable of locomotion has been developed by our researchers. Using impact forces, friction in the GI tract is overcome and allows control over speed and positioning when inspecting the GI tract. Further, the underlying locomotion technology is likely applicable for delivery of other cargo, such as other miniaturised medical devices or drugs.

Smart packaging has emerged as a potential solution to consumers to track the usage of a product. By collecting the data (e.g., volume, temperature, weight) from the sensor and wirelessly transmitting the measured data to a processing unit (e.g., mobile phone), the usage and quality of a product can be analyzed. The analyzed data can provide several information to the users, such as when to replenish the product, the effectiveness of a medicine and when the product is used. The Singapore company aspires to be the market leader in Smart packaging offering an integrated intelligent connected packaging label solution for fast-moving consumer goods (FMCG), Food and Healthcare products. Currently, fakes products are prevalent in both online and offline space. The ability to authenticate products are crucial for both consumers’ welfare and companies’ revenue. This is especially so for food related products. The company is currently providing solutions to help companies in S.E Asia and China on Brand Protection and Product authentication to prevent loss revenue due to counterfeit, track supply chain and engage consumers. The company believes in 2 broad future trends – (1) Product Authenticity and (2) Internet of Things (IoT). They are interested in technology that can be incorporated as intelligent packaging where a smart label on product packaging is engage consumers and help to track product consumption by the user. The company is seeking a wireless electronic tag that can be easily integrated or attached on a packaging and able to capture the usage and frequency of the consumption of products, such as milk powder, drink, medicine.   Use case for intelligent packaging label: A smart label is applied onto a healthcare supplement product. The label outside the packaging will automatically track how much supplement is left on the bottle and provide alerts to the consumer’s smartphone. It can be integrated to seller’s stores for delivery with a button. The sellers can also receive notification on real time consumption levels in different locations and help to ensure sufficient supplies for replenishment to their customers. The company is on the lookout for suitable partners to create, develop or integrate intelligent technology with brand protection technology solutions to allow consumers to first authenticate product purchase and then monitor product consumption level.

We are working with an established ingredients manufacturer supplying the food industry with a range of oils/fats and proteins. The production of these ingredients can require extensive processing, high energy consumption, and the use of large quantities of organic solvents (e.g. hexane), all of which provide environmental risks. The food industry and its supply chain currently face the dual challenge of moving to more sustainable sources (requiring alternative sources of oils/fats and proteins that can provide similar yield/quality to products such as palm oil), whilst finding ‘greener’ methods of processing that don’t require the use of organic solvents and capital intensive processes. This shift to sustainable farming and processing is being increasingly demanded by more knowledgeable consumers keen to protect the environment and the long-term health of the planet and its occupants. The client has committed to extending and improving the sustainability of their operations and seeks innovative partners to enable this change. The client is therefore actively searching for partners with expertise in the mild (sustainable and/or solvent-free) processing of plant-based raw materials that could enable the future production of oils/fats and proteins suitable for the food industry. We are therefore interested to connect with start-ups and established companies that can demonstrate proof of concept at pilot scale and beyond, for technologies with the potential for production scale within 5 years (>100s of tons).

A catalyst's performance is typically strongly interlinked with its manufacturing method, determining properties such as crystal size, porosity, mechanical stability of formed shapes, homogeneity, morphology, crystallinity, etc. Thus, different properties to the formally identical, established products are expected. The technology seeker is keen to jointly explore if and how catalyst performance would be changed - for better or worse. They are open to explore technologies that can improve the production process and the resulting catalyst over the existing state-of-the art, for instance increased yield, increased quality, tuning relevant material properties, reduced cost, or reduced CO2 footprint and increased sustainibility of production. Typical materials which the company manufactures are zeolites, (mixed) metal oxides, and supported (precious) metals and metal oxides (supports typically are based on alumina, steatite, cordierite or calcium aluminate). Specific exemplary materials would be Cu/ZnO/Al2O3 (used for methanol synthesis), FeOx (used as catalyst precursor for ammonia synthesis) or Pd or Ni on alumina carriers (used e.g. for hydrogenation or dehydrogenation). The resulting catalysts are currently used for applications around synthesis gas (e.g. methanol production, steam reforming, ammonia production, water gas shift), petrochemicals (e.g. olefin production, aromatics, styrene, ethylene oxide), and specialties (e.g. emission control, off-gas treatment, gas purification, selective oxidation, hydrogenation, fuel upgrading). New methods that are relevant along the production of inorganic solids are of interest, for instance for precipitation, mixing, synthesis, aging, filtration, impregnation, coating, drying, calcining and heat treatment, as well as shaping and forming (i.e. tableting, extrusion and pelletizing).

We are a Singapore startup with core technology in AI-assisted image post-processing. Our technology is available as a platform and is in prototype stage. Our propietary algorithms allows us to quickly scan through images where our AI models will identify trained-for image indicators e.g., wear and tear of structures, building defects, annomalities. We are applying this technology in the Smart Building Inspection space for purposes such as periodic facade inspection (PFI). Our technology is able to process image output from drone inspections to quickly compile a report for building management or inspectors. The report will contain imagery representing 3D generated model of the building structure. Our team possesses personnel with the know-how and license to operate for drone flights. The team possess domain expertises in the areospace and marine industry, as such they are no strangers to structure inspections and will be able to provide an environmental scan to provide for a customised fit for the final outputted structure/building inspection report. Our AI platform allows for human-in-the-loop machine learning model training. By working with structure/building experts over a number of drone flights and inspections, we use their labelled data to train more accurate and precise machine learning models, to allow for a fully autonomous defects identification and generation of inspection report; from input of drone flight images, to output of report.