TECHINNOVATION TECH OFFERS

Social issues such as labor shortages are becoming more apparent, making it urgent to utilize digital technology to transform workflows and work styles. In particular, there has been increasing demand for spatial digitalization to streamline renovation processes across various fields. When renovating offices, houses, factories, and other spaces, it is necessary to measure dimensions and create floor plans, which often involves manual work. However, measuring all dimensions and generating floor plans or 3D models manually takes a significant amount of time. Moreover, overlooked measurements often require additional site visits, further delaying the process. Recently, spatial digitalization using sensors such as cameras has been introduced to address these challenges. By sensing spaces and generating point clouds, which are then converted into 3D models, efficiency can be improved. However, existing methods still present issues. Creating point clouds with desktop devices is costly and time-consuming. When using general mobile devices, the accuracy is low and results depend heavily on the operator. Furthermore, transforming point clouds into 3D models often requires extensive manual work and considerable time. This method addresses these challenges. Using low-cost mobile devices, anyone can quickly and accurately acquire point clouds, which can then be automatically transformed into 3D models within just a few hours.

This IoT and AI-driven solution directly addresses critical logistics challenges, including product spoilage, quality degradation, and compliance failures, particularly in cold-chain and high-value supply chain environments. Given that product spoilage alone costs companies 3–7% of their annual revenue, the technology’s core value lies in its ability to transform logistics management from a reactive process into a proactive and intelligent operation. The solution’s robust platform is built on three key technological pillars: An IoT sensor device for real-time data collection. An AI-driven predictive model for deep analysis. An integrated data management platform that unifies insights. This system leverages domain-specific data management to handle complex knowledge, ensures quick and accurate forecasts through advanced modeling, and dynamically adjusts risk thresholds in real time using AI-based risk management. By integrating these elements, the technology provides comprehensive visibility and enables timely intervention, preventing minor issues from escalating into major disruptions. Ultimately, this solution is ideally suited for sectors such as biopharmaceuticals, fresh food, and high-value asset transportation, where its accuracy and speed can significantly reduce operational losses.

The foveal machine vision method is a well-established human-eye-inspired technology that mimics the way our eyes focus on details in the centre of vision (the fovea) while keeping peripheral areas in lower resolution. The current invention applies this mature principle to capsule endoscopy, and by integrating attention-driven imaging, adaptive radios, and visual–inertial fusion, it delivers a uniquely efficient and clinically relevant solution for fewer missed diagnoses and improved patient outcomes. For clinicians: The system integrates seamlessly with existing PACS (Picture Archiving and Communication System) and EMR (Electronic Medical Record), requires minimal onboarding, and mirrors current reading habits. It streamlines the review process while ensuring clinicians retain full control by accepting or editing findings before making the final decision. For patients: The exam remains outpatient and sedation-free, with no disruption to daily activity, while improved targeting and localization help reduce the need for repeat procedures. This technology overcomes key limitations of current capsule endoscopy in gastrointestinal (GI) diagnostics — namely low image resolution (~500 X 500 pixels), slow frame rates (<5 frames per second), and excessive energy use — that can compromise lesion detection and often necessitate repeat procedures. Ideal collaborators include R&D partners to advance development, gastroenterology departments for clinical validation, device manufacturers for capsule integration and scaling, and telemedicine providers to enable remote diagnostic deployment.

Modern buildings consume significant amounts of electricity through air conditioning systems. However, many conventional setups rely on static schedules or simple rule-based controls that do not adapt to dynamic factors such as external weather, occupancy, or usage patterns. This often results in higher energy costs, reduced occupant comfort, and unnecessary wear on air conditioning equipment. To address these challenges, the technology owner has developed an advanced air-conditioning optimisation system that leverages real-time sensor data, weather forecasts, and machine learning to dynamically regulate operations. The system features intelligent temperature detection that maintains an optimal balance, neither too cold nor too hot, while automatically controlling air-conditioning and heating in real time, thereby improving energy efficiency, supporting ESG practices, and ensuring a consistently comfortable indoor environment. Designed for seamless installation and operation via a user-friendly interface, the solution is suitable for both small-scale users and large facilities managing multiple air conditioning systems. When integrated with central air control systems, it reduces manual workload for operators while optimising energy use across entire buildings. Successfully deployed in retail stores, offices, and warehouses in Korea, the technology has demonstrated proven value across diverse environments. The technology owner is seeking industrial partners for test-bedding and adoption of their AIoT solution. They are also keen to collaborate with HVAC companies and air handling unit (AHU) manufacturers to co-develop integrated solutions that create win-win opportunities and drive sustainable growth.

Reliable cold storage is critical for preserving food and pharmaceutical products, yet conventional refrigeration requires a stable electricity supply that is often unavailable in underdeveloped regions. Traditional passive evaporative cooling methods, while centuries old, are highly dependent on ambient humidity and temperature and lack consistent performance. This technology introduces a Portable Electrostatic Cooling Enhancer that enhances evaporative cooling using a low-power electrostatic generator. By generating a gentle ionic wind directed at an evaporating medium such as a hydrogel, the device significantly accelerates evaporation and boosts cooling power with minimal energy input. The cooling strength can be adjusted easily by tuning the electrostatic generator, allowing goods to be maintained at desirable sub-ambient temperatures even under fluctuating environmental conditions. Compact and energy-efficient, this innovation has the potential to support cold-chain logistics operators, food and grocery delivery platforms, and pharmaceutical distributors, particularly in regions with limited infrastructure. Its portability also makes it suitable for widespread adoption across supply chains, ensuring reliable access to fresh produce, medicines, and vaccines.

Conventional stirred-tank bioreactors (STRs) often expose cells to high shear stress from impellers, which can damage sensitive cell types like mammalian or stem cells and reduce viability by up to 20–30%. Their complex internal structures with baffles, probes, and impellers also make cleaning and sterilization challenging, with cleaning-related downtime reported to account for as much as 30–40% of overall operation time. This technology offers a novel bladeless bioreactor that achieves homogeneous, gentle mixing without impellers, supported by a simple geometry that enhances cleanability. It enables the scalable and hygienic cultivation of sensitive cells, addressing critical bottlenecks in regenerative medicine and sustainable food production.

The technology is an advanced Clinical Decision Support System (CDSS) designed to streamline and enhance the process of medication review, with a strong focus on safe deprescribing practices. Built on evidence-based guidelines and best clinical practices, the application provides healthcare professionals (doctors, pharmacists, and nurses) with reliable recommendations to optimize medication regimens, particularly for older adults who are at higher risk of polypharmacy and adverse drug events. This team-care deprescribing application can be seamlessly launched across various points of care: hospitals, clinics, nursing homes, or community health settings. This enables clinicians to work collaboratively in reducing medication burden while safeguarding patient safety. By integrating into existing workflows, it not only improves efficiency and decision-making but also supports higher standards of clinical care, leading to better health outcomes and quality of life for patients.

There is a growing global demand for complex-shaped transparent ceramics such as spinel in specialised lenses, optoelectronics, electronic, semiconductor and biomedical applications. However, large-scale commercial production of ceramics parts of high transparency and complex geometries has not been fully established. At present, most transparent ceramics are commercially fabricated in simple geometries using conventional methods such as injection molding or hot-pressing. 3D-printing techniques such as direct ink-writing, digital light processing and stereolithography has enabled the fabrication of ceramic parts of higher complexities, but the optical transparency of such ceramic parts remains limited. This technology is among the first to provide high-transparency 3D-printed spinel ceramics with highly complex design. It integrates proprietary spinel ceramic paste, 3D printing process, and specialized heat treatment process. The resulting 3D-printed ceramics possesses a high relative density, exceptional mechanical strength, good optical transparency and wide design flexibility. Together, these advantages position the material as a strong alternative to current options such as 3D-printed silica glass, yttrium aluminum garnet (YAG), and sapphire. Moreover, compared to conventional manufacturing methods, 3D-printed spinel ceramics significantly reduce material waste while shortening the prototyping to production timeline. This appeals to both industry application and sustainability. This technology supports a wide range of design complexities, resolutions, and application needs. The technology owner is currently looking for more industry collaborators that are interested in exploring and pushing the boundaries for 3D-printed transparent ceramics. They are able to offer flexible co-development modes for specific use cases for partners with or without existing in-house 3D printing capabilities.

Marine and river pollution, particularly during coastal disasters, threatens the biodiversity of affected areas due to the inflow of hazardous contaminants. In addition, with the increasing use of plastics, microplastic pollution in water bodies is also on the rise. To address such marine pollution, cleanup operations must be carried out promptly to reduce the negative impact on the environment. However, these operations are typically costly, require extensive coordination, and are cumbersome. A Korean startup has designed and developed an autonomous floating robot capable of accurately detecting and collecting marine debris in real time during coastal disasters. This compact robot is built to remain durable and reliable even under harsh weather conditions. Equipped with proprietary AI algorithms as well as LiDAR and vision sensors, it enables intelligent perception and decision-making, adapting to changing marine environments such as obstacles, waves, and currents. With its on-device AI functionality, it can operate independently without relying on external communication networks. This provides a practical solution for faster and more cost-effective maritime emergency response, while delivering measurable ESG improvements. The technology owner is seeking marine environment service providers and government agencies that are open to conduct pilot trials, as well as partners to jointly develop complementary technologies to further enhance the robot’s capabilities.