TECH OFFERS

Conventional aircrafts have been a preferred mode for fast middle mile delivery within logistics and supply chain. With the increasing traction of drone technology, the usage of drone as a potential alternative mode of transport within the supply chain is greatly considered, given its comparable performance and more sustainable. Current conventional aircraft requires a runway for landing and take-off, limiting their use-case within space constraint areas. For drones, its slow operational speed and short operation range greatly limits it widespread industrial adoption. The technology owner developed a UAV solution which enables faster operational speed (up to four times) and longer flight duration (over 2 hours) compared to incumbent multicopter drones of the same class. This UAV solution comprises of tilt-electric ducted fans, a hybrid energy source and optimised design to harnesses the advantages from both drone and conventional aircraft technologies. Due to these capabilities, the technology solution enables high-risk and high-difficulty missions to be carried out, with the safety of the operator in mind, such as wide-area surveillance and reconnaissance, transportation to remote regions and shore-to-ship deliveries. The technology owner is looking for collaboration partners seeking to further explore drone technologies or integrate drones into existing workflow processes which require longer operational range and faster speed that current traditional multicopter drone is unable to accommodate. The UAV solution features a 3-meter wingspan, fixed-wing fuselage with four tilt EDFs (Electric Ducted Fans) that enables eVTOL (electric vertical take-off and landing) capabilities. It utilises a hybrid energy source system combining batteries and an eco-friendly generator for its operation, increasing its energy density for operation. Due to the proprietary flight control software, the UAV has the capability to fly for over two hours at a maximum speed of 200km/hr, providing 20 times flight range compared to conventional multicopter drones. With the optimised design of the UAV, it has a MTOW (maximum take-off weight) of 65 kg with a total mission payload of 10kg, enabling further customisation of the drone for function-specific applications. Based on the technical expertise, proprietary airframe design and flight control software, the technology owner envisions an air mobility solution to enable payloads between 200-250kg, maximum operational speed of 400km/hr and potential flight range of 400km, unlocking further capabilities for possible middle-mile transportation mode. With a heavier payload, faster operational speed and much longer flight range, the following potential applications can be explored, such as: Middle-mile transportation to currently inaccessible regions by conventional modes (road deliveries and light aircrafts) like mountains and remote islands Wide-area surveillance and reconnaissance requiring long deployment and constant monitoring Urban Air Mobility (UAM) for pilot training and ultra-light aircraft aerial transport Shore-to-ship transportation for logistical resupplies Disaster response for delivery of emergency medical supplies and services The global drone industry currently has a market size of $27 billion in 2021 and is expected to be valued at $122 billion in 2032, exhibiting a CAGR of approximately 14.6% during the forecasted period. This UAV solution integrates the advantages of both conventional drone technologies and conventional aircraft technologies, enabling eVTOL with a fixed-wing aircraft design. This enables vertical take-off and landing in confined spaces without a runway, while also enabling high-speed and long-distance flight similar to conventional fixed-wing airframe design. Additionally, by utilizing an eco-friendly hybrid energy source, it overcomes the low energy density limitations of traditional battery systems and allows for UAV operations independent of separate charging infrastructure. UAV, eVTOL, Logistics Transportation, Logistics Delivery, Drone, Advanced Air Mobility, Unmanned Aerial System Infocomm, Robotics & Automation, Smart Cities, Logistics, Transportation, Delivery & Distribution

In healthcare, accurately assessing pain is critical, yet it remains a significant challenge, particularly for patients unable to effectively communicate their discomfort. This includes individuals with cognitive impairments, critical care patients, and pre-verbal children. Traditional pain assessment methods rely heavily on verbal communication or subjective observer-based pain assessment, which can lead to missed or poorly managed pain, resulting in either under-treatment or over-analgesia treatment. To address this issue, this advanced AI-based solution automates the process of estimating pain intensity by analyzing facial expressions captured in video data. The technology is a deep learning system consisting of facial landmarks (specific points on a person's face, such as the corners of the eyes, nose, mouth, and other prominent facial features) extraction, 3D normalization and Spatial-Temporal Attention Long Short-Term Memory (STA-LSTM) model. These facial landmarks provide critical information about facial expressions, allowing the system to accurately assess pain levels. By integrating this technology into clinical settings, healthcare providers can significantly enhance patient care, reduce the burden on staff, and improve overall pain management practices. This solution not only ensures timely and appropriate intervention but also protects patient privacy by using non-identifiable facial landmarks, making it a powerful tool for modern healthcare environments. The technology is an advanced AI-based software algorithm designed for automated pain detection using facial expressions. It offers the following features: Automated Pain Detection: Utilizes a deep learning model that seamlessly integrates facial landmark extraction and analysis to estimate pain intensity levels without the need for human intervention. Real-Time Monitoring: Continuously tracks and assesses pain levels from video footage, providing instant feedback and visual representation of pain level distribution over time. AI-Driven Analysis: Powered by a Spatial-Temporal Attention Long Short-Term Memory (STA-LSTM) network, the system excels in identifying and analyzing specific facial expressions related to pain, ensuring high accuracy in pain detection. Privacy Protection: The system exclusively uses non-identifiable data by extracting and processing facial landmarks, ensuring patient privacy while maintaining the integrity of pain analysis. High Accuracy: Achieves a training accuracy of 98% and a validation accuracy of 92.2%, supported by robust data processing techniques, including 3D normalization of facial landmarks and strategic data balancing. This technology is highly suited for hospitals, nursing homes, and healthcare facilities that manage patients who are non-communicative, cognitively impaired, or otherwise unable to express their pain effectively. It is also valuable for telemedicine platforms, rehabilitation centers, and home care services, where remote patient monitoring is critical. Furthermore, the system can be seamlessly integrated into surgical and critical care units to provide real-time pain assessment. Its ability to integrate with existing infrastructure, such as CCTV systems, makes it a cost-effective, easily adoptable solution that enhances pain management across various healthcare settings. This system offers secure, non-invasive, objective and real-time pain assessment by analyzing non-identifiable facial landmarks, ensuring patient privacy and compliance with data protection regulations. Objective and Continuous Pain Assessment: Provides real-time, objective monitoring, reducing reliance on subjective assessments. Improved Patient Outcomes: Ensures timely and appropriate pain management, preventing under- or over-analgesia treatment. Privacy Protection: Uses facial landmarks for analysis, maintaining patient anonymity. Eases Healthcare Providers' Burden: Automates pain monitoring, allowing staff to focus on other critical tasks. Cost-Effective Integration: Easily integrates with existing infrastructure, offering a scalable solution. Broad Applicability: Suitable for diverse healthcare environments, including hospitals, nursing homes, and telemedicine. Facial Recognition, Pain Detection, Facial Landmarks, STA-LSTM, Healthcare, Cognitive Impairments Infocomm, Artificial Intelligence, Healthcare, Diagnostics, Medical Devices, Telehealth, Medical Software & Imaging, Healthcare ICT

Cooking oil waste has become a significant environmental problem in recent years. Improper disposal of used cooking oil and fried food scraps can lead to pollution of water sources and the release of harmful greenhouse gases. When poured down into drains, it travels through sewage systems to rivers and oceans, disrupting ecosystems, clogging water treatment plant filters, and complicating water purification processes. Additionally, there are higher costs associated with waste disposal in volume-based plastic garbage bags which are also not environmentally friendly. This technology addresses the above pain points by offering a sustainable solution that recycles discarded fried food scraps into high valued biodiesel raw material, preventing water pollution and sewage pipe blockage when discarded without appropriate measures. This innovation addresses a critical market need by providing a greener alternative to conventional disposal methods, reducing waste disposal costs and the production of high valued biodiesel as an end point.  The technology owner is seeking collaborations with companies in the fields of waste management and biodiesel production for test-bedding and research & development projects aimed at recycling fried food scraps into biodiesel. Advanced System Features: It starts with the input of fried food crumbs, where impurities are removed. The material undergoes heat treatment with controlled rotation to optimize the separation process. The mixture is then separated into two main components:  Sludge: used as a raw material for biodegradable plastics, supporting the development of sustainable materials. Crude Waste Cooking Oil: Further refined into biodiesel raw material, offering a renewable alternative to traditional fossil fuel. IT-Driven Collection and Digitalization: It utilizes an IT platform to collect and digitize the supply chain of fried crumbs which enhances the efficiency and traceability throughout the process. Recycling Focus: Emphasizes recycling food waste rather than upcycling, ensuring complete repurposing into new products which maximizes resource recovery by fully converting waste into valuable outputs. This technology has the potential to be applied on these areas, harnessing on its ability and process to convert waste cooking oil into high valued biodiesel. Renewable Energy Sector: The refined waste cooking oil can be used as a raw material for biodiesel, a renewable fuel that can power diesel engines in vehicles, machinery, and generators, reducing reliance on fossil fuels and lowering greenhouse gas emissions. Waste Management and Recycling: Innovative waste management solution for food processing industries, restaurants, and large-scale kitchens, turning waste by-products into valuable resources rather than disposing of them. Agriculture and Animal Feed: The sludge can also be used as a nutrient-rich feedstock for insect farming, supporting the production of sustainable animal feeds. The global biodiesel market was valued at approximately ~USD 43 billion in 2022, with an expected annual growth rate of 5.25%, projected to reach ~USD 65 billion by 2030. Additionally, the market for bio aviation fuel is anticipated to increase by 60 million tons by 2040 (growth of over 20%). This underscores a strong demand for sustainable biofuels. Innovative Raw Material Use: Unlike other companies that primarily use waste cooking oil, this technology utilizes fried food crumbs as the main raw material, allowing a more versatile input stream, tapping into an underutilized waste source. Superior Additive Development: Significant advancements in additive development have resulted in a 50% increase in overall yield, making their process 2.5 times more effective than competitors. Furthermore, the enhancement in acid value indicates a superior quality of biodiesel raw material, which translates to improved efficiency and performance. biodiesel, carbon neutral, recycling, cooked oil, waste reduction Sustainability, Circular Economy

With the global trend of industrial automation, robotic arm technology is being developed and integrated to existing business workflow, increasing labour productivity and operational efficiency. However, current end effectors attached to robotic arm excels in automation tasks of handling homogeneous robust objects but fall short in handling irregular, fragile objects. Current robotic grippers (end effector) lack the finesse and limberness required, limiting their usage in particular areas such as agriculture, F&B, pharmaceutical and logistics. The technology solution developed is a smart soft robotic gripper as a modular end effector that addresses the challenge of handling objects with varying sizes, shapes, and weights, an issue unsolved by traditional robotic grippers. This innovative gripper tool mimics the flexibility and versatility of biological structures like tendrils, enabling an extra dimension of growth and twining capabilities. By wrapping itself securely around objects, the gripper manipulates items gently, minimizing the risk of crushing or damaging them. Its integrated sensors provide real-time contact feedback capabilities, enabling precise monitoring and adaptive control by the robotic system. The technology owner is seeking collaborative partners, such as system integrators or end-users, who are in need and keen to integrate a versatile, adaptive, and gentle handling solution that can operate efficiently in environments where object fragility or irregularity is a key concern. The smart soft robotic gripper module comprises of three key components: flexible fingers, actuation system and sensor integration. A novel concept is introduced for a flexible finger, utilizing a single tendon within a flexible body to perform three-dimensional bending and twisting motions. This design enhances the gripper’s adaptability, allowing it to handle objects with various shapes, sizes, and weights, with current payload exceeding 10kg. The integration of vision and haptic sensors further refines its capabilities to provide gentle and precise manipulation of delicate items. Additionally, the sensor integration supports potential applications in sensor fusion and IoT systems, expanding its utility across advanced automation environments like smart farms and smart factories. With its modular design, it enables customisation and scalability to integrate into existing robotic systems. Handling of Food (urban farming, food and beverages) The gripper solution can gently handle delicate crops like bunches of vegetables and irregularly shaped fruits, which can facilitate automated harvesting or processing with minimal damage. Its adaptability makes it potentially suitable for smart farms where precision and adaptability are essential. A pilot test for harvesting automation is currently being conducted in an urban farming application. Smart Factories (warehousing, manufacturing) The gripper solution is able to handle a variety of fragile and odd-shaped product, providing flexibility to environments of heterogenous items. The technology also enables safe handling of items, promoting industrial automation of delicate assemblies and improving assembly precision. Pharmaceuticals (medical device, procedures) The gripper tool can handle sensitive medical devices and products to minimise or prevent damaging during handling. The tool is able to provide additional assistance to medical personnel for more delicate medical procedures, reducing discomfort while increasing precision. The smart soft robotic gripper is bio-inspired and mimics natural organism, like octopus arms, to enhance navigation and interaction with their surroundings. This results in an extra dimension of flexibility and versatility to handle intrinsic nonlinearity of soft, delicate, heterogenous materials. The integrated sensors enable situational awareness capabilities, providing adaptability and enhancing precision. Lastly, the modular design provides customisability to specific use-cases, with the gripper being able to be scaled to suit the operational needs. Soft Gripper, Smart Gripper, End Effector, Soft Robotic Gripper Electronics, Actuators, Manufacturing, Assembly, Automation & Robotics, Foods, Processes

In a more globalized and interconnected world, logistical management becomes more complex with more demand for real-time tracking of products within the supply chain. With global events potentially disrupting any section of the supply chain, companies within are now required to efficiently provide visibility of the orders while building up resiliency to ensure smooth operation of their services. The technology solution addresses the complexities of modern supply chains by providing a unified solution that integrates multiple products & tools for efficiently managing the logistics and warehouse. The platform uses AI and IoT to deliver real-time visibility, predictive analytics, and automated workflows. This innovation aims to improve efficiency, reduce costs, and enhance sustainability for enterprises within the logistics and warehouse sectors. The technology owner is looking for collaboration partners, who wish to leverage on their data and AI solutions to automate logistical workflow operations and enable data-driven decisions for supply chain optimisation. The solution suite encompasses a suite of modules including a warehouse management system (WMS), labor management system (LMS), transportation management system (TMS), and shipping solutions. The key features of this technology include AI-driven predictive analytics, real-time tracking, automated inventory management, and comprehensive API integrations with e-commerce platforms and carriers. The platform’s comprehensive and scalable solution accommodates to the growth plan of any business while providing smooth operation, improved operational efficiency and cost savings. The digital platform is a versatile solution improving supply chain processes across various industries such as Warehouse Automation: Enables streamline inventory tracking, order picking and shipment processing Inventory Management: Optimise inventory stock and prevents stockouts or overstock situations Logistics Management: Leverages on AI to optimise transportation route planning, shipment tracking and carrier management Supply Chain Processes: Provides real-time visibility and analytics while integrating seamlessly with existing system Retail Management: Enables management of omnichannel inventory, automating order fulfilment and ensuring timely deliveries The global logistics automation market is projected to reach USD 100 billion by 2025. The end-to-end platform solution provides workflow automation from the first mile to the last mile for any logistics operation needs. Its modular design offers customization while ensuring scalability, catering to the unique needs of both small businesses and large enterprises. This AI-powered solution provides AI-driven insights via forward technology integrations and seamless 3rd party system integration, enabling a high level of connectivity and accessibility. Logistics Automation, Warehouse Management, Supply Chain Visibility, Predictive Analytics, API Integration, Shipping, Freight Forwarding, Artificial Intelligence Logistics, Planning & Order Processing, Inventory Management, Delivery & Distribution, Value-Added Services

Cancer is one of the most deadly diseases worldwide, requiring pathological testing to confirm the diagnosis. With recent advancements in digital pathology, there is a growing demand for AI-based digital pathology diagnostic products to manage and shorten diagnosis time for accurate and targeted treatments. Thyroid cancer is a relatively common type of cancer. The malignancy of thyroid nodules is determined through the pathological examination of cells obtained via Fine Needle Aspiration (FNA) or Core Needle Biopsy (CNB). However, due to the complexities of thyroid nodule pathology, over 30% of patients' biopsy samples are classified as indeterminate, meaning they cannot be definitively diagnosed as benign or malignant. Additional testing, such as Next-Generation Sequencing (NGS) molecular tests are required to provide further clarification. However, the high cost of testing limits patient accessibility. This technology is an AI-powered solution that analyze pathology images obtained through Core Needle Biopsy (CNB), providing diagnostic results for benign or malignant nodules. It offers interpretation and visualization of AI analysis results. This allows for accurate diagnosis of not only the benign(C2) and malignant(C6) cases traditionally identified by pathologists but also indeterminate(C3,C4,C5) cases that were previously challenging to diagnose. This approach ultimately reduces unnecessary surgeries, thereby improving the quality of life for patients. It offers a cost-effective alternative to expensive and less accessible NGS testing, delivering similar diagnostic accuracy without the need for additional tests. The technology owner is seeking partnerships with medical institutions specializing in oncology, including major hospitals and clinical laboratories, pharmceutical and biotechnology companies.  AI-based Pathology Image Analysis Solution: This technology leverages AI to analyze CNB thyroid nodule tissue images stained with H&E. This process involves a highly complex series of steps distinct from typical natural image analysis. These steps include tissue detection within the image, patching of tissue images, feature extraction from these patches, and the classification of malignant and benign nodules. This AI solution provides an optimized technology pipeline for such analysis and incorporates state-of-the-art pathology image analysis AI system. This system is capable of diagnosing areas that human pathologists may not be able to detect visually, offering revolutionary diagnostic capabilities. AI Interpretation and Visualization: The solution provides a quantified score indicating the malignancy level of the thyroid nodule. It also highlights key areas within the tissue slide where the tumor is located using a localized heatmap, identifying major regions that affect malignancy. Optimal User Convenience: This solution offers a web-based service to ensure accessibility and user convenience, allowing medical professionals to access diagnostic tools and results from any location with internet connectivity. It supports hybrid deployment in both on-premise and cloud environments, providing flexibility to optimize user settings and service provision based on institutional needs. Additionally, this solution includes a custom-developed pathology image viewer and management system that supports various formats, enabling users to explore, manage, and review image information efficiently. Clinical Unmet Need: This technology addresses significant clinical unmet needs by providing accurate and timely diagnosis of thyroid nodules, reducing the number of indeterminate cases and minimizing the need for unnecessary surgeries. This improves patient outcomes and reduce healthcare costs. Personalized Cancer Treatment: This solution can be instrumental in the development of personalized cancer treatment plans. By accurately diagnosing the malignancy of thyroid nodules, healthcare providers can tailor treatment plans to the individual patient's condition, optimizing therapeutic efficacy and minimizing side effects. Cancer Metastasis Risk Prediction: By analyzing biopsy images and identifying malignant characteristics, this technology can help predict the risk of cancer metastasis. This early detection capability enables proactive management and monitoring of patients at high risk of cancer spread. Telepathology and Remote Diagnostics: The web-based and cloud-supported nature of the solution makes it ideal for telepathology applications. Pathologists can remotely analyze biopsy images and provide consultations, expanding access to expert diagnostics in underserved areas. Integrated Diagnostic Platforms: The solution can be integrated into comprehensive diagnostic platforms that combine imaging, molecular testing, and AI analysis. These platforms can offer a holistic view of a patient's condition enabling more accurate and comprehensive diagnosis. The technology targets a rapidly growing medical device market, particularly within the AI segment. The Singapore medical device market, recognized as a healthcare hub in the APAC region with world-class medical standards and infrastructure, is projected to reach $1.2 billion by 2028, with a compound annual growth rate (CAGR) of 6.3%. Additionally, the AI medical device segment is expected to achieve a remarkable CAGR of 45.8% by 2030, indicating the increasing integration and utilization of AI technology in the healthcare sector. Cost-Effectiveness: The significant cost savings compared to traditional molecular diagnostic test make this technology financially advantageous for both patients and healthcare providers. Integration and Usability: The ease of integration into existing systems and the support for remote diagnostics address practical implementation challenges, making the solution highly usable and scalable. Comprehensive Coverage: The ability to diagnose indeterminate cases and support remote diagnostics extends the reach and impact of the solution, offering substantial improvements over current methods. Digital Pathology, Thyroid Nodule Diagnosis, Thyroid Cancer, Clinical Decision Support System (CDSS), AI-Powered Infocomm, Artificial Intelligence, Healthcare, Diagnostics, Medical Devices, Telehealth, Medical Software & Imaging, Pharmaceuticals & Therapeutics

Maintaining clean air on ships is crucial for the health and well-being of passengers and crew, as well as for the proper functioning of sensitive equipment. Due to the structural specificity of ships and higher reliance on mechanical air conditioning than natural ventilation, addressing indoor air quality issues is particularly important. Advanced air purification solutions would be able to effectively address a range of airborne contaminants, including particulate matter, volatile organic compounds (VOCs), and biological pollutants, ensuring a safer and more pleasant environment on board. A Korean startup has developed an air sterilisation and purification system tailored specifically to the challenges of maritime environments that excels in delivering clean, safe, and compliant air quality solutions. They enhance health and safety, optimise operational efficiency, and contribute to a better overall experience for passengers and crew, while also meeting regulatory requirements and supporting environmental sustainability. The company is seeking collaborators from the maritime and built environment sectors, as well as HVAC and IoT companies, to expand their applications and explore integration of their technologies into existing HVAC systems. The technology consists of the following key features: A seamless three-step purification and sterilisation process using UV-C lamp, carbon filter, and HEPA filter Engineered housing design that increases air’s retention time, providing a wider and denser air distribution compared to a stand-type air purifier Utilises UV-C rays at a wavelength of 254 nm, ideal for disrupting the DNA and RNA of bacteria, without generating ozone Strong sterilisation capability through uniform dispersion of UV-C rays and a direct contact sterilisation method to maximise the effectiveness, achieving up to 99.8% removal of airborne viruses and bacteria Double filters remove up to 96.3% of major hazardous substance, including ammonia, acetic acid, acetaldehyde, toluene and formaldehyde  Can be retrofitted to existing diffusers The solutions have been successfully implemented on various types of ships and can also be applied to buildings, healthcare facilities or public areas on land where large gatherings occur. Potential applications include, but not limited to, the following: At sea: Ships (Existing / New) On land:  Healthcare facilities Educational facilities Commercial real estate Residential real estate Tailored for effective operations under the unique conditions found at sea Engineered housing design for enhanced air distribution and extended exposure time, allowing more thorough sterilisation of airborne particles  Enhanced health and safety contributing to the well-being and safety of passengers and crew Optimised operational efficiency leading to cost savings and improved reliability of critical ship systems Enhanced passenger experience by providing a more comfortable and pleasant on board environment Environment, Clean Air & Water, Sanitisation, Mechanical Systems, Sustainability, Sustainable Living

A smart manufacturing and supply chain platform has been developed, enabling seafood processors to automate and digitize their production, quality control, costing, traceability, cold chain, and inventory workflows using tablet computers, sensors, and IoT devices in real-time on the factory floor. This software is a “low-code” web app that can be easily configured for both simple and complex workflows, suitable for small or large production facilities, and adaptable to the wide variety of seafood processes, including live shellfish, fresh and frozen fish, smokehouses, and industrial-scale canneries. The workflow platform includes advanced modules for IoT hardware integration, artificial intelligence, advanced analytics and reporting, a wireless cold-chain sensor, a consumer tracing app, and computer vision for automated inspection. Generative AI is also integrated into the platform, allowing users to “talk to their data” and upload documents to train the large language model. The platform provides value to customers in three core areas: First, the software and AI reduce labor costs by making data collection, management, and reporting more efficient. Second, the software enables real-time process and inventory control, replacing outdated analog paper record-keeping. Third, the software reduces data errors and strengthens traceability, improving compliance with third-party certifications and food safety regulations. Additionally, it includes AI algorithms for yield prediction, anomaly detection, demand forecasting, and drain weight prediction in the fish canning sector. The software includes a core low-code workflow platform that can be configured for many different types of workflows and processes. The platform can be hosted on the cloud or on premise and includes features such as image and document uploading, inventory and logistics management, cost accounting, email and SMS notifications, data validations and real-time calculations, software integrations, and more. The core platform also includes several operational modules, such as: An advanced analytics module for data visualization and reporting. A generative AI module for exploring data and documents uploaded to the platform, enabling users to “talk to their data”. An interoperability module built on the standards of the Global Dialogue for Seafood Traceability and EPCIS supply chain protocols. An IoT connectivity module for label printers, weigh scales, scanners, and other devices A cold chain module with a remote, wireless temperature sensor communicating via LoRaWAN. A smart camera module programmed with computer vision models for automated visual inspection. An AI-enabled digital helper module programmed with machine learning algorithms for yield prediction, anomaly detection, demand forecasting, drain weight prediction (in tuna canneries), and more. A consumer tracing app that enables seafood businesses to share supply chain and food provenance information with consumers who can trace a QR code. The technology ideal collaborators are seafood manufacturers and supply chain operators. The software and AI platform and optional modules have the following potential digitization applications: Fishing vessel unloading Seafood Production and Quality Control Inventory and Warehousing Sales Orders, Fulfilment and Shipping Laboratory sampling and testing Compliance, ESG and Traceability Reporting Cold chain monitoring Cost accounting (manufacturing) Asset management The technology owner is seeking collaboration with seafood industry stakeholders, including manufacturers, suppliers, and distributors in Singapore and Southeast Asia, who are interested in improving efficiency, traceability, and compliance within the supply chain. Seafood is the most globally traded protein with a trade value of some $194 billion dollars, representing almost half of all seafood production in the world. Approximately 75% of seafood processors and supply chain operators manage their core operations with paper records and Microsoft Excel, lacking real-time business insights and struggling with process and inventory control. The technology offers the following: The platform offers easy and flexible configuration through low-code schemas, providing a user-friendly alternative to the extensive customization required by legacy software solutions. A complete all-in-one solution that includes core workflow digitization and inventory management, advanced analytics, computer vision for automated inspection, process automation, predictive analytics, generative AI, hardware integration, cold-chain monitoring, and consumer marketing and supply chain transparency. Expertise in seafood processing and supply chains is leveraged to enhance data collection and optimization, specifically addressing the needs of seafood companies. Applies artificial intelligence to seafood processing, utilizing advanced machine learning, computer vision, and generative AI technologies. Seafood, Fisheries, Supply Chain, Smart Manufacturing, Software, AI, ML, Computer Vision, Generative AI, Traceability Infocomm, Video/Image Analysis & Computer Vision, Artificial Intelligence, Internet of Things, Foods, Processes, Sustainability, Food Security

Plastic recycling plays a crucial role in achieving a sustainable future. Proper sorting of waste plastics is essential, especially in mixed waste streams where various materials are combined. Some types of plastic are not recyclable, and even recyclable ones can be difficult to separate efficiently. Sorting mixed waste streams into different recyclable categories can be time-consuming and labour-intensive, especially for materials with similar appearances, such as different types of plastic. To address these challenges, this technology aims to automate and accurately sort plastic waste, reducing the reliance on manual processing and improving overall plastic recycling efficiency. The technology on offer is a patented artificial intelligence (AI) based material sorting robot that sorts plastic waste accurately. Comprising of a camera, recognition unit and analysis unit, each unit of this system can continuously identify and sort waste plastics and generate information in real time. Blower vacuum adsorption devices are placed within each unit to pick waste in a speedy and accurate manner. This technology effectively reduces the issue of labour shortage in the waste sector, lowers operating costs and contamination rates that hinders recycling efforts. Currently, the technology has been deployed successfully in South Korea to sort polyethylene terephthalate (PET), polyethylene (PE) and polypropylene (PP). The technology owner is interested to work with Singapore waste collection companies on joint development projects to testbed this technology and improve plastic recycling rates. This technology comprises of the following hardware and software components: Camera unit – for real time monitoring Recognition unit – for real time item detection and data collection Analysis unit – for analysis of the type, colour, contamination level, and presence or absence of lids and labels Conversion unit – for item selection and sorting AI-enabled dashboard Key features of this AI-enabled material robot include: Sort rate of 96 pieces per minute 99.3% accuracy 7 types of waste This technology has been validated for plastic waste sorting (PET, PE and PP) and can be expanded into sorting of other types of wastes such as paper, plastic vinyl films, aluminium, iron and textiles. Other potential applications include construction and marine waste. High recognition and sorting accuracy Improves waste sorting efficiency by 240% in terms of speed and 126% in terms of operation time Cost-effective solution for resource efficiency (279% reduction in sorting costs) artificial intelligence, AI, robot, waste, plastic recycling, sorting, smart city, waste management, automation, environment, recycling, resource recycling, circular economy, sustainability Infocomm, Artificial Intelligence, Waste Management & Recycling, Industrial Waste Management, Automation & Productivity Enhancement Systems, Sustainability, Circular Economy