Monitoring safety and productivity on industrial sites is traditionally manual, error-prone, and resource-intensive. Supervisors often struggle to monitor multiple CCTV feeds, leading to missed incidents and project delays. This technology leverages AI-powered video analytics to automate the detection of safety violations—such as missing PPE, high-risk behavior, and productivity lapses—without the need for constant human oversight. In Singapore alone, over 3,000 construction-related injuries and 17 fatalities were reported in 2023, underscoring the need for smarter solutions. Beyond real-time alerts, the system delivers actionable insights to support long-term safety improvements and operational efficiency. The technology owner is seeking system integrators and software companies for R&D collaboration and test-bedding.

With the integration of monitoring electronics into our everyday lifestyle, such as wearables, the utilisation of flexible electronics becomes more apparent as users demand them to not impede into their daily activities while being operational due to their ability to be deployed in areas with mechanical motion. Conventional flexible printed circuits (FPC), due to use of non-stretchable substrates, struggle under various constant deformation, resulting in poor adhesion, poor electrical contact and even pressure points which potentially limits normal operation. With discomfort and limitation on their motions, users are also less inclined to adopt these wearable solutions. The technology owner has leveraged on their expertise in stretchable substrates and conductive ink to develop a stretchable printed circuit (SPC), which have the ability to maintain contact and performance comparable to a rigid printed circuit under repeated deformation, such as stretching and twisting. The developed SPC enables existing electrical and semiconductor components to be mounted, eliminating any need for proprietary electrical components, while fully operational under external environmental conditions. The technology excels in larger surface application with semi-disposability in mind while having good adhesion and comfortable on skin. The technology owner is currently seeking industrial collaborators looking to explore use-cases, such as medical equipment development and diagnostic devices, whereby electrical performance can be maintained while providing mechanical flexibility.

This technology comprises two AI-powered software solutions that automate radiological image analysis to support the diagnosis and evaluation of knee osteoarthritis (OA) and lower limb alignment. One module enhances musculoskeletal diagnostics by detecting radiographic features such as joint space narrowing and osteophytes using criteria like Kellgren & Lawrence grading. It enables standardized, automated evaluations that support radiologists and orthopedic professionals in making accurate assessments. A complementary module focuses on analyzing lower limb alignment by measuring critical anatomical parameters including the Hip-Knee-Ankle angle, Joint Line Convergence Angle, and Mechanical Lateral Distal Femoral Angle. These automated assessments reduce human error and reading time while improving diagnostic accuracy and consistency. Designed for seamless integration with Picture Archiving and Communication Systems (PACS), this system fits effortlessly into existing radiology workflows. Target adopters include hospitals, imaging centers, orthopedic clinics, and telemedicine platforms seeking improved efficiency, diagnostic consistency, and enhanced musculoskeletal healthcare outcomes.

This non-invasive wearable integrates advanced photoplethysmography (PPG) sensing with a proprietary Pulse Shape Variability (PSV) algorithm to deliver real-time insights into stress levels linked to blood pressure fluctuations. Unlike conventional wearables that rely solely on heart rate or HRV, this technology analyzes the full morphology of the pulse waveform, capturing dynamic changes in amplitude, rise time, and contour that reflect vascular tone modulation caused by psychological stress. The result is a highly responsive and motion-tolerant stress detection platform that functions effectively in real-world conditions. By transforming microvascular signals into actionable insights, the solution enables proactive stress awareness, personalized wellness coaching, and context-aware emotional feedback, unlocking new opportunities in digital health, telemedicine, fitness, and mental wellness ecosystems. The technology owner is primarily seeking industry adopters and solution partners including medical institutions, device manufacturers, software developers, and fitness centers, who can integrate the technology into real-world applications with interest in deploying the system for use cases such as mental wellness, stress monitoring, fitness optimization, and remote healthcare. They also welcome collaboration with subject-matter experts to jointly enhance the algorithm and explore new features or application areas.

The adoption of multi-functional autonomous robots is steadily increasing to support and enhance operational efficiency in the facilities management sector. This technology presents a robot integrated with advanced sensor systems, artificial intelligence (AI), and autonomous mobility to perform multiple tasks. As a digital concierge, the robot provides enhanced visitor experience with seamless 2-way communication and an integrated touchscreen to connect with site duty personnel. The same screen can double up as an announcement board for advertisements and alerts, thereby extending a virtual front-desk capability effectively. In the security domain, this robot conducts autonomous patrols with real-time video surveillance and A.I.-based anomaly detection. The security head is embedded with a "brain” to perform on-edge computing to detect security-related used cases, significantly improving safety and accuracy in complex indoor environments. For cleaning, the robot can detect over 30 types of waste with 99% accuracy. Its self-adaptive cleaning system adjusts to floor type and debris volume, while a verification mechanism ensures more effective spot-cleaning compared to conventional single-pass robots.  These Multi-Functional Autonomous Facility Management Robot can yield significant operational savings, increase patrol frequency and shorten response time to incidents. This technology offers a software that features plug-and-play solutions that be customised to specific SOPs and needs. The technology owner is looking for collaborators, such as building owners and integrated facility management companies, with use cases to test-bed AI models. Examples include but not limited to identification of suspicious baggage, illegal parking or stray supermarket trolleys. 

This technology uses Machine Learning and AI algorithms to identify what appliances get plugged in to a building and when they are wasting energy. Plug Power represents 40% of the energy in a commercial building. Half of this energy is wasted with appliances left on when nobody is in the building. When wasted energy is found the plugs automatically switch off the appliances wasting energy and turn them back on before people return to the building. The technology not only saves energy and carbon emissions but makes buildings safer by detecting and preventing unsafe energy loads as well as reporting on occupancy and enabling behavioural change with occupants. The technology provider is seeking collaboration partners among businesses operating commercial buildings that utilize plug sockets — particularly those with multiple locations and high energy-consuming appliances. Potential partners include, but are not limited to, retail chains, F&B chains, the hospitality industry, healthcare facilities, education and training centres, and fitness and wellness chains.

Manual built environment inspection suffers from multiple issues such as shortage of manpower, human error and miscommunication. To overcome these issues, there is a need for an automated and centralized inspection system capable of detecting multiple defects of interest and presenting the inspection results in an easy to access format. The technology presented uses data acquired from LiDAR and Cameras mounted on an autonomous robot to inspect building interiors and external facades. The system utilizes an AI engine and can accurately detect defects such as cracks, holes, and other built imperfections stated in building quality guidelines such as CONQUAS. Defect reports can be autonomously generated after the acquired image and LiDAR data has been processed by the AI analytics engine. 

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.  

With the focus on food security and sustainability, urban farming is gaining traction in Singapore. Most farmers who are new to the industry still rely heavily on pesticides for pest control and crop protection. Although effective, the use of pesticides pose several concerns such as: Health and Environmental Risks: Pesticide residues in food pose potential health hazards, while excessive use can lead to soil degradation, water contamination, and harm to beneficial insects and biodiversity. Regulatory and Market Pressure: Stricter regulations on pesticide use and growing demand for organic and naturally grown produce create the need for sustainable solutions. In addition, the educated consumers increasingly prefer pesticide-free vegetables, thereby driving the need for natural alternatives. Biological solutions such as biofertilizers, bionutrients, and biostimulants offer a promising alternative to agriculture. These solutions can: Enhance Plant Growth: Improve nutrient uptake and plant resilience through naturally derived growth stimulants. Improve Soil Health: Support microbial activity and enhance soil fertility without chemical degradation. Reduce Dependence on Chemical Fertilizers and Pesticides: Provide natural pest resistance and nutrient supply. Promote Sustainable Production of Asian Leafy Greens: Crops such as bak choy, butterhead lettuce, and spinach Farmers are seeking to collaborate with companies with biological solutions to run validation trials in their farms.

Agricultural activities in Asia Pacific region generate significant amounts of manure from various farming operations, including: Layer Hens: A layer hen produces approximately 0.08–0.12 kg of manure per day. Cattle Farming: Dairy and beef cattle generate an average of 30 kg of manure per day per animal. Pig Farms: Pigs produce about 2–4 kg of manure per day. Manure accumulation presents several environmental and operational challenges such as odour pollution, water contamination, greenhouse gas emissions and pathogen proliferation. Despite these challenges, manure has significant potential when processed effectively. It can be converted into valuable resources such as: Biogas & Bioenergy Biochar & Carbon Sequestration Organic Fertilizers and Soil Conditioners Farms have found solutions that produce good quality fertilisers and soil conditioners with their manure. However the amount of manure generated is more than what they can use and would like to work with innovation technologies to manage and convert their farm's manure efficiently. 

According to the Health Promotion Board (HPB) in Singapore, 90% of Singapore residents' consumption of sodium exceeds the daily recommended intake, with the average consumption at 3620 mg, nearly double of the recommended 2000 mg per day. As a result, one in six Singapore residents report health problems like hypertension and hypolipidaemia. In an effort to curb this, HPB launched the "Less Salt, More Taste" campaign in 2024 to encourage the food manufacturing and food service industry to change their recipes and add less salt and sauces, or switch to use lower-sodium alternatives for salt, sauces and seasonings. Manufacturers are also encouraged to increase the supply of lower-sodium ingredients for the food service sector. Consumers are also encouraged to choose low sodium options, or use less salt in their home cooking. This sodium reduction strategy aims to reduce Singaporeans’ sodium intake by 15% by 2026.