TECH OFFERS

Indoor vertical farming is pivotal for addressing future food challenges, particularly in arable land-scarce countries. One common method is hydroponics, which uses mineral and nutrient solutions in a water-based platform to grow crops. To optimize the crop yield and to reduce the man work hours required, it is important to automate crop health monitoring and replenishing of specific nutrients. Currently, these tasks are labour-intensive and subjective. While some imaging techniques exist for detecting plant stress and chlorophyll monitoring, a complete system covering all aspects is still lacking. For nutrient analysis, tools like pH and electroconductivity meters can only detect a change in the nutrient composition to start a feedback loop but are unable to determine the specific nutrient component or deficiency level. This technology is a comprehensive quantitative monitoring system integrating imaging spectroscopy and laser-based elemental spectroscopy to quickly identify the crop growth stages, alert crop stresses (tested on several lettuce species) and quantify specific nutrient levels in the nutrient supply. This allows for reduced man work hours and improvement of crop yield. Complete crop health monitoring through combined leaf, root, and nutrient supply monitoring, with automated replenishment Real-time in-situ component wise nutrient monitoring capability with high sensitivity (in ppb levels) enabling automated selective nutrient replenishing Non-invasive and non-contact, no sample preparation required Modular sub-systems allowing for easy integration with existing systems Machine learning capability for improved spectral library creation, enabling rapid and efficient monitoring   Applications validated at lab scale: Automated hydroponic crop monitoring in large indoor agricultural farms Inline, real-time nutrient monitoring of nutrient solutions Other applications tested at experimental POC scale and shown to be more rapid and accurate than existing methods: Real-time water quality monitoring Post-harvest quality determination of crops Trace elemental detection in body fluid   Offers full-spectrum monitrong for both crop health and nutrient supply, covering both leaf and root systems Enables automated, real-time nutrient replenishment with precise, component-wise monitoring at ppb sensitivity levels Features modular subsystems and easy integration with existing setups, supported by specific spectral libraries and machine learning for efficient monitoring and classification   Hydroponics, Nutrient Monitoring, Non-destructive Monitoring, Urban Farming, Indoor Farming, Spectroscopy, Imaging Life Sciences, Agriculture & Aquaculture, Foods, Quality & Safety, Environment, Clean Air & Water, Sensor, Network, Monitoring & Quality Control Systems

Leaks in water pipelines are a common problem for utility companies. In the utility sector, the term “real losses” refers to actual physical water leaks that occurs on transmission and distribution mains, leakage and overflow at utility storage tanks and leakage on service connections up to the water meter. These non-revenue water losses cause a significant economic loss even to some of the most well-managed water distribution systems in the world. To manage and reduce water loss, utility companies carry out preventive maintenance, perform active water network monitoring by using noise loggers, smart meters, flow/pressure meters to collect useful data. Another proactive approach is to employ state of the art leak detection and localisation technologies such as acoustic leak detection (hydrophones), accelerometers, or the use of robots/endoscopes. Such approaches often face the challenges of false alarms, inaccurate leak pinpointing, limited exploration range and high cost of long-term monitoring. Developed by a South Korea-based startup, the proposed technology herein relates to an AI-aided exploration robot for underground/buried pipeline diagnosis for leaks, cracks, corrosion, scale, surface damage and other anomalies using image, audio, pH and LiDAR sensor data. Unlike conventional robots, the exploration robot is designed to be relatively small (smallest being 4.4 cm diameter x 11 cm length) to enable direct inspection of the inside of small diameter water pipelines. Designed to complement hydroacoustic technology, the exploration robot also addresses the current challenge of short explorable distance of about 100 m by offering up to 3 km exploration range. The startup is seeking to work with utilities or companies providing services to utilities to perform trial preferably in Singapore and explore long term collaborations in terms of customising solutions to specific applications, as well as technology licensing and revenue sharing through joint development with Singapore-based partners. Consist of two types of tethered exploration rovers: 1) Small robot equipped with image, sound and pH sensors, and 2) Robot equipped with LiDAR equipment. Designed to navigate bends and angles within pipelines, the robot is capable of inspecting water pipes with diameters ranging from 50 mm to 300 mm. Based on the collected data, the system performs AI-aided diagnosis of anomalies of up to 5 classes, i.e., Normal Pipe, Weld, Corrosion, Scale, and Surface Damage, along with a water pipe deterioration score and recommendation for pipe cleaning and/or replacement cycle. Capability to develop 3D maps based on image and other sensor data to enable digital twin-based asset management solution for the water distribution network and facilities. Utilities or public agencies that operates and maintains the water distribution network. Facilities that are close to its useful life: for early warning / prediction of the cleaning and replacement cycle of pipes. Future development for oil and gas pipelines applications. As of 2018, the global water industry generated about $1087.4 billion, accounting for about $600 billion in capital expenditures and operational expenditures for water and sewage-related facilities. Singapore's smart city and infrastructure management market is growing rapidly, and it is expected to reach billions of dollars by 2025. In particular, the water supply and infrastructure management market constitute a significant portion, estimated at several million to tens of millions of dollars annually. The nationwide water leakage rate in Singapore is around 10%, which is a substantial loss for a small city-state. Efficient and accurate pipeline inspection and maintenance powered by AI image analysis and digital twin. Exploration robots equipped with multiple types of sensors including LiDAR to generate 3D maps, with industry leading exploration range of up to 3 km. AI-driven robot inspects water pipelines in real-time, detecting issues such as leaks, corrosion, and blockages without requiring service interruptions, which ensures a continuous water supply and minimises costly manual inspections. Water pipes, Abnormal signs, Exploratory robot, 3D maps, Digital twin Environment, Clean Air & Water, Sensor, Network, Monitoring & Quality Control Systems