智慧

Migraine patients account for about 640 million people (15) in the world,about 1.75 million (9.1) in Taiwan. Our team had developed a wearable brain-computer interface system with the newly developed graphene dry electrodeadaptive noise subspace reconstruction technology. This system combined the physiological indicators before migraine attacksuses AI technology to build an intelligent migraine early warning system,combined BrainSTIM electrical stimulation technology to assist migraine patients.

In agriculture, the team has developed a “Chinese Medicinal Functional Compound Prediction A.I. System” that can predict compounds production during cultivation period. Moreover, in application, we have implemented a smart agricultural platform-AgriTalk to link the “Functional Compound Prediction System”“Smart Fertilization System” to provide a comprehensive management in farm production.

This system help doctors to distinguish age-related macular degeneration (ARMD)polypoidal choroidal vasculopathy (PCV) by color fundus photography. We have collected large image dataset from Taipei Veterans General Hospitalother hospitals to establishvalidate CNN model, which had been tested by external image datasetmodified to improve the accuracy of the AI model.

To resolve public safety and security issues, NCHC developed intelligent video analytics and retrieval system, which can integrate the attribute analysis and recognition of vehicles/pedestrians from CCTV surveillance cameras, utilize TWCC high-speed operation in developments such as AI image semantic analysis and video synopsis technique, to effectively and rapidly search for key targets(vehicles/pedestrians) and provide short clips of the targets’ moving path simultaneously, and as a result fulfill the quick search application service of technological surveillance and Investigation.

Our team construct an AIoT smart aquaculture management system. The management system mainly consists of: (1) Image Behavior MonitoringAnalysis Subsystem (2) Smart Feeding Subsystem (3) IOT Subsystem including underwater sensors, ROV,Drone (4) Cloud Subsystem (5) Big Data Analysis Subsystem.

The sweet pepper cultivationplant protection robot developed includes three parts: the intelligent image identificationpositioning system of sweet pepper diseasesinsect pests is composed of YOLO4 deep learning modelimage 3D vision integration. It can perform disease detectionspatial positioning,guide the robotic arm spraying device to accurately spray the diseased. The automatic walking system can use GPS to plan the movement path of the plant protection robot in the field, search for plants infected with pestsdiseases,perform the tasks of pest control.

Artificial intelligence 3D sensing image processing system based on array sensing Lidar aims to construct 3D image with high-quality immersion for AR/VR. The developed 3D scene recording system is based on the color camerahigh-accuracy chaotic LiDAR. The chaotic Lidar with APD arrayTOF sensors supports millimeter-accuracyinterference-avoiding capability within 100 meter in both indooroutdoor environments. High-performance embedded CNN processor supports high-throughput, high energy-efficient,low DRAM bandwidth computations for various image AI applications.

Ted-ICU AI Platform: (1)Provide a single view of patients＇ EMRsvital signs (2)Support remote ICU monitoring (3)Online labeling tool & Expandable AI algorithms repository (4)Disease-specific prediction models (5)Standardized EMR templates

We develop smart fabrics by electrospinning crystallinity-modified self-healing materials, which are facilitated by the reversible physical crosslinking between poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP)ionic liquid. The fiber morphology can be maintained without losing the fibrous structure. The fabrics can achieve the healing effects without the need of seamingany adhesive. The fabrics are waterproofbreathable. By printing electrically conductive channels using ionic liquid, capacitive pressure sensorsresistive tensile sensor arrays are fabricated.

A technique compatible to IC process has been presented to prepare gas sensing chips the lightly-doped region of nanoelectronic devices are grown with different sensing materials to form a gas sensor array. During gas sensing, individual nanodevice was Joule-heated, reducing power consumption to microWatts/device, solving the current high power consumption problem. With self-calibration of temperature, humidityinterfering gas, problems like cross-sensitivity, quantification, specificitysensitivity are solved. A demonstration of I+Nose with smart phone was presented for CO detection.

The smoke removal device with smart detection has the capability of gas detectionindoor air circulation. The system is internally equipped with a sensing device. If an abnormal PM2.5 valuea high concentration of dangerous gas is detected, the fan can be automatically activated immediately to quickly filter the air,both preventivemonitoring functions can be achieved.

Dynamic vision sensors have been investigated to report motion-only images for moving object recognition. Less but essential information helps post-process recognition algorithm reduces computationimproves accuracy. Implement low powerlow latency deep Learning chip based on neuromorphic Intelligence. The neuromorphic obstacle detection algorithm integrates visualproprioceptive signals. The algorithm is characterized by its efficiencylow power consumption. We possess the next-generation in-memory computing AI chipsnext-generation UAV key softwarehardware technology

We develop an asynchronous framework across userkernel spaces for deep learning applications on the improvement of Wi-Fi performanceimplement it in the driver of commodity Intel Wi-Fi cards. Under this framework, we apply deep reinforcement learning to developing an intelligent rate adaptation (RA) algorithm (DRL-RA), which can achieve the highest throughput in varying channel conditions given many rate options of current Wi-Fi technologies. Its on-learning capability can learn how to efficiently approach the best rate from the experiences of its common usage patternenvironment.

National Taipei University of Technology (NTUT) announces the latest approach“embedded smart textiles arrays display module” (ESTAD module) . The ESTAD module involves twoparts,one is circuitthe other is control box. The circuit is to attach the fabric seamlessly,this could be twistedrubbed to fit various design. The control box is designed smaller than the current form to put in the pocketsomewhere hidden in the potential application.

mmW 5G/B5G/6GLEO satellites use large active antenna arrays of more than 1000 elements. A number reduction aided by low cost intelligent panels is developed to reduce at least 60 cost. AiPAiM are used to compact the array with reconfigurability at low power losses. The gains are compensated by phase-reconfigurable AiP/AiM to feed smart multi-beam panels of large apertures. It may steer directional beams by operating the active RF modules tightly fed by AiP/AiM based arrays. Tile architecture can be implemented using multiple AiPs/AiMs for flexible array configurations.

We are proposing a pipeline including de novo genome assemblywhole genome SNP array design to improve the practice in precision medicineprecision agriculture. We design GABOLA, a de novo genome assembly system, combining advantages in leading sequencing platform, to construct completeaccurate individual genomes. GABOLA can resolve large structural variants, fills the gap in human reference genome,avoid the bias from reference genome. We combine the knowledge of population geneticsfunctional information to design whole genome SNP array to aid future genomic study.

We propose a spatial-temporal inference model, which uses a large amount of spatialtemporal data in the city to help governmentsenterprises predict future long-short-term important urban indicator values, such as traffic flow, human mobility, pollution level, number of criminal caseseven commercial profitability. The SIM model exploits IoT to integrate multiple real-time geospatial big data, including population, the flow of people, geographical data, Traffic,real-time sensor values. SIM can make effective predictionsprovide explainability for making decisions.

With the astronomically growing trade flows, customs administrations need effective and explainable methods to detect suspicious transactions. This project presents a novel artificial intelligence-based model named DATE that ranks trade flows in the order of fraud risk and to maximize customs revenue. We confirm the superiority of DATE over state-of-the-art AI models, with a remarkable precision of 92.7% on illegal cases and a recall of 49.3% on revenue after inspecting only 1% of all trade flows. Predictions of DATE are also interpretable from the attention mechanism. We are deploying DATE in Nigeria and Malawi Customs Services, in collaboration with the World Customs Organization (WCO). DATE has been published in ACM KDD 2020, which is an AI top conference.

This technology is a new microarray chip sensing technology that integrates "organic light-emitting diodes", "liquid crystal chemical sensors" and "mobile communication system" into "multifunctional liquid crystal smart cloud sensors". The obtained signals are uploaded to the cloud for multi-dimensional analysis to achieve multiplex detection in one single sample. This sensor device is lightweight, low-cost, simple to operate, and the target-of-interest can be custom-made according to user needs.

1. Demonstrate Virtual Manufacturing/AR/VR technology, integrate product designprocess planning processes (simultaneous engineering). 2. 3D printing design system: Utillized Rhinos built-in calculation editor Grasshopperinfinite element method to generate complex lattice microstructures. The lattices model could directly transfer to all types additive manufacturing machine to fabricate the designs, allowing for rapid prototypinglattices shapes iteration.

This technology uses in-situ optical photointerrupt sensorin-situ acoustic ultrasonic transducer to measure the growth of fouling layer thickness during membrane water treatment. Being the world’s first to combine real-time filter speed attenuation dataphysical mode of clogging, the clogging of film can be instantly analyzed in a smart way which in turn effectively extends its lifetime. T

This project aims to incorporate the state-of-the-art InformationCommunication Technologies (ICT), the Internet of Things (IoT), Big Data techniques in linking every aspect of community-based integrated long-term care (LTC), improving the efficiency of care servicesadministrative process,to realize the idea of Aging in Place emphasized in the Long-term Care Policy 2.0 in Taiwan.

This successful technology is the digital interventions on depression patients based on (1) heart rate variability bio-feedbacks (HRVBs) measured by a novel flexible sensor patch attached on patient’s wrist(2) an APP. An innovative flexible low-power PPG patch has been designed which is capable of providing weeks of high-quality PPG signals which are essential towards accurate estimation of HRV for favorable efficacy of designed digital interventions. Also, An AI model correlating the HRVsand PHQ-9/HDRS scores of depression patients will be built based on collected data.

The core concept of the decision support system is to establish machine learning-based predictive modelsenable their interpretability to support physicians making clinical decisions in practice. The developed technique is part of the capstone project named "Smart Emergency Department," sponsored by the Ministry of ScienceTechnology. The system comprises NTUH (National Taiwan University Hospital) EMR (Electronic Medical Record) importance analysis, accurate clinical quality indicator prediction,similar medical record retrieval. It is expected to improve the patients＇ flowalleviate emergency department crowding. It has been verified in retrospective studieswill officially enter the clinical trial phase this year.

"Four automatic rumor detection models based on artificial intelligencenatural language processing. Rumor Detection on Twitter Using Multiloss Hierarchical BiLSTM with an Attenuation Factor Exploiting Microblog Conversation Structures to Detect Rumors Birds of a Feather Rumor Together? Exploring HomogeneityConversation Structure in Social Media for Rumor Detection Meet The Truth: Leverage Objective FactsSubjective Views for Interpretable Rumor Detection Experimental results show that these four models have greatly improved the accuracy of rumor detection, surpassing other SOTA models."

This project uses AIoT technology to face the occurrence issue of incorrect preｓｃｒｉｐｔion drugs of the drug dispensing phase in hospital dispensing Room. The proposed learning-object-detection based deep technology AI mechanism can automatically identifyverify the correctness of the drugs in the drug bag, thereby significantly improving the accuracy of drug dispensing in Hospital.

Use NLP techniques to realize the automatic coding of ICD10. According to the input of the patient’s age, gender, medical order, admissions, progress note, surgical records, discharge, ICD-10 diagnostic codeICD-10 disposal code, perform machine learning model trainingcode prediction. In addition, the combination codemedical order-related coding rules in practice are used to establish corresponding rules to optimize the accuracy of AI prediction.

Taiwan faces a major water shortage crisis in 2021. Hydrogel as a commercial soil conditioner has the potential to improve soil propertiesreduce water scarcity in growing plants. This technology discovered that environmentally responsive cellulose-based hydrogels have the potential for use as soil conditionersas controlled release devices in horticultureagriculture. Waterfertilizer soil conditioners can be manufactured based on the ecological recycling process. In the future, technology can develop other carriers that require the controlled release of active ingredients.

The Hospital has been investing in rural health care for a long time, providing community intelligence testing equipment on the health care side, providing health care workers to take the measuring equipment with them for real-time measurementdata uploading,providing home physiological measuring equipment, allowing people to take measurements at homeupload the values to the system immediately to achieve personal health management functions. It is hoped that this will reduce the workload of the health center staffprovide interactive health care services to local residents.

Our technology combines optimized semiconductor manufacturing technique with unique biomediator preparation to achieve the first reliable POC biosensing platform. Sensors developed according to this method possess reproducibility, accuracy,stability that meet POC. Our sensors are portable, require low sample volume, do not require sample processing,are extremely suitable for use in POC settings. They can also be integrated into IoT systems to aide in rapid decision making,can be mass produced. Overall, we are the first to achieve accessible, reliable detection at the POC.