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.

This multi-sensing system has pH range in 3 – 13temperature resistance of 2 Ω/°C. The conductivity part can clearly distinguish the conductivity of different liquids. This multi-sensor has good stabilitycan be applied to different water bodies in the future,combined with the cloud system, provides a intelligent detection methods.

The environmental information is very important to the human life, the proposed technologies of Environment Sensing Hub including: (1) Air sensing hub: temperature sensor, humidity sensor, pressure sensor, infrared sensor, noise sensor (microphone), PM 2.5 sensor (2) Water sensing hub: heavy metal ion sensor, spectrochip

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.

"In this project, the proposed technologies of Environment Sensing Hub including： (1) Air sensing hub：integrate H/T/P sensor, PM 2.5 sensorwireless multiplexing module for system-on-package (SiP)system-on-chip (SoC) (2) Water sensing hub：heavy metal ion sensor (modules integration, startup company), spectrochip (systems integration, startup company)"

The smart graphene (Gr) sensor developed by this team is self-assembly arranged through Gr. No traditional polarization process is further required due to use of high conductivity of Gr. Further, because of the conductivity of the Gr sensor itself, no additional electrodes are required for collecting the mechanical-electric signals.The process of manufacturing the piezoelectric film can be simplifiedthe cost of process reduced. Moreover, the Gr sensor can be directly coated on materials with different curved shapes and, the sensitivity of the direct-coated sensor can be greatly enhanced.

This technology develops an intelligent surgical pressure detection system, including a pressure sensing element embedded in a surgical cotton pad, a signal reading device,a big data analysis database. The measurement data can be transferred to the AI big data database. Using AI technology, the surgeon＇s force can be recognized in real timethe calculation result can be immediately returned to the system APP. Let the surgeon who performs the operation get the most real-time information, which can avoid organ damage during the operation,effectively protect the safety of patientsthe rights of physicians.

Devices with physical flexibilitystretchability have attracted a great deal of interest for use in wearable electronic technologylarge-area electronics, including displays, energy harvesters, energy storage devices, distributed sensor networks,Internet of Things applications. The present invention relates to methods for growingtransferring single-crystal III-nitride nanorodstwo dimensional transition metal dichalcogenides (2D TMDs) nanostructures,devices having the transferred nanostructures for flexible device, microLED,3DIC fabrications.

In this study, the embedded LiDARAI recognition of smart headlight for autonomous driving is demonstrated. At driving process, the vehicle can provide artificial intelligence to identify the type, distancespeed of the object to be measured based on the fusion data of the LiDAR point cloudoptical image of the environment,then feedback to the headlight control system. Finally, this smart headlight would perform the suitable lighting mode during the daynightfit the automotive lamp safety regulationsstandards (ECE R112SAE J3069).

Although masks protect us from COVID-19, they cover a substantial portion of the face,eliminates important facial expressions during communications. EmoMask is a human-AI collaborative mask that mediates these interactions in mask-wearing environments through emotion-aware sensorsAI algorithms, which works with humans to create facial expressions. The EmoMask system identifiesdifferentiates expressions using TinyML-based AI algorithm,conducts real-time classificationsregressions to create matching facial expressions during a communication while faces are covered.

The self-powered sensing system realizes self-powered wireless wearable pressure sensing modules, self-powered intelligent environment sensing robots,self-powered smart window, which can carry out self-powered sensing signals combined with the transmission of the Internet of Things. Functions such as medical monitoring aidsautomated environmental quality sensing. In the future, this system opens a window towards automatic monitoring of environmental analysispersonal smart healthcare.

Our system uses wireless insole in the shoes to measure foot plantar pressure of athletes.

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.

This technology is used micro-electro-mechanical systems combined nanomaterials and micro-heater systems, because the interdisciplinary integrated manufacturing technologies are used to make miniaturized sensor elements, which are equipped with bluetooth functions of algorithms and detection devices to monitor the ketones gas concentration during patient breathing applied in healthy care.

The objective of this project is to develop a portablewireless urine detection systemplatform for prevention of cardiovascular disease. The main idea is to develop a system-on-chip, a microelectrodemicrochannel chip to detect biomarkers concentrations in urine. And then, it will be wirelessly transmitted to a smart application platform to evaluate user’s cardiovascular status.

Through patented wearable sensor fusion technology, human 3D motions can be captured in real-time which allow 7-DOF robotic armdexterous robotic hand to perform anthropomorphic motiongrasping action. Integrated with eye-in-hand visual module, the adaptive gripper can intelligently decide optimal grasping strategy to ensure success grasping of arbitrary shape of objects in smart manufacturing applications.

Smallsensitive, high temperature resistant, acidalkali resistanttransparent bending sensor.

"Tool replacementtool life diagnosis" in smart manufacturing is a key link between the quality of workpiecethe efficiency of the manufacturing process, so it is an indicator of the operating efficiency of machine tools. This technology combines on-site monitoring data, laboratory analysisdeep learning to provide best tool selectionprocessing parameter combinations for

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

The system consists of a racket sensor, a smartphone App, and the IoT shuttlecock serving machines. Data of the 3-axis inertial sensor will be sent to the smartphone via Bluetooth for analysis. The App can recognize 7 stroke activities, including clear, cut, drive, lob, rush, net play, and smash using machine learning algorithms, while the speed, force, and stroke times are recorded at the same time. The App also enables the user to set parameters of the serving machines for assigning shot placements and serving schedules.

1.Low-Power Processing-in-sensor CMOS Image Sensor 2.Implementation of Low-PowerLow-Latency Deep Learning Chip based on Neuromorphic Intelligence (collaborated with MOST 108-2622-8-007-009) 3.Development of Neuromorphic Chip based on The Fruit Fly VisualSpatial Sensory Systems 4.Hardware-Software Co-Design for Neuromorphic AI Chips

This technique uses Tainan 11 (TN11), which occupies about 70 of the rice planting area in Taiwan. Building the early watering warning system of crops by combining the physiological indicators of rice with environmental dataartificial intelligence technology. The system can analyzepredict the impending water shortage for rice in advanceissue drought warning immediately. Therefore, decision makers can give the timelyappropriate amount for rice irrigationimprove the efficiency of using waterreducing the cost of farmersfarming losses.

This technology integrates acoustic-optical sensing calculationrecognition information,uses hydrophones to estimate the state of dynamic targetsvisually recognizelocate the dynamic target for vehicle motion control. The fusion acoustic-optical sensing architecture can be used according to the target statecharacteristics. By calculatingadapting to the environmenttarget state characteristics, the exploration tasks will be performed.

Our IoT of food allergen detection system has high sensitivityspecificity by magnetic nano-beads with advanced material coating. This advanced material successful inhibit biofouling in biosensor system. Other than this, Our system combine nanotechnology, biotechnology, IoTAI model. Device is small any easily carry to anywhere.

This project developed a CMOS Image Sensor (CIS) for the 2nd generation remote sensing satellite,its main achievement is to improve the ground resolution (also known as the Ground Sampling Distance, GSD) from 2 meters to sub-meter. The 12-cm large size chip of CMOS image sensor is implemented using Back-Side Illumination (BSI) CIS technology with mask stitching technologyutilizing the CMOS Time Delay Integration (CMOS TDI) technology in this design.

Based on the mass production technique to fabricate 2D materials developed by our group, efficient gas sensors against NOx with sensitivity of 100 ppb are successfully demonstrated. In comparison to international competitors, our products exhibit superior sensitivityselectivity. Furthermore, the technique would be extended to other 2D materials to fabricate various gas sensors against multiple target gases. The integration with internet of things would then open new feasibilities for early monitoring in environmental pollutionhuman safety.

A CMOS image sensor is developed for the national space organization (NSPO) 3rd generation high-resolution remote sensing satellite,the main achievement is its capability to satisfy the demanded ground resolution of 0.5 m. This CMOS image sensor with a new time delay integration circuit is implemented using Back-Side Illumination CIS 0.13 μm technology. The anti-radiation capability of the chip is also boosted to extend the lifetime of the chip. Measurement systemdata analysis programs are developed to provide performance parameters of the proposed CMOS image sensor.

The smart glove was made by soft force sensor with the multi-walled carbon nanotube cast in the mesh structurecombined with an interdigitated electrode together, then used AC/DC conversionspace calculation to establish the interactive virtual reality(VR) somatosensory system under the wireless. The recipient can achieve the same feedback as the demonstrator＇s behaviorskills in VR.

The electrochemical sensor can detect bioaminesall amino acids without chemically labeling proceduresenzymatic catalysisbe capable of performing the measurement in pH-varied solutions . The electrodes can be modified with a specific membrane for the selective detection of histamineintegrated with a separation device to perform high selective detection of multi-analytes.

This project is used for advanced driver assistance systems (ADAS)automatic driving. At present, our project will use a more sensitive CMOS single photon detector array to reduce the number of photons required for detection to less than ten, in order to break through the cost barriers of applications of LiDARestablish low-cost, high-performance LiDAR modules.