Sensor

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.

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.

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.

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

The TSRI biomedicalepidemic prevention sensor chip platform uses multi-functional integrated design, with advanced sensorchip design technologies integrating with AI systems, to achieve the goal of diversified epidemic prevention. The platform is open for R&D teams from industryuniversities to develop genetic engineering modification of specific virus typesestablish DNA identification technology, as well as to accelerate development cycle for emerging virus detectorsshorten the virus detection time.

Here, we introduce an electricity-free centrifuge platform based on a manual centrifuge. The provided centrifugal force is sufficient to produce a plasma purity of 99 separated in as little as 2−3 min. We then performed an immunoassay on a paper devicethe results were observed by a portable reader. As a result, the detection limit of the C-Reactive Protein is 1 ng/mL, with a total turnaround time of 7 min.

This technique combines more than one AI models to precisely predict current under noisy data from current sensoroptimizes speed rate based on this AI forecasting model. At the same time, it considers the practical requirementslimitations of workpiece surface roughness, tool machine current load, etc. This technique provides decision supports for optimizing parameters of CNC milling machine to keep high efficiencyenhance energy conservation.

Searchlight is composed to high brightness redgreen LEDs. The message of Morse code is transmitted through LED colorlengths of ”on/off” time in human-machine interface. CCD image sensor integrated with LEDs receives light signal of LED from another ship,then identify the real message through the image recognition software.

Based on deep learning camera/radar object detectiontracking technology, the proposed road side unit (RSU) system has achieved over 95 vehicle detection accuracy within 100m detection range in the processing performance of 10fps under nVidia Jetson Xavier platform. Compared to the 32-beam lidar based RSU, the proposed RSU achieves 97 reduction of sensor cost that exhibits high competitiveness in deployment cost. The proposed RSU system has been verified in fieldswe are now cooperating with an industry partner to deploy the RSU system in both TainanTao-Yuan cities.

Within 10 years, Taiwan will become a super senior society with the proportions in silver hairs of more than 20. Thus, a high-throughputsmart platform with bio-physiology-marker panels is developed for PD progression by combining the bio-medicalphysical sensors, SPRsmart circuit design, leading to a new UPDRS for a more accurateearly diagnosis of a physician.

This technology aims to automatically extractdefine features from a data-driven perspective through a series of data engineering, machine learningensemble learning technologies via the big data collected from equipment sensorsquality characteristic measurement results. For products that have no quality measurement, a virtual metrology resultpredicted confidence score are provided as a decision-making basis for process control.

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.

This work presents a low powersecure IoT communication scheme. A physical unclonable function (PUF) based mutual authentication scheme in conjunction with a trusted third party (TTP),the low power transceiver with secure wake-up mechanism are integrated for networkhardware security thereby enabling to extend the battery lifetimeensuring reliability for the IoT systems.

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.