• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1049-1050
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• 2008

It is difficult to measure the pulse wave in a short time because radial artery position and located depth are different depending on the person. In this paper, the pulse wave measurement system was developed using 3 channel piezoresistive sensor array to detect the most significant pulse wave. Augmentation Index(AI) and Heart Rate(HR) analysis are also available for predicting cardiovascular risks. The developed system is small and easy to use. And it is promising to be used as home healthcare device.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.155-159
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• 1995

A design method that can easily construct intelligent patient monitoring systems is proposed. To achieve the design method, the SES/MB concept and a discrete event-based logic control formalism based on a set theory is introduced. In this control paradigm the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by DEVS model of the system under control. Because data to be used for rule-based symbolic reasoning are to be abstracted, several AI methods are applied the processes. These methods are applied to intelligent patient monitoring systems so that they facilitate transformation from low level raw data to high level linguistic data. Model-based system representations have advantages of reusability, extensibility, flexsibility, independent testability and encapsulation.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.1
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• pp.54-59
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• 2006

The smart space is composed of the wire and/or wireless network, multi-sensor-based environment, and many various controllers. For the smart space, this paper presents a new design method of multirate digital decentralized controller using the intelligent digital redesign technique. In specific, the proposed method is based on the delta-operator and the multirate sampling and takes the form of the LMIs. To shows the feasibility of the suggested method, the computer simulations for Heating, ventilating, and ai. conditioning (HVAC) system are provided.

• Electronics and Telecommunications Trends
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• v.33 no.6
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• pp.107-117
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• 2018

In recent years, with the development of autonomous driving technology, high-performance artificial intelligence computing hardware platforms have been developed that can process multi-sensor data, object recognition, and vehicle control for autonomous vehicles. Most of these hardware platforms have been developed overseas, such as NVIDIA's DRIVE PX, Audi's zFAS, Intel GO, Mobile Eye's EyeQ, and BAIDU's Apollo Pilot. In Korea, however, ETRI's artificial intelligence computing platform has been developed. In this paper, we discuss the specifications, structure, performance, and development status centering on hardware platforms that support autonomous driving rather than the overall contents of autonomous driving technology.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.92-97
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• 2022

Plastics are classified into 7 types such as PET (PETE), HDPE, PVC, LDPE, PP, PS, and Other for separation and recycling. Recently, large corporations advocating ESG management are replacing them with bioplastics. Incineration and landfill of disposal of plastic waste are responsible for air pollution and destruction of the ecosystem. Because it is not easy to accurately classify plastic materials with the naked eye, automated system-based screening studies using various sensor technologies and AI-based software technologies have been conducted. In this paper, NIR scanning devices considering the NIR wavelength characteristics that appear differently for each plastic material and a system that can identify the type of plastic by learning the NIR spectrum data collected through it. The accuracy of plastic material identification was evaluated through a decision tree-based SVM model for multiclass classification on NIR spectral datasets for 8 types of plastic samples including biodegradable plastic.

• Journal of Sensor Science and Technology
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• v.33 no.2
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• pp.78-85
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• 2024

We proposed a method for visual place recognition that represents images using objects as visual words. Visual words represent the various objects present in urban environments. To detect various objects within the images, we implemented and used a zero-shot detector based on a large-scale image language model. This zero-shot detector enables the detection of various objects in urban environments without additional training. In the process of creating histograms using the proposed method, frequency-based weighting was applied to consider the importance of each object. Through experiments with open datasets, the potential of the proposed method was demonstrated by comparing it with another method, even in situations involving environmental or viewpoint changes.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.71-76
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• 2023

In this paper, a humidity sensor using a microstrip patch antenna(MPA) and polyvinyl alcohol(PVA) is studied. PVA is a polymer material whose permittivity changes with humidity, and a rectangular slot is added to the radiating edge of the MPA, which is sensitive to changes in electric field, in order to increase the sensitivity to changes in relative permittivity. After thinly coating the area around the radiating edge with the rectangular slot of the MPA fabricated on a 0.76 mm-thick RF-35 substrate with PVA, the changes in the resonant frequency and magnitude of the MPA's input reflection coefficient are measured when relative humidity is adjusted from 40% to 80% in 10% increments at a temperature of 25 degrees using a temperature and humidity chamber. Experiment results show that when the relative humidity increases from 40% to 80%, the resonance frequency of the antenna' input reflection coefficient decreases from 2.447 GHz to 2.418 GHz, whereas the magnitude increases from -7.112 dB to -3.428 dB.

• Journal of Information Technology Services
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• v.22 no.4
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• pp.97-110
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• 2023

In this study, we propose a technique to automatically generate transfer documents using sensor data from livestock manure transfer systems. The research involves analyzing sensor data and applying machine learning techniques to derive optimized outcomes for livestock manure transfer documents. By comparing and contrasting with existing documents, we present a method for automatic document generation. Specifically, we propose the utilization of Gradient Boosting, a machine learning algorithm. The objective of this research is to enhance the efficiency of livestock manure and liquid byproduct management. Currently, stakeholders including producers, transporters, and processors manually input data into the livestock manure transfer management system during the disposal of manure and liquid byproducts. This manual process consumes additional labor, leads to data inconsistency, and complicates the management of distribution and treatment. Therefore, the aim of this study is to leverage data to automatically generate transfer documents, thereby increasing the efficiency of livestock manure and liquid byproduct management. By utilizing sensor data from livestock manure and liquid byproduct transport vehicles and employing machine learning algorithms, we establish a system that automates the validation of transfer documents, reducing the burden on producers, transporters, and processors. This efficient management system is anticipated to create a transparent environment for the distribution and treatment of livestock manure and liquid byproducts.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.23-29
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• 2022

To detect harmful chemical substances in seawater, we fabricated a prototype sensor and evaluated its performance. The prototype sensor consisted of a detector, housing, and driving circuit. We built the detector by printing an Indium-Tin-Oxide (ITO) nanoparticle film on a flexible substrate, and it had two detection parts for simultaneous detection of temperature and HNS concentration. The housing connected the detector and the driving circuit and was made of Teflon material to prevent chemical reactions that may affect sensor performance. The driving circuit supplied electric power, and display measured data using a bridge circuit and an Arduino board. We evaluated the sensor performances such as response (ΔR), the limit of detection (LOD), response time, and errors to confirm the specification.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.15-23
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• 2020

Automated driving car is drawing attention as a seminal service representing 4th industrial revolution era based on 5G network, AI, IOT and sensor technology. automated driving car is expected to evolve into the final level which does not require driver's input. Drivers are able to consume new additional time in private space. Many industries started to compete to control these time and space. Media industry is expecting quite big change due to the introduction of automated driving cars. This research examines the impact of the media industry and social & institutional issues of automated driving cars based on depth interviews of experts. The introduction of automated driving cars is giving new opportunity for media industry as contents provider. Telcos and IT corporations are expected to compete each other to get the control of infotainment systems of automated driving cars. The reform of current regulations regarding car driving is pointed as important task to protect private information and the introduction of automated driving cars.