• Journal of Sensor Science and Technology
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• v.29 no.6
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• pp.420-426
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• 2020

A metal oxide semiconductor gas sensor is operated by measuring the changes in resistance that occur on the surface of nanostructures for gas detection. ZnO, which is an n-type metal oxide semiconductor, is widely used as a gas sensor material owing to its high sensitivity. Various ZnO nanostructures in gas sensors have been studied with the aim of improving surface reactions. In the present study, the sol-gel and vapor phase growth techniques were used to fabricate nanostructures to improve the sensitivity, response, and recovery rate for gas sensing. The sol-gel method was used to synthesize SnO₂ nanoparticles, which were used as the seed layer. The nanoparticles size was controlled by regulating the process parameters of the solution, such as the pH of the solution, the type and amount of solvent. As a result, the SnO₂ seed layer suppressed the aggregation of the nanostructures, thereby interrupting gas diffusion. The ZnO nanostructures with a sol-gel processed SnO₂ seed layer had larger specific surface area and high sensitivity. The gas response and recovery rate were 1-7 min faster than the gas sensor without the sol-gel process. The gas response increased 4-24 times compared to that of the gas sensor without the sol-gel method.

• The Journal of Bigdata
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• v.6 no.1
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• pp.161-178
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• 2021

The importance of 'Big Data' is increasing to the point that it is likened to '21st century crude oil'. For smart city IoT data, attention should be paid to quality control as the quality of data is associated with the quality of public services. However, data quality indicators presented through ISO/IEC organizations and domestic/foreign organizations are limited to the 'User' perspective. To complement these limitations, the study derives supplier-centric indicators and their priorities. After deriving 3 categories and 13 indicators of supplier-oriented smart city IoT data quality evaluation indicators, we derived the priority of indicator categories and data quality indicators through AHP analysis and investigated the feasibility of each indicator. The study can contribute to improving sensor data quality by presenting the basic requirements that data should have to individuals or companies performing the task. Furthermore, data quality control can be performed based on indicator priorities to provide improvements in quality control task efficiency.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.61-73
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• 2020

Real-time location-sensing technology using location information collected from IoT devices is being applied for safety management purposes in many industries, such as ports. On the other hand, positional error is always present owing to the characteristics of GPS. Therefore, accident-risk detection algorithms must consider positional error. This paper proposes an methodology of calibration for falling object accident-risk-zone approach detection algorithm considering GPS errors. A probability density function was estimated, with positional error data collected from IoT devices as a probability variable. As a result of the verification, the algorithm showed a detection accuracy of 93% and 77%. Overall, the analysis results derived according to the GPS error level will be an important criterion for upgrading algorithms and real-time risk managements in the future.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.51-63
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• 2022

Up-to-date statistics of crop cultivation status is essential for farm land management planning and the advancement in remote sensing technology allows for rapid update of farming information. The objective of this study was to develop a classification model of rice paddy or winter crop fields based on NDWI, NDVI, and HSV indices using Sentinel-2 satellite images. The 18 locations in central Korea were selected as target areas and photographed once for each during summer and winter with a eBee drone to identify ground truth crop cultivation. The NDWI was used to classify summer paddy fields, while the NDVI and HSV were used and compared in identification of winter crop cultivation areas. The summer paddy field classification with the criteria of -0.195

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.3
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• pp.138-151
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• 2023

Korea's port infrastructure is rapidly aging, with old port facilities with more than 30 years of public life expected to surge from about 23% in 2019 to 47% in 2029. Traditional, aging ports lose competitiveness in logistics processing, reducing development around the port and increasing human casualties due to the human resource-based maintenance of the facilities. Therefore, it is necessary to solve this problem by establishing systematic management technology based on a digital twin. This research aimed to present the specific implementation steps of a digital twin reflecting smart port technology through cases of port infrastructure disasters, aging status, and smart ports. The study analyzed the port infrastructure linkage system and created and mapped scenarios essential for digital twin implementation. Three-dimensional (3D) modeling and simulation data for disaster and aging management among existing port infrastructure systems were collected. A digital twin port was implemented with 3D modeling. It implements a port digital twin simulation that links data such as sensing data and image data acquired from the port infrastructure in real time. Implementing a digital twin port for port infrastructure disasters and aging management can secure predictive port infrastructure management and disaster safety

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.151-162
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• 2022

Prefab members have attracted attention because they can be mass-produced in factories through smart construction technology. For prefab prestressed concrete girders, it is important to manage the shapes of the girders properly from production to the pre-installation stage for consistency with the prefab floor plate during the erection process. This paper presents a camber reconstruction method using collocated strain measurements from the top and bottom of the prefab girder. In particular, the camber reconstruction method is applied to measured strain data in which the time-dependent behavior of concrete is considered after the introduction of prestress. Through Monte Carlo numerical simulations, the statistical accuracy of the reconstructed camber for a limited number of sensors, measurement errors, and nonlinear time-dependent behaviors are analyzed and validated.

• Journal of the Korean Geotechnical Society
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• v.39 no.6
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• pp.13-19
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• 2023

Lunar ice is a resource available for future human exploration in deep space and long-term extraterrestrial habitat. However, the origin and nature of lunar ice remains unclear. In addition to remote sensing, international space agencies are competitively planning and conducting missions for lunar surface exploration to determine the existence and resource extent of lunar ice. If a sufficient amount of lunar ice is confirmed, its future in-situ resource utilization is expected to be greatly beneficial. However, due to ice extraction, settlement may occur, which should be taken into account from a geotechnical engineering perspective. Herein, experimental investigations of the potential settlement caused by lunar ice extraction were conducted and different textures of lunar ice were simulated. Consequently, it was confirmed that significant settlement occurs even at the initial water content of ~10% in lunar regolith simulant-ice-mixed soil.

• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.31-56
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• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1162-1167
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• 2003

This paper presents a simple sensor network consists of a group of sensors, RF components, and microprocessors, to perform a distributed sensing and information transmission using wireless links. In the proposed sensor network, though each sensor node has a limited capability and a simple signal-processing engine, a group of sensor nodes can perform a various tasks through coordinated information sharing and wireless communication in a large working area. Using the capability of self-localization and tracking, we show the sensor network can be applied to localization and navigation of mobile robot in which the robot has to be coordinated effectively to perform given task in real time.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.1
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• pp.22-28
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• 2016

Multi-loop control of a boost converter needs a current-sensing circuit to detect the inductor current. Current sensorless multi-loop control reduces the cost, size and weight of the converter. The Luenberger observer (LO) is widely used to estimate the inductor current for current sensorless control of a switching converter. However, the design of the LO-based sensorless multi-loop control has not been well presented, so far. In this paper, a closed-loop characteristics evaluation method is proposed to design an LO-based current sensorless multi-loop control for boost converters. Simulations show evaluations of the closed-loop characteristics. Practical experiments on a digital processor confirm the simulations.