• 한국태양에너지학회 논문집
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• 제29권4호
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• pp.15-21
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• 2009

Since the solar radiation is main input for sizing any solar photovoltaic system and solar thermal power system, it will be necessary to understand and evaluate the insolation data. The Korea Institute of Energy Research(KIER) has begun collecting horizontal global insolation data since May, 1982 and direct normal insolation data since December 1992 at 16 different locations. Because of a poor reliability of existing data, KIER's new data will be extensively used by solar energy system users as well as by research institutes. Among some significant results, the yearly averaged horizontal global insolation was turned out 3.60 kWh/$m^2$/day and the yearly mean 2.62 kWh/$m^2$/day of the direct normal insolation was evaluated for all days.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2016년도 춘계 종합학술대회 논문집
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• pp.255-256
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• 2016

In this paper, we analyze the operations and/or status of our structure which builds the management structure measuring integrated monitoring system based on linked open data in a short term or long term bases. We have applied a novel analyzing method of linked open data to expect what movements can be occurred in the structure, and we improve the monitoring system using an integrated design to solve the drawbacks of conventional types of monitoring. And collecting data through cloud and their reliability can be proved by evaluation of soundness of data amount and their confidence.

• 반도체디스플레이기술학회지
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• 제19권2호
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• pp.51-54
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• 2020

To develop gas-distinguishing sensor system, it is highly required to integrate multiple sensors for effective detection of a single targeted gas or mixture of gases. In addition, it is important to collect the reliable data from individual sensors into one integrated measuring device. Collecting the data of toxic gases on the spot should be done without inhalation. We suggest simple wirelessly running system for data collection that guarantees both reliability of data sources and safety. Here, we made a multi-gas measuring instrument(device) combined with Bluetooth module which provides a safe and precise big data accumulation system.

• 한국지반환경공학회 논문집
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• 제11권12호
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• pp.19-25
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• 2010

기초조사란 위험비탈면에 실시하는 정밀조사와는 달리 비탈면의 현황을 파악하고자 실시한다. 과거 기초조사자료를 토대로 하여 전국 국도변에 분포하고 있는 비탈면의 일반현황을 분석하였다. 또한 비탈면 일반 현황과 붕괴가 발생한 비탈면에 대한 비교분석을 통하여 유지관리 시 중요한 사항에 대하여 연구를 수행하였다. 10년 전 붕괴가 발생된 자료와 현재 붕괴된 자료를 통하여 비탈면 파괴 유형 및 대책공법의 적용에 대한 변화 추이를 분석하였다. 추후 원인별 붕괴형태 분석 및 대책공법과의 연관성을 연구하려 한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.353-355
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• 2018

The aim of this paper is Although a large amount of sensor data is generated in the manufacturing process of a manufacturing company and the necessity of utilizing sensor data is felt, there is a real difficulty in collecting a large amount of sensor data and introducing analysis / service. Using W3C Web document standard format, XML based technology, it collects data to provide production status and equipment status information, and researches middleware for sensor data processing that user can analyze.

• Architectural research
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• 제20권4호
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• pp.109-120
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• 2018

In the context of ever-faster urbanization, cities are becoming increasingly complex, and data collection to understand such complex relationships is becoming a very important factor. This paper focuses on the lighter weight of the method of collecting urban data, and studied how to use such complementary data collection using crowdsourcing. Especially, the method of converting mobile acceleration sensor information to urban trip information by combining with locational information was experimented. Using the parameters for transportation type classification obtained from the research, information was obtained and verified in Singapore and Zurich. The result of this study is thought to be a good example of how to combine raw data into meaningful behavior information.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2018년도 하계학술대회
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• pp.45-46
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• 2018

This paper focuses on human activities monitoring problem using onboard smartphone sensors as data generator. Monitoring such activities can be very important to detect anomalies and prevent disease from patients. Machine learning (ML) algorithms appear to be ideal approaches to use for processing data from smartphone to get sense of how to classify human activities. ML algorithms depend on quality, the quantity and even more important, the properties or features, that can be learnt from data. This paper proposes a mobile virtual reality visualization system that helps to view data representation in a very immersive way so that its quality and discriminative characteristics may be evaluated and improved. The proposed system comes as well with a handy data collecting application that can be accessed directly by the VR visualization part.

• International Journal of Computer Science & Network Security
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• 제21권2호
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• pp.221-228
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• 2021

Recent improvements on the quality, fidelity and availability of biometric data have led to effective human physical activity detection (HPAD) in real time which adds significant value to applications such as human behavior identification, healthcare monitoring, and user authentication. Current approaches usually use machine-learning techniques for human physical activity recognition based on the data collected from wearable accelerometer sensor from a single wearable smart device on the user. However, collecting data from a single wearable smart device may not provide the complete user activity data as it is usually attached to only single part of the user's body. In addition, in case of the absence of the single sensor, then no data can be collected. Hence, in this paper, a continuous HPAD will be presented to effectively perform user activity detection with mobile service infrastructure using multiple wearable smart devices, namely smartphone and smartwatch placed in various locations on user's body for more accurate HPAD. A case study on a comprehensive dataset of classified human physical activities with our HAPD approach shows substantial improvement in HPAD accuracy.

• Journal of Multimedia Information System
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• 제8권1호
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• pp.61-68
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• 2021

The paper is based on data collected from the Amazon website (specific in the Handmade's Category) to understand and analyze Vietnamese artisans' business context. Data analysis is also applied to determine the factors that bring success Handmade products and compare products of the same industry among competitors to find out potential products. By collecting data from Amazon and analyzing the data, we extracted useful information for online business developers. Besides, the list of potential products in Handmade sector can be referred to improve the business and compete with competitors. This paper also proposes solutions to help Vietnamese products become more appealing to international customers on the Amazon website.

• Journal of Positioning, Navigation, and Timing
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• 제12권1호
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• pp.37-42
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• 2023

Wi-Fi Received Signal Strength Indicator (RSSI) is considered one of the most important sensor data types for indoor localization. However, collecting a RSSI fingerprint, which consists of pairs of a RSSI measurement set and a corresponding location, is costly and time-consuming. In this paper, we propose a Wi-Fi RSSI learning technique without true location data to overcome the limitations of static database construction. Instead of the true reference positions, inertial measurement unit (IMU) data are used to generate pseudo locations, which enable a trainer to move during data collection. This improves the efficiency of data collection dramatically. From an experiment it is seen that the proposed algorithm successfully learns the unsupervised Wi-Fi RSSI positioning model, resulting in 2 m accuracy when the cumulative distribution function (CDF) is 0.8.