• The Journal of Bigdata
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• v.4 no.1
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• pp.119-127
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• 2019

This study explains how to solve engineering problems easily and efficiently by using cloud based big data platform. To do this, we propose a cloud based big data analysis platform. The application helps users easily create models for data analysis using cloud based big data analysis platform. Analytical models modeled using components are analyzed through an analysis engine. Our platform include pre-processing, analysis, and visualization algorithms required for data analysis. Finally, we show an application of effluent concentration in a sewage treatment process.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.689-705
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• 2016

This paper proposed an realtime total monitoring platform for various kind of multi weather radars to analyze and predict weather phenomenons and prevent meteorological disasters. Our platform is designed to process each weather radar data on each radar site to minimize overloads from conversion and transmission of large volumed radar data, and to set observers up the definitive radar data via public framework server separately. By proposed method, weather radar data having different spatial or temporal resolutions can be automatically synchronized with there own spatio-temporal domains on public GIS platform having only one spatio-temporal criterion. Simulation result shows that our method facilitates the realtime weather monitoring from weather radars having various spatio-temporal resolutions without other data synchronization or assimilation processes. Moreover, since this platform doesn't require some additional computer equipments or high-technical mechanisms it has economic efficiency for it's systemic constructions.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.279-291
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• 2024

The "Korea Institute of Geoscience and Mineral (KIGAM) Quake" is a web-based open platform developed for publicly serving seismological data from 61 stations operated by KIGAM in Korea. The service provides meta-information related to observatory sites, sensors, and recorders necessary for utilizing the seismological data, as well as mainly observed continuous and strong-motion waveforms. The data is available through both the web and International Federation of Digital Seismograph Networks (FDSN) web services (open API), a unified data-providing interface in seismology. The platform aims to strengthen its open nature by offering a signal processing function for strong ground motions that can be controlled by user requests. The processed results can be downloaded in ASCII format, designed to meet the increased demands and accessibility in the earthquake engineering field. The platform also offers earthquake research information produced by KIGAM, such as recent major earthquake source information and academic annual report of earthquakes. Additionally, a site flat file was constructed for the geotechnical characteristics of 61 KIGAM station (KGNET) sites based on direct investigations and estimations.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.108-113
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• 2024

The purpose of this study is to analyze user perceptions of tourism platforms through big data. Data were collected from Naver, Daum, and Google as big data analysis channels. Using semantic network analysis with the keyword 'tourism platform,' a total of 29,265 words were collected. The collection period was set for two years, from August 31, 2021, to August 31, 2023. Keywords were analyzed for connected networks using TexTom and Ucinet programs for social network analysis. Keywords perceived by tourism platform users include 'travel,' 'diverse,' 'online,' 'service,' 'tourists,' 'reservation,' 'provision,' and 'region.' CONCOR analysis revealed four groups: 'platform information,' 'tourism information and products,' 'activation strategies for tourism platforms,' and 'tourism destination market.' This study aims to expand and activate services that meet the needs and preferences of users in the tourism field, as well as platforms tailored to the changing market, based on user perception, current status, and trend data on tourism platforms.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1073-1080
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• 2008

A GPS receiver platform has been developed to design an interference rejection filter and the platform is also able to evaluate performance of those filters. This platform consists of RF/IF part, data acquisition part and PC part. The RF/IF part converts RF signals to IF signals, the data acquisition part transmits the IF signals to PC using USB device. The PC part rejects the interferences with a filter and then it does navigation with GPS software receiver. The RF/IF part and data acquisition part had been validated with signal spectrum, and the PC part had been validated with the navigation results of GPS receiver. Finally, the entire platform including interference rejection filter has been confirmed with the navigation results in case that the GPS signals and interference entered this platform. As a result, the GPS receiver operated well against interference with 45dB JSR.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.569-572
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• 2005

This paper proposed the design and implementation of a DSP platform for the various multimedia streaming. The DSP platform synchronizes with host PC to configure DSP and to transmit multimedia streaming through PCI. The suggested DSP platform decodes high-capacity video/audio data using the suggested high-speed FIFO, CPLD and memory interface. The buffer control techniques is proposed in other to avoid the under/over-run of the audio/video data during the audio/video decoding. For the DSP platform test, host PC transmits program stream(PS) that consists of the MPEG-2 video MP@ML and 5.1ch AC3 audio data (Coyote.mov file, half hour running time) to DSP platform. The DSP platform plays continuously back the high sound-quality audio and high-definition video at once.

• Journal of Platform Technology
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• v.9 no.1
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• pp.32-39
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• 2021

Existing environmental measuring devices mainly focus on electromagnetic wave and eco-friendly product certification and durability test, and sensor reliability verification and verification of measurement data are conducted mainly through sensor performance evaluation through type approval and registration, acceptance test, initial calibration, and periodic test. This platform has established an ICT-based environmental monitoring sensor reliability verification system that supports not only performance evaluation for each target sensor, but also a verification system for sensor data reliability. A sensor board to collect sensor data for environmental information was produced, and a sensor and data reliability evaluation and verification service system was standardized. In addition, to evaluate and verify the reliability of sensor data based on ICT, a sensor data platform monitoring prototype using LoRa communication was produced, and the test was conducted in smart cities. To analyze the data received through the system, an optimization algorithm was developed using machine learning. Through this, a sensor big data analysis system is established for reliability verification, and the foundation for an integrated evaluation and verification system is provide.

• The Journal of Bigdata
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• v.8 no.2
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• pp.83-95
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• 2023

Big data analytics and AI play a critical role in the development of smart plants. This study presents a big data platform for plant data and an 'AutoML platform' for AI-based plant O&M(Operation and Maintenance). The big data platform collects, processes and stores large volumes of data generated in plants using Hadoop, Spark, and Kafka. The AutoML platform is a machine learning automation system aimed at constructing predictive models for equipment prognostics and process optimization in plants. The developed platforms configures a data pipeline considering compatibility with existing plant OISs(Operation Information Systems) and employs a web-based GUI to enhance both accessibility and convenience for users. Also, it has functions to load user-customizable modules into data processing and learning algorithms, which increases process flexibility. This paper demonstrates the operation of the platforms for a specific process of an oil company in Korea and presents an example of an effective data utilization platform for smart plants.

• Korean Journal of Computational Design and Engineering
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• v.20 no.4
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• pp.385-400
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• 2015

ISO 15926 is an international standard for the integration and sharing of plant lifecycle data. Plant 3D design data typically consist of logical configuration, equipment specifications and ports, and 3D shape data. This paper presents the method for the ISO 15926-based integration of plant 3D design data. For this, reference data (class, attribute, and template) of ISO 15926 were extended to describe plant 3D design data. In addition to the data model extension, a plant design information integration platform which reads plant 3D design data in ISO 15926 and displays 3D design information was developed. Finally, the prototype platform is verified through the experiment of loading and retrieving plant 3D design data in ISO 15926 with the platform.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.176-185
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• 2018

With the recent development of manufacturing technology and the diversification of consumer needs, not only the process and quality control of production have become more complicated but also the kinds of information that manufacturing facilities provide the user about process have been diversified. Therefore the importance of big data analysis also has been raised. However, most small and medium enterprises (SMEs) lack the systematic infrastructure of big data management and analysis. In particular, due to the nature of domestic manufacturing companies that rely on foreign manufacturers for most of their manufacturing facilities, the need for their own data analysis and manufacturing support applications is increasing and research has been conducted in Korea. This study proposes integrated analysis platform for process and quality analysis, considering manufacturing big data database (DB) and data characteristics. The platform is implemented in two versions, Web and C/S, to enhance accessibility which perform template based quality analysis and real-time monitoring. The user can upload data from their local PC or DB and run analysis by combining single analysis module in template in a way they want since the platform is not optimized for a particular manufacturing process. Also Java and R are used as the development language for ease of system supplementation. It is expected that the platform will be available at a low price and evolve the ability of quality analysis in SMEs.