• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.71-78
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• 2022

This paper proposes an algorithm for 3D object detection by processing point cloud data of 3D LiDAR. Unlike 2D LiDAR, 3D LiDAR-based data was too vast and difficult to process in three dimensions. This paper introduces various studies based on 3D LiDAR and describes 3D LiDAR data processing. In this study, we propose a method of processing data of 3D LiDAR using clustering techniques for object detection and design an algorithm that fuses with cameras for clear and accurate 3D object detection. In addition, we study models for clustering 3D LiDAR-based data and study hyperparameter values according to models. When clustering 3D LiDAR-based data, the DBSCAN algorithm showed the most accurate results, and the hyperparameter values of DBSCAN were compared and analyzed. This study will be helpful for object detection research using 3D LiDAR in the future.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.11-16
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• 2022

Efforts to incorporate blockchain into various fields are continuing as cryptocurrency transactions become more active. Blockchain has the characteristic that once recorded facts cannot be modified or deleted. Due to these characteristics, the use in the field of recording and proving certain facts, such as voting or proof of ownership, is attracting attention. In this paper, users who want to participate in the transaction process using private blockchain, one of the types of blockchain, are divided into real estate brokers, building owners, and purchasers (lessors), and roles are assigned to each user. In addition, we would like to propose a system to increase reliability through the participation of institutions. Through this, we intend to not only present a real estate transaction system that prevents damage from real estate fraud related to false sales and fraudulent contracts, but also enhances reliability and contributes to finding ways to utilize blockchain in the future.

• Journal of Internet of Things and Convergence
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• v.8 no.3
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• pp.47-54
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• 2022

The purpose of this study was to examine the mediating effect of family organization patterns of family resilience on the relationship between parenting stress and parenting efficacy. A total of 263 participants who have children with disabilities participated in this study by responding to the following questionnaires: Parenting Stress Index(PSI), Family Resilience Scale, Parenting Efficacy Scale. The collected data were analyzed using SPSS 25.0 and Amos 22.0. The main findings were as follows. There was a significant partial mediating effect of family organization patterns of family resilience on the relationship between parenting stress and parenting efficacy. The results of this study can provide useful information for family who have children with disabilities. suggestions for future study were discussed.

• Journal of Internet of Things and Convergence
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• v.8 no.4
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• pp.9-15
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• 2022

NAND flash memory is used as a medium for various storage devices due to its high data processing speed with low power consumption. However, since the read processing speed of data is about 10 times faster than the write processing speed, various studies are being conducted to improve the speed difference. In particular, flash dedicated buffer management policies have been studied to improve write speed. However, SSD(solid state disks), which has recently been used for various purposes, is more vulnerable to read performance than write performance. In this paper, we find out why read performance is slower than write performance in SSD composed of NAND flash memory and study buffer management policies to improve it. The buffer management policy proposed in this paper proposes a method of improving the speed of a flash-based storage device by analyzing the pattern of read data and applying a policy of pre-reading data to be requested in the future from NAND flash memory. It also proves the effectiveness of the read-ahead policy through simulation.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.249-257
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• 2022

In recent years, if we order food by easily accessing the online market with our smartphone, we can receive the product in a fresh state at dawn the next day. Cold chain is an industry that can create high added value because it has both the characteristics of general logistics and sensitivity to temperature. Based on the electrical specifications derived from the reefer container capacity requirement investigation, we proved that power supply to up to 33 reefer containers can be made by using three additional auxiliary power supplies which are applied for freight trains in Korea. In this paper, we conducted a research on a design of power supply system for freight train reefer container based on simulation as a basic research necessary for low-temperature distribution and cold chain construction based on the reefer container railroad. Consequently, the simulation was conducted using the three-phase inverter diagram in PSIM and the SVPWM (3-harmonic injection method) control technique, and it was verified that the required power voltage was satisfied with 622V_dc, which is lower than the input voltage of general SPWM of 718V_dc. The details of this paper could be used as a foundational study for constructing cold chains based on a reefer container dedicated to freight trains in the future.

• Journal of Internet of Things and Convergence
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• v.8 no.3
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• pp.63-68
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• 2022

Due to COVID-19, many paradigm shifts in existing manufacturing facilities and the expansion of non-face-to-face services are accelerating worldwide. A representative technology is digital twin technology. Such digital twin technology, which existed only conceptually in the past, has recently become feasible with the construction of a 5G-based network. Accordingly, this paper designed and implemented a part of the USB process to enable digital twins based on OPC UA communication, which is a standard interlocking structure, between real object objects and virtual reality-based USB process in accordance with this paradigm change. By reflecting the physical characteristics of real objects together, it is possible to simulate real-time synchronization of these with real objects. In the future, this can be applied to various industrial fields, and it is expected that it will be possible to reduce costs for decision-making and prevent dangerous accidents.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.95-101
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• 2023

Globally, the importance of utilization and management of marine spatial information is being maximized, and analyzing such data is emerging as a major driving force for R&D. In Korea, it is expected that collecting marine data from the past to the present and extracting its value will play an important role in the development of science in Korea in the future. In particular, marine static data constitutes a huge big database, and it is necessary to store and store the collected data without loss as high data collection costs and high-level observation techniques are required. In addition, the Disaster Safety Intelligence Convergence Center's "Marine Digital Twin Establishment and Utilization-Based Technology Research" task requires collection and analysis of marine data, so this paper conducts a current status survey of static marine data. And we present a series of algorithms that collect and store them in a database.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.117-123
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• 2023

While applying new digital technologies, interest in software and artificial intelligence is quite high. In particular, many changes are being made for the development of software and artificial intelligence in the field of education. From 2025, software and artificial intelligence-related curricula will be applied to public education in elementary, middle and high schools. The Ministry of Education is also conducting various camps to experience software and artificial intelligence in various ways in elementary, middle and high schools before they are applied to public education. Several platforms for experience camps related to software and artificial intelligence are also being used. In this study, we intend to increase the educational efficiency of the learning method for software and artificial intelligence to be developed in the future by designing a model for software and artificial intelligence experiential learning platforms.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.65-76
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• 2023

This paper identifies the aspects of living environment elements (PM^2.5, PM¹⁰, Noise) throughout Seoul and the urban characteristics that affect them by utilizing the big data of the S-Dot sensors in Seoul, which has recently become a hot topic. In other words, it proposes a big data based urban computing research methodology and research direction to confirm the relationship between urban characteristics and living environments that directly affect citizens. The temporal range is from 2020 to 2021, which is the available range of time series data for S-Dot sensors, and the spatial range is throughout Seoul by 500mX500m GRID. First of all, as part of analyzing specific living environment patterns, simple trends through EDA are identified, and cluster analysis is conducted based on the trends. After that, in order to derive specific urban planning factors of each cluster, basic statistical analysis such as ANOVA, OLS and MNL analysis were conducted to confirm more specific characteristics. As a result of this study, cluster patterns of environment elements(PM^2.5, PM¹⁰, Noise) and urban factors that affect them are identified, and there are areas with relatively high or low long-term living environment values compared to other regions. The results of this study are believed to be a reference for urban planning management measures for vulnerable areas of living environment, and it is expected to be an exploratory study that can provide directions to urban computing field, especially related to environmental data in the future.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.47-56
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• 2023

Hydrogen energy is an eco-friendly energy that produces heat and electricity with high energy efficiency and does not emit harmful substances such as greenhouse gases and fine dust. In particular, smart hydrogen energy is an economical, sustainable, and safe future smart hydrogen energy service, which means a service that stably operates based on 'data' by digitally integrating hydrogen energy infrastructure. In this paper, in order to implement a data-based hydrogen charging station demand forecasting model, three hydrogen charging stations (Chuncheon, Sokcho, Pyeongchang) installed in Gangwon-do were selected, supply and demand data of hydrogen charging stations were secured, and 7 machine learning and deep learning algorithms were used. was selected to learn a model with a total of 27 types of input data (weather data + demand for hydrogen charging stations), and the model was evaluated with root mean square error (RMSE). Through this, this paper proposes a machine learning-based hydrogen charging station energy demand prediction model for optimal hydrogen energy supply and demand.