• Title/Summary/Keyword: IoT 기반 관리

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Development of Accident-prevention Smart Monitoring System for Woman Diver using Zigbee Module and GPS Sensor (Zigbee와 GPS를 이용한 해녀 사고예방 스마트 모니터링 시스템 개발)

  • Choi, Min Ho;Kim, Young Sang
    • Smart Media Journal
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    • v.5 no.3
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    • pp.74-80
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    • 2016
  • In this paper, we propose an accident-prevention smart monitoring system for Haenyeo(Woman diver) using Zigbee module and GPS sensor. This system can collect such information as the diving location, the body temperature, the depth of diving, and the diving time of a Woman diver working under the water and then respond immediately to an accident occurring. The research developed a smart Teawak and smart swimming goggles which can measure the state of a Woman diver and her diving activities. Smart Teawak, the buoy tool while a Woman diver is collecting seafoods under water, is able to receive GPS and transmit the data from smart swimming goggles and Zigbee Module to IHSS(IoT based Haenyeo Safety service Software) server. In addition, IHSS, a responsive web, provides the diving location and the state of a Woman diver on the smart phone. As a result, the system will be useful in the aspects of Woman diver' health care and the safety, furthermore, which will significantly contribute to global marketing of Woman diver with its being designated as a UNESCO intangible cultural asset.

UAV and LiDAR SLAM Combination Effectiveness Review for Indoor and Outdoor Reverse Engineering of Multi-Story Building (복층 건물 실내외 역설계를 위한 UAV 및 LiDAR SLAM 조합 효용성 검토)

  • Kang, Joon-Oh;Lee, Yong-Chang
    • Journal of Cadastre & Land InformatiX
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    • v.50 no.2
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    • pp.69-79
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    • 2020
  • TRecently, smart cities that solve various problems in cities based on IoT technology are in the spotlight. In particular, cases of BIM application for smooth management of construction and maintenance are increasing, and spatial information is converted into 3D data through convergence technology and used for safety diagnosis. The purpose of this study is to create and combine point clouds of a multi-story building by using a ground laser scanner and a handheld LiDAR SLAM among UAV and LiDAR equipment, supplementing the Occluded area and disadvantages of each technology, examine the effectiveness of indoor and outdoor reverse design by observing shape reproduction and accuracy. As a result of the review, it was confirmed that the coordinate accuracy of the data was improved by creating and combining the indoor and outdoor point clouds of the multi-story building using three technologies. In particular, by supplementing the shortcomings of each technology, the completeness of the shape reproduction of the building was improved, the Occluded area and boundary were clearly distinguished, and the effectiveness of reverse engineering was verified.

Vaccine Cold Chain Monitoring System Using IoT Vaccine Fridge for Developing Countries (IoT 백신 냉장고를 사용한 개발도상국 백신 콜드체인 모니터링 시스템)

  • Lyu, Jang-Hyeon;Park, Samuel;Yu, Jong-Ha;Wang, Xin-Lin;Im, Hyuck-Soon;Rhee, Hyop-Seung;Ahn, Sung-Hoon
    • Journal of Appropriate Technology
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    • v.7 no.1
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    • pp.26-32
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    • 2021
  • In the process of vaccine delivery and vaccination, temperature is mostly controlled by an insulated containers containing ice. Moreover, amount of wasted vaccine is significant because the temperature of the vaccine is not properly controlled. A core challenge of vaccination is temperature data monitoring, since it is critical for managing and operating strategical vaccination by health organizations. In this research, a real-time monitoring vaccine carrier system was developed. Temperature, location, and power consumption data of the vaccine carrier were monitored and working performances of the vaccine carrier were tested in both Korea and Tanzania (Arusha and Kilimanjaro regions). For both places, Short Message Service (SMS) communication method was used to send information of the carrier's status. As a result, the monitoring system was able to transmit and receive real-time data of the vaccine carrier status while the vaccine carrier was tested. The vaccine status data can be accessed from any location through the cloud server and web-based user interface.

A Study on a Smart City Supply Chain Security Model Based on Zero-Trust (제로 트러스트(Zero-Trust) 기반의 스마트시티 공급망 보안모델 연구)

  • Lee, Hyun-jin;Son, Kyung-ho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.1
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    • pp.123-140
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    • 2022
  • Recently, research on solving problems that have introduced the concept of smart city in countries and companies around the world is in progress due to various urban problems. A smart city converges the city's ICT, connects all the city's components with a network, collects and delivers data, and consists of a supply chain composed of various IoT products and services. The increase in various cyber security threats and supply chain threats in smart cities is inevitable, in addition to establishing a framework such as supply chain security policy, authentication of each data provider and service according to data linkage and appropriate access control are required in a Zero-Trust point of view. To this end, a smart city security model has been developed for smart city security threats in Korea, but security requirements related to supply chain security and zero trust are insufficient. This paper examines overseas smart city security trends, presents international standard security requirements related to ISMS-P and supply chain security, as well as security requirements for applying zero trust related technologies to domestic smart city security models.

MLOps workflow language and platform for time series data anomaly detection

  • Sohn, Jung-Mo;Kim, Su-Min
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.11
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    • pp.19-27
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    • 2022
  • In this study, we propose a language and platform to describe and manage the MLOps(Machine Learning Operations) workflow for time series data anomaly detection. Time series data is collected in many fields, such as IoT sensors, system performance indicators, and user access. In addition, it is used in many applications such as system monitoring and anomaly detection. In order to perform prediction and anomaly detection of time series data, the MLOps platform that can quickly and flexibly apply the analyzed model to the production environment is required. Thus, we developed Python-based AI/ML Modeling Language (AMML) to easily configure and execute MLOps workflows. Python is widely used in data analysis. The proposed MLOps platform can extract and preprocess time series data from various data sources (R-DB, NoSql DB, Log File, etc.) using AMML and predict it through a deep learning model. To verify the applicability of AMML, the workflow for generating a transformer oil temperature prediction deep learning model was configured with AMML and it was confirmed that the training was performed normally.

A Study on the Inference of Detailed Protocol Structure in Protocol Reverse Engineering (상세한 프로토콜 구조를 추론하는 프로토콜 리버스 엔지니어링 방법에 대한 연구)

  • Chae, Byeong-Min;Moon, Ho-Won;Goo, Young-Hoon;Shim, Kyu-Seok;Lee, Min-Seob;Kim, Myung-Sup
    • KNOM Review
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    • v.22 no.1
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    • pp.42-51
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    • 2019
  • Recently, the amount of internet traffic is increasing due to the increase in speed and capacity of the network environment, and protocol data is increasing due to mobile, IoT, application, and malicious behavior. Most of these private protocols are unknown in structure. For efficient network management and security, analysis of the structure of private protocols must be performed. Many protocol reverse engineering methodologies have been proposed for this purpose, but there are disadvantages to applying them. In this paper, we propose a methodology for inferring a detailed protocol structure based on network trace analysis by hierarchically combining CSP (Contiguous Sequential Pattern) and SP (Sequential Pattern) Algorithm. The proposed methodology is designed and implemented in a way that improves the preceeding study, A2PRE, We describe performance index for comparing methodologies and demonstrate the superiority of the proposed methodology through the example of HTTP, DNS protocol.

Implementation of Smart Automatic Warehouse to Improve Space Utilization

  • Hwa-La Hur;Yeon-Ho Kuk;Myeong-Chul Park
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.171-178
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    • 2023
  • In this paper, we propose a smart automated warehouse to maximize space utilization. Previous elevator-type automatic warehouses were designed with a maximum payload of 100kg on trays, which has the problem of extremely limiting the number of pallets that can be loaded within the space. In this paper, we design a smart warehouse that can maximize space utilization with a maximum vertical stiffness of 300kg. As a result of the performance evaluation of the implemented warehouse, the maximum payload was 500.6kg, which satisfied the original design and requirements, the lifting speed was 0.5m/s, the operating noise of the device was 67.1dB, the receiving and forwarding time of the pallet was 36.92sec, the deflection amount was 4mm, and excellent performance was confirmed in all evaluation items. In addition, the PLC control method, which designs the control UI and control panel separately, was integrated into the PC system to improve interoperability and maintainability with various process management systems. In the future, we plan to develop it into a fully automatic smart warehouse by linking IoT sensor-based logistics robots.

Generalized On-Device AI Framework for Semantic Segmentation (의미론적 분할을 위한 범용 온디바이스 AI 프레임워크)

  • Jun-Young Hong;Kyung-Jae Lee
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.5
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    • pp.903-910
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    • 2024
  • Complex semantic segmentation tasks are primarily performed in server environments equipped with high-performance graphics hardware such as GPUs and TPUs. This cloud-based AI inference method operates by transmitting processed results to the client. However, this approach is dependent on network communication and raises concerns about privacy infringement during the process of transmitting user data to servers. Therefore, this paper proposes a Generalized On-Device Framework for Semantic Segmentation that can operate in mobile environments with high accessibility to people. This framework supports various semantic segmentation models and enables direct inference in mobile environments through model conversion and efficient memory management techniques. It is expected that this research approach will enable effective execution of semantic segmentation algorithms even in resource-constrained situations such as IoT devices, autonomous vehicles, and industrial robots, which are not cloud computing environments. This is expected to contribute to the advancement of real-time image processing, privacy protection, and network-independent AI application fields.

Implementation of the Large-scale Data Signature System Using Hash Tree Replication Approach (해시 트리 기반의 대규모 데이터 서명 시스템 구현)

  • Park, Seung Kyu
    • Convergence Security Journal
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    • v.18 no.1
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    • pp.19-31
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    • 2018
  • As the ICT technologies advance, the unprecedently large amount of digital data is created, transferred, stored, and utilized in every industry. With the data scale extension and the applying technologies advancement, the new services emerging from the use of large scale data make our living more convenient and useful. But the cybercrimes such as data forgery and/or change of data generation time are also increasing. For the data security against the cybercrimes, the technology for data integrity and the time verification are necessary. Today, public key based signature technology is the most commonly used. But a lot of costly system resources and the additional infra to manage the certificates and keys for using it make it impractical to use in the large-scale data environment. In this research, a new and far less system resources consuming signature technology for large scale data, based on the Hash Function and Merkle tree, is introduced. An improved method for processing the distributed hash trees is also suggested to mitigate the disruptions by server failures. The prototype system was implemented, and its performance was evaluated. The results show that the technology can be effectively used in a variety of areas like cloud computing, IoT, big data, fin-tech, etc., which produce a large-scale data.

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Development of Vending Machine for Electricity Based on Z-Wave Mesh Network (Z-Wave 메쉬 네트워크 기반의 전기 자판기 개발)

  • Kang, Ki-beom;Ahn, Hyun-kwon;Kim, Han-soo;Lee, Seung-hyun;Jwa, Jeong-woo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.10
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    • pp.1256-1262
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    • 2016
  • As the population of camping is increased in campsites and auto camp sites, the electrical equipment can safely supply electricity to users in a variety of electricity bill policy is required in the campsite. In this paper, we develop the vending machine for electricity that can control the outdoor electrical outlet from the management server using the Z-Wave WPAN and android mobile application. The developed vending machine for electricity consists of the management server, the controller, the outdoor outlet box, and the mobile application. The management server provides reservation and electricity bill payment to users. The management server controls the electrical outlet box through the controller to safely supply electricity to users. The controller that is a relay device between the management server and the switch controls switches based on Z-Wave mesh network. Outdoor electrical outlet box has 2 meter switches. We receive the relevant authorization to provide commercial electricity services using the outdoor electrical outlet box in the campsite.