• Title/Summary/Keyword: IoT Data

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A study on the development of quality control algorithm for internet of things (IoT) urban weather observed data based on machine learning (머신러닝기반의 사물인터넷 도시기상 관측자료 품질검사 알고리즘 개발에 관한 연구)

  • Lee, Seung Woon;Jung, Seung Kwon
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1071-1081
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    • 2021
  • In addition to the current quality control procedures for the weather observation performed by the Korea Meteorological Administration (KMA), this study proposes quality inspection standards for Internet of Things (IoT) urban weather observed data based on machine learning that can be used in smart cities of the future. To this end, in order to confirm whether the standards currently set based on ASOS (Automated Synoptic Observing System) and AWS (Automatic Weather System) are suitable for urban weather, usability was verified based on SKT AWS data installed in Seoul, and a machine learning-based quality control algorithm was finally proposed in consideration of the IoT's own data's features. As for the quality control algorithm, missing value test, value pattern test, sufficient data test, statistical range abnormality test, time value abnormality test, spatial value abnormality test were performed first. After that, physical limit test, stage test, climate range test, and internal consistency test, which are QC for suggested by the KMA, were performed. To verify the proposed algorithm, it was applied to the actual IoT urban weather observed data to the weather station located in Songdo, Incheon. Through this, it is possible to identify defects that IoT devices can have that could not be identified by the existing KMA's QC and a quality control algorithm for IoT weather observation devices to be installed in smart cities of future is proposed.

WiFi-Based Home IoT Communication System

  • Chen, Wenhui;Jeong, Sangho;Jung, Hoekyung
    • Journal of information and communication convergence engineering
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    • v.18 no.1
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    • pp.8-15
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    • 2020
  • Internet-of-Things (IoT) technologies are used everywhere, and communication is one of its core and essential aspect. To solve the networking and communication of small IoT terminals, in this paper, a communication scheme based on low-cost WiFi is proposed, which also has the advantages of good compatibility and low power consumption. At the same time, it has a convenient one-key configuration mode, which reduces the technical requirements for operators. In this study, a communication protocol is designed that mainly aims at up to dozens of domestic IoT terminals, in which the amount of data is not large, data exchange is not high, and network is unstable. According to the alarm data, update data, and equipment or network fault, the protocol can respectively transmit in real time, regularly and repeatedly. This protocol is open and easy to integrate, and after cooperating with tiny encryption algorithm, information can be safely transmitted.

A Review on Preserving Data Confidentiality in Blockchain-based IoT-Supply Chain Systems

  • Omimah Alsaedi;Omar Batarfi;Mohammed Dahab
    • International Journal of Computer Science & Network Security
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    • v.23 no.11
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    • pp.110-116
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    • 2023
  • Data confidentiality refers to the characteristic that information kept undisclosed or hidden from unauthorized parties. It considered a key security requirement in current supply chain management (SCM) systems. Currently, academia and industry tend to adopt blockchain and IoT technologies in order to develop efficient and secure SCM systems. However, providing confidential data sharing among these technologies is quite challenging due to the limitations associated with blockchain and IoT devices. This review paper illustrates the importance of preserving data confidentiality in SCM systems by highlighting the state of the art on confidentiality-preserving methodologies in the context of blockchain based IoT-SCM systems and the challenges associated with it.

A new type of lightweight stream encryption algorithm motif for applying low capacity messaging data encryption for IoT / QR / electronic tags (IoT/QR/전자태그용 저용량 메시지 데이터 암호화 적용을 위한 새로운 방식의 스트림 경량 암호화 알고리즘 모티브 제안)

  • Kim, Jung-Hoon
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.1
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    • pp.46-56
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    • 2017
  • Recently, the spread of IoT technology has been spreading, and it has been applied to all industrial fields such as home / home appliance / medical care. Due to the low specification, low power consumption characteristic and communication data characteristic of IoT, implementation of existing algorithm is difficult thing. From this reason, we have proposed for the first time that encryption and decryption can be proceeded by introducing a kind of variable length bit XOR operation method which changes a variable the bit length value by using carry up and carry down method. We confirmed the practicality of encrypting short message data frequently processed by IoT device / QR code / RFID / NFC without changing the size of data before and after encryption.

GDPR Compliant Consent Procedure for Personal Information Collection in the IoT Environment (IoT 환경에서 GDPR에 부합하는 개인정보수집 동의 절차)

  • Lee, Goo Yeon;Bang, Junil;Cha, Kyung Jin;Kim, Hwa Jong
    • The Journal of Korean Institute of Information Technology
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    • v.17 no.5
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    • pp.129-136
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    • 2019
  • Many IoT devices like sensors lack screen and input devices, thus making them hard to meet the consent conditions that GDPR requires. This is acting as a legal barrier for further advancement in the business field. In this paper, we designed the process for consent of personal information collection that meets the legal conditions. In this design, user's personal data is received in an encrypted form by data collecting server first. The encrypted personal data can be decrypted after associating with user agent based on the consent procedure of the collection of personal information. During the consent procedure, user agent understands the privacy policy about personal information collection and offers the key to decrypt the data. This kind of personal information collection agreement procedure will satisfy the transparent and freely given consent requirements of GDPR. Thus, we can speculate from here that the proposed procedure will contribute to the evolution of IoT business area dealing with personal information.

Multi-blockchain model ensures scalability and reliability based on intelligent Internet of Things (지능형 사물인터넷 기반의 확장성과 신뢰성을 보장하는 다중 블록체인 모델)

  • Jeong, Yoon-Su;Kim, Yong-Tae
    • Journal of Convergence for Information Technology
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    • v.11 no.3
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    • pp.140-146
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    • 2021
  • As the environment using intelligent IoT devices increases, various studies are underway to ensure the integrity of information sent and received from intelligent IoT devices. However, all IoT information generated in heterogeneous environments is not fully provided with reliable protocols and services. In this paper, we propose an intelligent-based multi-blockchain model that can extract only critical information among various information processed by intelligent IoT devices. In the proposed model, blockchain is used to ensure the integrity of IoT information sent and received from IoT devices. The proposed model uses the correlation index of the collected information to trust a large number of IoT information to extract only the information with a high correlation index and bind it with blockchain. This is because the collected information can be extended to the n-tier structure as well as guaranteed reliability. Furthermore, since the proposed model can give weight information to the collection information based on blockchain, similar information can be selected (or bound) according to priority. The proposed model is able to extend the collection information to the n-layer structure while maintaining the data processing cost processed in real time regardless of the number of IoT devices.

Real-time IoT Big Data Analysis Platform Requirements (실시간 IoT Big Data 분석 플랫폼 요건)

  • Kang, Sun-Kyoung;Lee, Hyun-Chang;Shin, Seong-Yoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.05a
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    • pp.165-166
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    • 2017
  • It is demanding to receive information of data in real time anywhere and analyze it with meaningful data. Research on the platform for such analysis is actively underway. In this paper, we try to find out what are important factors in solving the problems of collecting and analyzing IoT data in real time. How much better than existing data collection methods and analytical methods can be the basis for judging the value of the data. It is important to accurately collect and store data more quickly and quickly from many sensors in real time in real time, and analytical methods that can derive values from the stored data. Therefore, an important requirement of the analysis platform in the IoT environment is to process large amount of data in real time and to centralize and manage it.

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Mobile-based Big Data Processing and Monitoring Technology in IoT Environment (IoT 환경에서 모바일 기반 빅데이터 처리 및 모니터링 기술)

  • Lee, Seung-Hae;Kim, Ju-Ho;Shin, Dong-Youn;Shin, Dong-Jin;Park, Jeong-Min;Kim, Jeong-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.6
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    • pp.1-9
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    • 2018
  • In the fourth industrial revolution, which has become an issue now, we have been able to receive instant analysis results faster than the existing slow speed through various Big Data technologies, and to conduct real-time monitoring on mobile and web. First, various irregular sensor Data is generated using IoT device, Raspberry Pi. Sensor Data is collected in real time, and the collected data is distributed and stored using several nodes. Then, the stored Sensor Data is processed and refined. Visualize and output the analysis result after analysis. By using these methods, we can train the human resources required for Big Data and mobile related fields using IoT, and process data efficiently and quickly. We also provide information that can confirm the reliability of research results through real time monitoring.

Secret Key-Dimensional Distribution Mechanism Using Deep Learning to Minimize IoT Communication Noise Based on MIMO (MIMO 기반의 IoT 통신 잡음을 최소화하기 위해서 딥러닝을 활용한 비밀키 차원 분배 메커니즘)

  • Cho, Sung-Nam;Jeong, Yoon-Su
    • Journal of Convergence for Information Technology
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    • v.10 no.11
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    • pp.23-29
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    • 2020
  • As IoT devices increase exponentially, minimizing MIMO interference and increasing transmission capacity for sending and receiving IoT information through multiple antennas remain the biggest issues. In this paper, secret key-level distribution mechanism using deep learning is proposed to minimize MIMO-based IoT communication noise. The proposed mechanism minimizes resource loss during transmission and reception process by dispersing IoT information sent and received through multiple antennas in batches using deep learning. In addition, the proposed mechanism applied a multidimensional key distribution processing process to maximize capacity through multiple antenna multiple stream transmission at base stations without direct interference between the APs. In addition, the proposed mechanism synchronizes IoT information by deep learning the frequency of use of secret keys according to the number of IoT information by applying the method of distributing secret keys in dimension according to the number of frequency channels of IoT information in order to make the most of the multiple antenna technology.

Implementation of IoT Home System based on MQTT (MQTT 기반 IoT 홈 시스템 구현)

  • Kim, U-zo;Choi, Jin-ku
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.1
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    • pp.231-237
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    • 2020
  • In this paper, we implemented a home IoT system based on MQTT protocol. In this system, data are collected from sensors in real time and transmitted to the server system. Based on collected data, home devices could be controlled automatically or manually. By using the MQTT protocol, we were able to see the data values of sensors collected in real time according to the topic setting. We implemented a system that automatically sets up home devices based on topic data, and it worked. The system is expected to be useful in applications that require monitoring and tracking of data in real time.