• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.159-166
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• 2019

The collection and manipulation of Internet of Things (IoT) data is increasing at a fast pace and its importance is recognized in every sector of our society. For efficient utilization of IoT data, the vast and varied IoT data needs to be reliable and meaningful. In this paper, we propose an IoT framework to realize this need. The IoT framework is based on a four layer IoT architecture onto which context aware computing technology is applied. If the collected IoT data is unreliable it cannot be used for its intended purpose and the whole service using the data must be abandoned. In this paper, we include techniques to remove uncertainty in the early stage of IoT data capture and collection resulting in reliable data. Since the data coming out of the various IoT devices have different formats, it is important to convert them into a standard format before further processing, We propose the RDF format to be the standard format for all IoT data. In addition, it is not feasible to process all captured Iot data from the sensor devices. In order to decide which data to process and understand, we propose to use contexts and reasoning based on these contexts. For reasoning, we propose to use standard AI and statistical techniques. We also propose an experiment environment that can be used to develop an IoT application to realize the IoT framework.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.85-97
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• 2014

IoT devices that collect information for end users and provide various services like giving traffic or weather information to them that are located everywhere aim to raise quality of life. Currently, the number of devices has dramatically increased so that there are many companies and laboratories for developing various IoT devices in the world. However, research about IoT computing such as connecting IoT devices or management is at an early stage. A server node that manages lots of IoT device in IoT computing environment is certainly needed. But, it is difficult to manage lots of devices efficiently. However, anyone cannot surly know about how many servers are needed or where they are located in the environment. In this paper, we suggest a method that is a way to dynamic clustering IoT computing environment by logical distance among devices. With our proposed method, we can ensure to manage the quality in large-scale IoT environment efficiently.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.35-41
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• 2016

Internet of Things (IoT) services are widely used in appliances of daily life and industries. IoT services also provide various conveniences to users and are expected to affect value added of all industries and national competitiveness. However, a variety of security threats are increased in IoT environments and lowers reliability of IoT devices and services that make some obstacles for commercialization. The attacks arising in IoT environments are making industrial and normal life accidents unlike existing information leak and monetary damages, and can expand damage scale of leakage of personal information and privacy more than existing them. To solve these problems, we design a session key based access control scheme for secure communications in IoT environments. The proposed scheme reinforces message security by generating session key between device and access control network system. We analyzed the stability of the proposed access scheme in terms of data forgery and corruption, unauthorized access, information disclosure, privacy violations, and denial of service attacks. And we also evaluated the proposed scheme in terms of permission settings, privacy indemnity, data confidentiality and integrity, authentication, and access control.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.893-895
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• 2016

Data center has a lot of management efforts for the facility, energy, and efficient usage monitoring. Data center power management is important to make the data center have reliable service and cost-effective business. In this paper, IoT based energy measurements monitoring which gives support to energy consumption analysis including indoor, outdoor temperature condition. This converged information for energy analysis gives various aspects of energy consumption effects. With IoT big data, energy machine learning system can give the relation of energy components and measurements, it is the key information of the quick energy analysis in the just one month data trend for the prediction and estimation.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1239-1244
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• 2023

In this study, we developed an IoT-based management system to manage a can/PET crusher. Various sensors such as two load cells, DHT22 temperature and humidity sensor, and fine dust meter were interfaced with ESP32 to construct an IoT device, and a management server was built using Node-RED. The system monitors the weight of pressed cans and shredded PET bottles in real time and sends a text message to the manager when the weight exceeds the predetermined threshold for timely collection. The results of the operational test confirmed that the system provides accurate monitoring and efficient notification functions, and offers the possibility of solving environmental problems by improving the efficiency of waste management such as cans and PET bottles.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.305-306
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• 2021

본 논문에서는 인천공항 Airside와 Landside에 위치한 자산의 효율적인 관리를 위한 사물인터넷(IoT) 기반 스마트 자산관리 시스템의 구성과 실증을 제시한다. IoT기반 스마트 자산관리시스템은 위치정보를 생성하는 IoT 태그와 게이트웨이, 수집된 위치정보를 수신하고 표출하는 서버로 구성되어 있으며, IoT 태그를 자산에 부착하여 자산의 실내외 위치정보를 자산관리 시스템에서 실시간으로 확인할 수 있다. 실내 위치정보는 BLE(Bluetooth Low Energy)를 통해 취득하며, 실외 위치정보는 GPS와 LoRa(Long Range)를 통해 취득 가능하다. 개발한 시스템의 성능 검증을 위해 인천공항 제1여객터미널 내 기설치된 AP를 활용하였으며, 공항 전역을 커버할 수 있는 LoRa Gateway를 설치하였다. 개발한 자산관리 시스템은 공항이 보유한 자산의 도난 방지 등 효율적인 관리 와 공항운영에 기여할 것으로 예상된다.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.325-331
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• 2022

As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.173-181
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• 2023

Data collection is an essential element in the construction and operation of a smart factory. The quality of data collection is greatly influenced by network conditions, and existing wireless network systems for IoT inevitably lose data due to wireless signal strength. This data loss has contributed to increased system instability due to misinformation based on incorrect data. In this study, I designed a distributed MQTT IoT smart sensor and gateway structure that supports wireless multicasting for smooth sensor data collection. Through this, it was possible to derive significant results in the service latency and data loss rate of packets even in a wireless environment, unlike the MQTT QoS-based system. Therefore, through this study, it will be possible to implement a data collection management system optimized for the domestic smart factory manufacturing environment that can prevent data loss and delay due to abnormal data generation and minimize the input of management personnel.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.18-23
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• 2016

Internet of things (IoT) is revolutionizing in the patient-Centered medical monitoring and management by authorizing the Smartphone application and data analysis with medical centers. The network connectivity is basic requirement to collect the observed human beings' health information from Smartphone to monitor the health from IoT medical devices in personal healthcare. The IoT environment built in Smartphone is very effective and does not demand infrastructure. This paper presents the smart phone deployed personal IoT architecture for Non-Invasive ECG Capturing. The adaptable IoT medical device cum Gateway is used for personal healthcare with big data storage on cloud configuration. In this approach, the Smartphone camera based imaging technique used to extract the personal ECG waveform and forward it to the cloud based big data storage connectivity using IoT architecture. Elaborated algorithm allows for efficient ECG registration directly from face image captured from Smartphone or Tablet camera. The profound technique may have an exceptional value in monitoring personal healthcare after adequate enhancements are introduced.

• Journal of Environmental Health Sciences
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• v.44 no.5
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• pp.421-432
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• 2018

Objectives: In this study, we started to develop an indoor garden integrated IoT solution based on IAQ (indoor air quality) and interconnection with an environmental database for smart management of indoor gardens. The purpose of this study was to develop and apply an integrated solution for customized air purification from an indoor garden through big data analysis using IoT technology. Methods: An IoT-based IAQ monitoring system was established in three households within a new apartment building. Based on real-time and long-term data collected, $PM_{2.5}$, $CO_2$, temperature, and humidity changes were compared to those of indoor garden applications and the analyzed results were indexed. Results As a result of the installation, all three households had no results exceeding the standard for indoor air pollution on average $PM_{2.5}$ and $CO_2$ indices. In the case of indoor garden installation, the IAQ index increased to the "Good" section after the installation, and readings in the "Bad" section shown before the installation disappeared. The comfort index also did not dip into the "Uncomfortable" section, where it had been preinstallation, and significantly lowered the average score from "Uncomfortable for sensitive groups" to "Good". Overall, the IAQ composite index for the generation of installations decreased the "Good" interval, but "Bad" did not appear. Conclusions In this study on developing an integrated solution for IAQ based on IoT indoor gardens, big data was analyzed to determine IAQ and comfort indexes and an IAQ composite index. Through this process, it became understood that it is necessary to monitor IAQ based on IoT.