Do Hyun Kim

Dr. Do Hyun Kim

Department of Computer Engineering, Jeju National University, South Korea

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 May 2019 in Electronics
Verified
Journal Article
Open access
PDF file
FJFaisal Jamil
Faisal Jamil
LHLei Hang
Lei Hang
KKKyu Hyung Kim
Kyu Hyung Kim
DKDo Hyun Kim
Do Hyun Kim
At present, in pharmacology one of the most serious problems is counterfeit drugs. The Health Research Funding organization reported that in developing countries, nearly 10–30% of the drugs are fake. Counterfeiting is not the main issue itself, but, rather, the fact that, as compared to traditional drugs, these counterfeit drugs produce different side effects to human health. According to WHO, around 30% of the total medicine sold in Africa, Asia, and Latin America is counterfeit. This is the major worldwide problem, and the situation is worse in developing countries, where one out of every 10 medicines are either fake or do not follow drug regulations. The rise of Internet pharmacies has made it more difficult to standardize drug safety. It is difficult to detect counterfeits because these drugs pass through different complex distributed networks, thus forming opportunities for counterfeits to enter the authentic supply chain. The safety of the pharmaceutical supply chain has become a major concern for public health, which is a collective process. In this paper, we propose a novel drug supply chain management using Hyperledger Fabric based on blockchain technology to handle secure drug supply chain records. The proposed system solves this problem by conducting drug record transactions on a blockchain to create a smart healthcare ecosystem with a drug supply chain. A smart contract is launched to give time-limited access to electronic drug records and also patient electronic health records. We also carried out a number of experiments in order to demonstrate the usability and efficiency of the designed platform. Finally, we used Hyperledger Caliper as a benchmarking tool to conduct the performance of the designed system in terms of transactions per second, transaction latency, and resource utilization.

13 April 2020 in Sensors
Verified
Journal Article
Open access
PDF file
FJFaisal Jamil
Faisal Jamil
Shabir AhmadShabir Ahmad
Shabir Ahmad
NINaeem Iqbal
Naeem Iqbal
DKDo Hyun Kim
Do Hyun Kim
Over the past several years, many healthcare applications have been developed to enhance the healthcare industry. Recent advancements in information technology and blockchain technology have revolutionized electronic healthcare research and industry. The innovation of miniaturized healthcare sensors for monitoring patient vital signs has improved and secured the human healthcare system. The increase in portable health devices has enhanced the quality of health-monitoring status both at an activity/fitness level for self-health tracking and at a medical level, providing more data to clinicians with potential for earlier diagnosis and guidance of treatment. When sharing personal medical information, data security and comfort are essential requirements for interaction with and collection of electronic medical records. However, it is hard for current systems to meet these requirements because they have inconsistent security policies and access control structures. The new solutions should be directed towards improving data access, and should be managed by the government in terms of privacy and security requirements to ensure the reliability of data for medical purposes. Blockchain paves the way for a revolution in the traditional pharmaceutical industry and benefits from unique features such as privacy and transparency of data. In this paper, we propose a novel platform for monitoring patient vital signs using smart contracts based on blockchain. The proposed system is designed and developed using hyperledger fabric, which is an enterprise-distributed ledger framework for developing blockchain-based applications. This approach provides several benefits to the patients, such as an extensive, immutable history log, and global access to medical information from anywhere at any time. The Libelium e-Health toolkit is used to acquire physiological data. The performance of the designed and developed system is evaluated in terms of transaction per second, transaction latency, and resource utilization using a standard benchmark tool known as Hyperledger Caliper. It is found that the proposed system outperforms the traditional health care system for monitoring patient data.

14 May 2019 in Sensors
Verified
Journal Article
Open access
PDF file
LHLei Hang
Lei Hang
DKDo Hyun Kim
Do Hyun Kim
With the rapid development of communication technologies, the Internet of Things (IoT) is getting out of its infancy, into full maturity, and tends to be developed in an explosively rapid way, with more and more data transmitted and processed. As a result, the ability to manage devices deployed worldwide has been given more and advanced requirements in practical application performances. Most existing IoT platforms are highly centralized architectures, which suffer from various technical limitations, such as a cyber-attack and single point of failure. A new solution direction is essential to enhance data accessing, while regulating it with government mandates in privacy and security. In this paper, we propose an integrated IoT platform using blockchain technology to guarantee sensing data integrity. The aim of this platform is to afford the device owner a practical application that provides a comprehensive, immutable log and allows easy access to their devices deployed in different domains. It also provides characteristics of general IoT systems, allows for real-time monitoring, and control between the end user and device. The business logic of the application is defined by the smart contract, which contains rules and conditions. The proposed approach is backed by a proof of concept implementation in realistic IoT scenarios, utilizing Raspberry Pi devices and a permissioned network called Hyperledger Fabric. Lastly, a benchmark study using various performance metrics is made to highlight the significance of the proposed work. The analysis results indicate that the designed platform is suitable for the resource-constrained IoT architecture and is scalable to be extended in various IoT scenarios.

19 February 2021 in IEEE Access
Verified
Journal Article
Open access
FJFaisal Jamil
Faisal Jamil
NINaeem Iqbal
Naeem Iqbal
- Imran- Imran
- Imran
Shabir AhmadShabir Ahmad
Shabir Ahmad
DKDo Hyun Kim
Do Hyun Kim
It is expected that peer to peer energy trading will constitute a significant share of research in upcoming generation power systems due to the rising demand of energy in smart microgrids. However, the on-demand use of energy is considered a big challenge to achieve the optimal cost for households. This paper proposes a blockchain-based predictive energy trading platform to provide real-time support, day-ahead controlling, and generation scheduling of distributed energy resources. The proposed blockchain-based platform consists of two modules; blockchain-based energy trading and smart contract enabled predictive analytics modules. The blockchain module allows peers with real-time energy consumption monitoring, easy energy trading control, reward model, and unchangeable energy trading transaction logs. The smart contract enabled predictive analytics module aims to build a prediction model based on historical energy consumption data to predict short-term energy consumption. This paper uses real energy consumption data acquired from the Jeju province energy department, the Republic of Korea. This study aims to achieve optimal power flow and energy crowdsourcing, supporting energy trading among the consumer and prosumer. Energy trading is based on day-ahead, real-time control, and scheduling of distributed energy resources to meet the smart grid’s load demand. Moreover, we use data mining techniques to perform time-series analysis to extract and analyze underlying patterns from the historical energy consumption data. The time-series analysis supports energy management to devise better future decisions to plan and manage energy resources effectively. To evaluate the proposed predictive model’s performance, we have used several statistical measures, such as mean square error and root mean square error on various machine learning models, namely recurrent neural networks and alike. Moreover, we also evaluate the blockchain platform’s effectiveness through hyperledger calliper in terms of latency, throughput, and resource utilization. Based on the experimental results, the proposed model is effectively used for energy crowdsourcing between the prosumer and consumer to attain service quality.

25 April 2019 in Electronics
Verified
Journal Article
Open access
PDF file
LHLei Hang
Lei Hang
ECEunchang Choi
Eunchang Choi
DKDo Hyun Kim
Do Hyun Kim
Recent advancements in information and communication technology is enabling a significant revolution in e-Health research and industry. In the case of personal medical data sharing, data security and convenience are crucial requirements to the interaction and collaboration of electronic medical record (EMR) systems. However, it’s hard for current systems to meet these requirements as they have inconsistent structures in terms of security policies and access control models. A new solution direction is essential to enhance data-accessing while regulating it with government mandates in privacy and security to ensure the accountability of the medical usage data. Blockchain seems to pave the way for revolution in the conventional healthcare industry benefiting by its unique features such as data privacy and transparency. In this paper, a blockchain-based medical platform using a smart contract is proposed to secure the EMR management. This approach provides patients a comprehensive, immutable log and easy access to their medical information across different departments within the hospital. A case study for hospital is built on a permissioned network, and a series of experimental tests are performed to demonstrate the usability and efficiency of the designed platform. Lastly, a benchmark study by leveraging various performance metrics is made and the outcomes indicate that the designed platform surpasses the ability of existing works in various aspects. The results of this work reveal that the proposed solution has the great potential to accelerate the development of a decentralized digital healthcare ecosystem.

5 January 2021 in IEEE Access
Verified
Journal Article
Open access
NINaeem Iqbal
Naeem Iqbal
FJFaisal Jamil
Faisal Jamil
Shabir AhmadShabir Ahmad
Shabir Ahmad
DKDo Hyun Kim
Do Hyun Kim
The recent advances in information management systems coupled with machine learning algorithms paved the way for a significant revolution in animal healthcare industries. However, the data in such systems suffer from various challenges such as security, reliability, and convenience, to name a few. Traditional systems are not useful to meet these critical issues because these systems have not a consistent structure for data security and reliability policies. Therefore, a new solution is required to enhance data accessibility and should regulate government security policies to ensure the accountability of the usage of the medical records system. Moreover, it is also required to analyze historical data of veterinary clinic using data mining and machine learning techniques to predict the future appointments scheduling requests, which is essential for veterinary management to drive better future decisions, for instance, future demands of medical supplies and to plan veterinary medical staff, etc. This paper aims to fill the gap by proposing a novel blockchain-based reliable and intelligent veterinary information management system (RIVIMS) using smart contract and machine learning techniques. The proposed RIVIMS consists of two main modules; blockchain-based secured veterinary information management, data and predictive analytics modules. First, a blockchain-based secure and reliable veterinary clinic information management system is developed using Hyperledger Fabric. Second, a smart contract enabled data, and predictive analytics modules are developed using permissioned blockchain framework. The data and predictive modules aim to analyze veterinary clinic patients appointments data in order to discover underlying patterns and build a robust prediction model using machine learning algorithms. The data and predictive helps veterinary management to drive better future business decisions to provide better healthcare services to veterinary patients. Hyperledger Caliper is used as a benchmark tool to evaluate the performance of the developed blockchain-based system in terms of transaction per second, transaction success rate, transaction throughput, and transaction latency. Furthermore, machine learning performance measures have utilized, such as MAE, RMSE, and R2 score to evaluate the overall performance of the prediction model. The experimental results demonstrate the effectiveness and robustness of the proposed RIVIMS.