• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.613-625
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• 2019

The rise of the Internet of Things (IoT) devices have greatly influenced many industries and one of them is healthcare where wearable devices started to track all your daily activities for better health monitoring accuracy and even down to tracking daily food intake in some cases. With the amounts of data that are being tracked and shared between from these devices, questions were raised on how to uphold user's data privacy when data is shared between these IoT devices and third party. With the blockchain platforms started to mature since its inception, the technology can be implemented according to a variety of use case scenarios. In this paper, we present a system architecture based on the healthcare system and IoT network by leveraging on multiple blockchain networks as the medium in between that should enable users to have direct authority on data accessibility of their shared data. We provide proof of concept implementation and highlight the results from our testing to show how the efficiency and scalability of the healthcare system improved without having a significant impact on the performance of the Electronic Medical Record (EMR) that mostly affected by the previous solution since these solutions directly connected to a public blockchain network and which resulted in significant delays and high cost of operation when a large amount of data or complicated functions are involved.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.424-433
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• 2021

The aim of this study is to explores the possibility of applying new aquaponics using guppies, a tropical fish breeding as companion fish at home, different from the aquaponics system using fish species such as loach, carp, and catfish for commercial purposes. To facilitate the application of Aquaponics at home, a system was established by connecting a water tank, water plants, hydroponic pots, plant growth LEDs, and Arduino sensors using Internet of Things(IoT) technology. As a hydroponic crops, lettuce that can be easily obtained and consumed at home was selected. In order to confirm the applicability of aquaponics using tropical fish, the growth rates of hydroponic crops in the same environment were compared as a control. The growth rate of aquaponics crops using tropical fish was about 77.4% of that of hydroponic crops. This will produce the same effect as hydroponic cultivation if conditions correspond with enough fish quantity to feed plant and appropriate pH control for growth are met. It can be seen that, and in the future, it can be used to develop an Aquaphonics standard system applicable at home.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.183-190
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• 2021

This study is a study on the implementation and operation of smart air cleaning system to improve indoor air quality. Recently, the problem of indoor air quality is getting serious due to various environmental factors. In this study, to improve the problems of indoor air quality, we implement an air cleaning system using IoT sensor. In particular, we proposed a system that can measure air pollution in real time and change different air flow paths according to pollution level. Through this, we examined efficient air quality improvement, extension of filter life, and system energy reduction. In addition, the main functions of the indoor air quality improvement system were constructed and prototypes were manufactured to confirm the operability. Finally, the utility of fine dust resolution through the implementation of the indoor air quality improvement system was examined.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1158-1164
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• 2020

In Korea, the dependence on imported energy is very high, and research to reduce standby power is being conducted based on Zigbee, a low-power technology, to reduce wasted power and improve power efficiency. However, because Zigbee is not an IoT standard protocol and is not network-based, it is necessary to build a network with a separate gateway, and research on standby power is insufficient because the standards for international power consumption of devices are ambiguous. Therefore, in this paper, we applied the IoT standard protocol MQTT to the existing Zigbee technology to build a network network without a separate gateway, and designed and implemented a standby power reduction system that collects standby power degradation and user patterns. As a result of evaluating with the existing system, it was confirmed that about 7.11% of standby power was consumed compared to the existing system.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.25-31
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• 2023

The brain-machine interface(BMI) is a next-generation interface that controls the device by decoding brain waves(also called Electroencephalogram, EEG), EEG is a electrical signal of nerve cell generated when the BMI user thinks of a command. The brain-machine interface can be applied to various smart devices, but complex computational process is required to decode the brain wave signal. Therefore, it is difficult to implement a brain-machine interface in an embedded system implemented in the form of an edge device. In this study, we proposed a new type of brain-machine interface system using IoT technology that only measures EEG at the edge device and stores and analyzes EEG data in the cloud computing. This system successfully performed quantitative EEG analysis for the brain-machine interface, and the whole data transmission time also showed a capable level of real-time processing.

• Korean Journal of Construction Engineering and Management
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• v.24 no.3
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• pp.42-51
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• 2023

Freeze and burst water meter in winter causes many social costs, such as meter replacement cost, inability of water use, and secondary damage by freezing water. The government is making efforts to modernize local waterworks, and in particular, is promoting SWM(Smart Water Management) project nationwide. In this study suggests a new freeze risk notification information service based on the temperature by IoT sensor inside the water meter box rather than outside temperature. In addition, in order to overcome the quantitative and regional limitation of IoT temperature sensors installed nationwide, and AI based temperature prediction model was developed that predicts the temperature inside water meter boxes based on data acquired from IoT temperature sensors and other information. Through the prediction model optimization process, a nationwide water meter freezing risk information service was convinced.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.83-101
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• 2021

This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.171-178
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• 2017

Data mashup is a web technology that combines information from multiple sources into a single web application. Mashup applications create a new horizon for new services, like environmental monitoring. Environmental monitoring is a serious tool for the state and private organizations, which are located in regions with environmental hazards and seek to gain insights to detect hazards and locate them clearly. These organizations utilize a data mashup to merge datasets from different Internet of multimedia things (IoMT) context-based services in order to leverage its data analytics performance and the accuracy of the predictions. However, mashup different datasets from multiple sources is a privacy hazard as it might reveal citizens specific behaviors in different regions. The ability to preserve privacy in mashuped datasets and at the same time provide accurate insights becomes a key success for the spread of mashup services. In this paper, we present our efforts to build a fog-based middleware for private data mashup (FMPM) to serve a centralized environmental monitoring service. The proposed middleware is equipped with concealment mechanisms to preserve the privacy of the merged datasets from multiple IoMT networks involved in the mashup application. Also, these mechanisms preserve the aggregates in the dataset to maximize the usability of information to attain accurate analytical results. We also provide a scenario for IoMT-enabled data mashup service and experimentation results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.51-57
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• 2023

Smart mirror is an IoT device that attaches a display and an embedded computer to the mirror and provides various information to the user along with the mirror function. This paper presents performance evaluation of the CoMirror system as an extension of the previous research in which proposed and implemented the CoMirror system that connects Smart Mirrors using a network. First, the login performance utilizing face recognition was evaluated. As result of the performance evaluation, it was concluded that the 40 face images are most suitable for face learning and only one face image is most suitable for face recognition for login. Second, as a result of evaluating the message transmission time, the average time was 0.5 seconds for text, 0.63 seconds for audio, and 2.9 seconds for images. Third, as a result of measuring a video communication performance, the average setup time for video communication was 1.8 seconds and the average video reception time was 1.9 seconds. Finally, according to the performance evaluation results, we conclude that the CoMirror system has high practicality.