• ETRI Journal
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• v.39 no.2
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• pp.202-212
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• 2017

With the advent of the Internet-of-Things paradigm, the amount of data production has grown exponentially and the user demand for responsive consumption of data has increased significantly. Herein, we present DART, a fast and lightweight stream processing framework for the IoT environment. Because the DART framework targets a geospatially distributed environment of heterogeneous devices, the framework provides (1) an end-user tool for device registration and application authoring, (2) automatic worker node monitoring and task allocations, and (3) runtime management of user applications with fault tolerance. To maximize performance, the DART framework adopts an actor model in which applications are segmented into microtasks and assigned to an actor following a single responsibility. To prove the feasibility of the proposed framework, we implemented the DART system. We also conducted experiments to show that the system can significantly reduce computing burdens and alleviate network load by utilizing the idle resources of intermediate edge devices.

• Annual Conference of KIPS
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• 2018.10a
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• pp.235-237
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• 2018

The Internet has allowed many things to move fast, including sharing of data, files and others within a second. Many domains use applications range from IoT, smart cities, healthcare, and organizations to share the data when necessary. However, there are some challenges faced by existing systems that works on centralized nature. Such challenges are data breach, trustiness issue, unauthorized access and data fraud. Therefore in this work, we focus on using a smart contract which is used by blockchain platform and works on decentralized form. Furthermore, in this work our contract provides an access to the file uploaded onto the decentralized storage such as IPFS. By leveraging smart contract-role based which consist of a contract owner who can manage the users when access the certain resources such as a file and as well as use of decentralized storage to avoid single point of failure and censorship over secure communication channel. We checked the gas cost of the smart contract since most of contracts tends to be a high cost.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.625-640
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• 2023

This paper propose a circuit that can measure the inductance of an inductive sensor used in IOT applications. The circuit was constructed using the characteristics of an RL low-pass filter circuit, comparator, current control switch, and capacitor, and the inductance value within the range 1[nH] < L ≤ 1[H] can be derived through the duration time during the output voltage of the RL low-pass filter circuit is greater than the reference voltage.

• Journal of Sensor Science and Technology
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• v.32 no.4
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• pp.213-218
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• 2023

Triboelectric nanogenerators (TENGs) have emerged as a highly promising energy harvesting technology capable of harnessing mechanical energy from various environmental vibrations. Their versatility in material selection and efficient conversion of mechanical energy into electric energy make them particularly attractive. TENGs can serve as a valuable technology for self-powered sensor operation in preparation for the IoT era. Additionally, they demonstrate potential for diverse applications, including energy sources for implanted medical devices (IMDs), neural therapy, and wound healing. In this review, we summarize the potential use of this universally applicable triboelectric energy harvesting technology in the disinfection and blocking of pathogens. By integrating triboelectric energy harvesting technology into human clothing, masks, and other accessories, we propose the possibility of blocking pathogens, along with technologies for removing airborne or waterborne infectious agents. Through this, we suggest that triboelectric energy harvesting technology could be an efficient alternative to existing pathogen removal technologies in the future.

• International journal of advanced smart convergence
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• v.6 no.4
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• pp.50-55
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• 2017

Workers' demands for new applications, especially mobile applications, are increasing. Many industry analysts, researchers and corporate executives say the demand for mobile applications is becoming increasingly difficult to follow in the IT department. Gartner predicts that by 2021, the demand for mobile application development within the enterprise will increase about five times faster than IT can deliver applications. The purpose of this paper is to provide an environment where non-developers who are in charge of business development can develop apps and webs for their work. The basic concept of a new innovative App development tool, Smart Maker Authoring Tool is to develop Apps on the level using easy-to-learn Word or Excel in a computer. The main feature is that the app is developed by a non-developer worker. The coding technology is perfectly optimized to the structure and operation mechanism of the IT Infra such as hardware devices and operating system, which are the targets for implementing a desired function. Rather, it shows excellent software productivity. The most important feature of future business development is that it is developed by a non-developer worker. In this paper, we propose a no-code and low-code platform for non - developers to develop their business. In the future, we will link the IoT based Arduino system and artificial intelligent interpretation system.

• KIISE Transactions on Computing Practices
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• v.24 no.2
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• pp.67-76
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• 2018

BLE (Bluetooth Low Energy) has been extensively used for communication between mobile applications and wearable devices in IoT (Internet of Things). In developing Android applications, wearable devices, on which the applications can run, should be available because the existing Android SDK does not support any BLE emulation facility. In this study, we have designed and implemented the first Android BLE emulator. Using this, we are able to develop and test BLE-based Android applications even when without wearable devices. We have also proposed an automatic generation method of Android BLE scenarios based on graph model. We have shown that the method is useful for systematically testing BLE application protocols by running the generated scenarios on the Android BLE emulator.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.199-210
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• 2021

Recently, research in blockchain technology has grown in popularity. Most of these researches have pointed out designing and improving conceptual structures to create digital systems that are more secure, accessible, and effective. Although blockchain offers a wide range of advantages, it also has some pitfalls. This research aims to present an understanding of the properties of blockchain, the advantages, pitfalls, and applications based on blockchain technology. To achieve the goal of understanding blockchain technology concepts, a systematic literature review approach was introduced. 93 papers were chosen and reviewed in total. Therefore, this research provides a summary of recent studies that have been published in the field of blockchain. Moreover, we have created concept maps and tables that aid in a deep understanding of blockchain technology concepts and exhibit some of the blockchain applications. In blockchain-based applications, we focused on two areas, namely the Internet of Things (IoT) and healthcare.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.285-292
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• 2023

With the wide spread of smart farms and the advancements in IoT technology, it is easy to obtain additional data in addition to crop images. Consequently, deep learning-based crop disease diagnosis research utilizing multimodal data has become important. This study proposes a crop disease diagnosis method using multimodal supervised contrastive learning by expanding upon the multimodal self-supervised learning. RandAugment method was used to augment crop image and time series of environment data. These augmented data passed through encoder and projection head for each modality, yielding low-dimensional features. Subsequently, the proposed multimodal supervised contrastive loss helped features from the same class get closer while pushing apart those from different classes. Following this, the pretrained model was fine-tuned for crop disease diagnosis. The visualization of t-SNE result and comparative assessments of crop disease diagnosis performance substantiate that the proposed method has superior performance than multimodal self-supervised learning.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.3
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• pp.679-691
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• 2016

As vehicle started to contain many different communication devices, collecting external information became possible in IoT environment. In such environment, remotely controling vehicle is possible when vehicle information is obtained by looking in to vehicle network through smart device. However, android based smart device applications are vulnerable to malicious modulation and redistribution. Modulated android application can lead to vehicle information disclosure that could bring about vehicle control accident which becomes threat to drivers. furthermore, since vehicles today does not contain security methods to protect it, they are very vulnerable to security threats which can cause serious damage to users and properties. In this paper, many different vehicle management android applications that are sold in Google Play has been analyzed. With this information, possible threats that could happen in vehicle management applications are being analysed to prove the risks. the experiment is done on actual vehicle to prove the risks. Also, access control method to protect the vehicle against malicious actions that could happen through external network in IoT environment is suggested in the paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1967-1983
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• 2020

The goal of this paper is to analyze and build an algorithm to recognize hand gestures applying to smart home applications. The proposed algorithm uses image processing techniques combing with artificial neural network (ANN) approaches to help users interact with computers by common gestures. We use five types of gestures, namely those for Stop, Forward, Backward, Turn Left, and Turn Right. Users will control devices through a camera connected to computers. The algorithm will analyze gestures and take actions to perform appropriate action according to users requests via their gestures. The results show that the average accuracy of proposal algorithm is 92.6 percent for images and more than 91 percent for video, which both satisfy performance requirements for real-world application, specifically for smart home services. The processing time is approximately 0.098 second with 10 frames/sec datasets. However, accuracy rate still depends on the number of training images (video) and their resolution.