• Journal of Sensor Science and Technology
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• v.31 no.5
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• pp.307-311
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• 2022

With the development of Internet of Things (IoT) technologies, numerous people worldwide connect with various electronic devices via Human-Machine Interfaces (HMIs). Considering that HMIs are a new concept of dynamic interactions, wearable electronics have been highlighted owing to their lightweight, flexibility, stretchability, and attachability. In particular, wearable strain sensors have been applied to a multitude of practical applications (e.g., fitness and healthcare) by conformally attaching such devices to the human skin. However, the stretchable elastomer in a wearable sensor has an intrinsic stretching limitation; therefore, structural advances of wearable sensors are required to develop practical applications of wearable sensors. In this study, we demonstrated a 3-dimensional (3D), porous, and piezoelectric strain sensor for sensing body movements. More specifically, the device was fabricated by mixing polydimethylsiloxane (PDMS) and polyvinylidene fluoride nanoparticles (PVDF NPs) as the matrix and piezoelectric materials of the strain sensor. The porous structure of the strain sensor was formed by a sugar cube-based 3D template. Additionally, mixing methods of PVDF piezoelectric NPs were optimized to enhance the device sensitivity. Finally, it is verified that the developed strain sensor could be directly attached onto the finger joint to sense its movements.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.229-237
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• 2018

As IoT and AI have recently developed, interest in digital healthcare is increasing. Therefore, this study aims to identify technology trends through a patent analysis on digital healthcare and present future promising areas by analyzing domestic and foreign technology competitiveness and keywords. The detailed technologies to be analyzed were designated as Health Information Measurement Technology, Healthcare Platform Technology and Healthcare Remote Service Technology, and 61,166 patents were analyzed to identify the patent trends of the world's major patent offices and major patent applications. In addition, the analysis of the technological competitiveness of each detailed technology and Korea's technological competitiveness based on its patent activity, the rate of major market securing, and the uses of the patents showed that Korea's technological competitiveness was lower than global technology. In addition, the key keyword analysis showed that the core promising areas of digital healthcare were expected to require a focused strategy for fostering health care platform technologies in Korea.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.25-31
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• 2016

With the development of IOT technology and the expansion of ICT services recently, a variety of home network services have been advanced based on wired and wireless high speed telecommunication. Domestic and global companies have been studying on the innovative technology for the users using IOT based technology and the environment for the smart home services has been gradually developed. The users live their lives with more convenience due to the expansions and developments of smart phones. However, the threatening on the security of the smart home network had occurred by various attacks with the connection to the smart environment telecommunication, lack of applications on low powered and light weight telecommunication, and the problems of security guideline. In addition, the solutions are required for the new and variant attacking cases such as data forgery and alteration of the device for disguising approach with ill will. In this article, the safe communication protocol was designed using certification management technique based on AKI which supplemented the weakness of PKI, the existing certification system in the smart environment. Utilizing the signature technique based on ECDSA, the efficiency on the communication performance was improved, and the security and the safety were analyzed on the security threat under the smart home environment.

• Journal of Broadcast Engineering
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• v.25 no.2
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• pp.200-207
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• 2020

Recently, deep neural networks such as CNN are showing excellent performance in various fields such as image classification, object recognition, visual quality enhancement, etc. However, as the model size and computational complexity of deep learning models for most applications increases, it is hard to apply neural networks to IoT and mobile environments. Therefore, neural network compression algorithms for reducing the model size while keeping the performance have been being studied. In this paper, we apply few compression methods to CNN models and evaluate their performances in the embedded environment. For evaluate the performance, the classification performance and inference time of the original CNN models and the compressed CNN models on the image inputted by the camera are evaluated in the embedded board equipped with QCS605, which is a customized AI chip. In this paper, a few CNN models of MobileNetV2, ResNet50, and VGG-16 are compressed by applying the methods of pruning and matrix decomposition. The experimental results show that the compressed models give not only the model size reduction of 1.3~11.2 times at a classification performance loss of less than 2% compared to the original model, but also the inference time reduction of 1.2~2.21 times, and the memory reduction of 1.2~3.8 times in the embedded board.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.31-40
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• 2018

With the development of IT technology recently, medical information systems are being constructed in an integrated u-health environment through cloud services, IoT technologies, and mobile applications. These kinds of medical information systems should provide the medical staff with authorities to access patients' medical information for emergency status treatments or therapeutic purposes. Therefore, in the medical information systems, the reliable and prompt authentication processes are necessary to access the biometric information and the medical information of the patients in charge of the medical staff. However, medical information systems are accessing with simple and static user authentication mechanism using only medical ID / PWD in the present system environment. For this reason, in this paper, we suggest a dynamic situation authentication mechanism that provides transparency of medical information access including various authentication factors considering patient's emergency status condition and dynamic situation authentication system supporting it. Our dynamic Situation Authentication is a combination of user authentication and mobile device authentication, which includes various authentication factor attributes such as emergency status, role of medical staff, their working hours, and their working positions and so forth. We designed and implemented a dynamic situation authentication system including emergency status decision, dynamic situation authentication, and authentication support DB construction. Finally, in order to verify the serviceability of the suggested dynamic situation authentication system, the medical staffs download the mobile application from the medical information server to the medical staff's own mobile device together with the dynamic situation authentication process and the permission to access medical information to the patient and showed access to medical information.

• Korea Science and Art Forum
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• v.31
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• pp.21-32
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• 2017

Local festivals form the regional cultures and atmosphere of communication; they increase the demand of domestic tourism businesses and thus, have an important role in ripple effects (e.g. regional image improvement, tourist influx, job creation, regional contents development, and local product sales) and economic revitalization. IoT (Internet of Thing) technologies have been developed especially, beacon-one of the IoT services has been applied as plenty of types and forms both domestically and internationally. However, notwithstanding expansion of current digital mobile technologies, it still remains as difficult for the individual to track the information about all the local festivals and to fulfill the tourists' needs of enjoying festivals given the weak strategic approaches and advertisement activities. Furthermore, current festival-related mobile applications don't function well as delivering information and have numerous contents issues (e.g. ways of information delivery within the festival places, independent application usage for each festival, one time usage due to one time event). This research, based on the background mentioned above, aims to develop the local festival mobile application and data analysis system applying beacon technology. First of all, three algorithms were developed, namely, 'festival crowding algorithm', 'visitor stats algorithm', and 'customized information algorithm', and then beta test was followed with the developed application and data analysis system. As a result, they could form the database of visitors' types and behaviors, and provide functions and services, such as personalized information, waiting time for festival contents, and 'hot place' function. Besides, in Google Play store, they also got the titles given with more than 13,000 downloads within first three months and as the most exposed application related with festivals; and, thus, got credited with their marketability and excellence. This research follows this order: chapter 2 shows the literature review of local festival related with technology development, beacon service, and festival application. In Chapter 3, design plans and conditions are described of developing local festival mobile application and data analysis system with beacon. Chapter 4 evaluates the results of the beta performance test to verify applicability of the developed application and data analysis system, and lastly, chapter 5 explains the conclusion and suggests the future research.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.4
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• pp.189-198
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• 2015

Most IoT-related approaches have tried to establish the relation by connecting the network between things. The proposed research will present how the pervasive interaction of eco-system formed by touching the objects between humans and things can be recognized on purpose. By collecting and sharing the detected patterns among all kinds of things, we can construct the environment which enables individualized interactions of different objects. To perform the aforementioned, we are going to utilize technical procedures such as event-driven signal processing, pattern matching for signal recognition, and hardware in the loop simulation. We will also aim to implement the prototype of sensor processor based on Arduino MCU, which can be integrated with system using Arduino-Matlab/Simulink hybrid-interoperation environment. In the experiment, we use piezo transducer to detect the vibration or vibrates the surface using acoustic wave, which has specific frequency spectrum and individualized signal shape in terms of time axis. The signal distortion in time and frequency domain is recorded into memory tracer within sensor processor to extract the meaningful pattern by comparing the stored with lookup table(LUT). In this paper, we will contribute the initial prototypes for the acoustic touch processor by using off-the-shelf MCU and the integrated framework based on Matlab/Simulink model to provide the individualization of the touch-sensing for the user on purpose.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1436-1457
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• 2018

Secure routing services in Wireless Sensor Networks (WSNs) are essential, especially in mission critical fields such as the military and in medical applications. Additionally, they play a vital role in the current and future Internet of Things (IoT) services. Lightness and efficiency of a routing protocol are not the only requirements that guarantee success; security assurance also needs to be enforced. This paper proposes a Secure-Fuzzy Energy Aware Routing Protocol (S-FEAR) for WSNs. S-FEAR applies a security model to an existing energy efficient FEAR protocol. As part of this research, the S-FEAR protocol has been analyzed in terms of the communication and processing costs associated with building and applying this model, regardless of the security techniques used. Moreover, the Qualnet network simulator was used to implement both FEAR and S-FEAR after carefully selecting the following security techniques to achieve both authentication and data integrity: the Cipher Block Chaining-Message Authentication Code (CBC-MAC) and the Elliptic Curve Digital Signature Algorithm (ECDSA). The performance of both protocols was assessed in terms of complexity and energy consumption. The results reveal that achieving authentication and data integrity successfully excluded all attackers from the network topology regardless of the percentage of attackers. Consequently, the constructed topology is secure and thus, safe data transmission over the network is ensured. Simulation results show that using CBC-MAC for example, costs 0.00064% of network energy while ECDSA costs about 0.0091%. On the other hand, attacks cost the network about 4.7 times the cost of applying these techniques.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.539-554
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• 2018

Effective interaction between user and device is considered an important ability of IoT devices. For some applications, it is necessary to recognize human facial expressions in real time and make accurate judgments in order to respond to situations correctly. Therefore, many researches on facial image analysis have been preceded in order to construct a more accurate and faster recognition system. In this study, we constructed an automatic recognition system for facial expressions through two steps - a facial recognition step and a classification step. We compared various models with different sets of data with pixel information, landmark coordinates, Euclidean distances among landmark points, and arctangent angles. We found a fast and efficient prediction model with only 30 principal components of face landmark information. We applied several prediction models, that included linear discriminant analysis (LDA), random forests, support vector machine (SVM), and bagging; consequently, an SVM model gives the best result. The LDA model gives the second best prediction accuracy but it can fit and predict data faster than SVM and other methods. Finally, we compared our method to Microsoft Azure Emotion API and Convolution Neural Network (CNN). Our method gives a very competitive result.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.95-102
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• 2019

As the number of fish keepers increases, fishbowl-related convenience products are on the rise. Existing products are not welcomed by consumers because of their lack of functions or high price. In this paper, we deal with a system that remotely controls sensors and motors of fish bowl based on Raspberry Pi and Arduino. In Android applications, you can use the following functions. firstly, feeding. Second, water changing. Third, it measures, visualizes temperature and pH values including alert function. Through the several experiments, it was verified that the system can be quickly accessed from the outside, and when it is appropriate to change water. This system allows the user to keep the fish more comfortable and safe.