• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.49-59
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• 2017

Smart sensing plays a key role in a variety of IoT applications, and its importance is growing more and more together with the development of artificial intelligence. Therefore the importance of smart sensors cannot be overemphasized. However, most studies related to smart sensors have been focusing on specific application purposes, for example, security, energy saving, monitoring, and there are not much effort on researches on how to efficiently configure various types of smart sensors to be needed in the future. In this paper, a component-based framework with hierarchical structure for efficient construction of smart sensor is proposed and its application to smart home is designed and implemented. The proposed method shows that various types of smart sensors to be appeared in the near future can be configured through the design and development of necessary components within the proposed software framework. In addition, since it has a layered architecture, the configuration of the smart sensor can be expanded by inserting the internal or external layers. In particular, it is possible to independently design the internal and external modules when designing an IoT application service through connection with the external device layer. A small-scale smart home system is designed and implemented using the proposed method, and a home cloud operating as an external layer, is further designed to accommodate and manage multiple smart homes. By developing and thus adding the components of each layer, it will be possible to efficiently extend the range of applications such as smart cars, smart buildings, smart factories an so on.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.442-454
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• 2017

As the demand for meat products has steadily increased in Korea, so the livestock industry has full grown. However, the opening of import meat products is taking a toll on the local industry. Cost reduction on livestock feed, which comprises the majority of costs involved in the industry is urgent to gain a competitive edge. As Internet of Things (IoT) technologies are being applied across a multiple of industries, so are the cases of applied Smart Farm technology for efficient production. The following research aims to utilize IoT technologies to measure, in real time, the rate of depletion of feed and remaining amount and to propose an effective automated reorder & delivery system. First, a method of utilization of ultrasonic and temperature/humidity sensors to obtain corresponding data of remaining feed in the Feedbin is proposed. In addition, a method of sending the obtained data via on-the-farm gateway to Supply Chain Management (SCM) servers is proposed. Finally, utilization of the stored data to construct an automated reorder & delivery service system is proposed. It is in the researcher's intention to contribute to and enable the local livestock industry with the application of various IoT services.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.550-558
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• 2019

As the scale of the Internet of Things (IoT) environment grows and develops day by day, the information collected and shared through IoT devices becomes increasingly diverse and more common. However, because IoT devices have limitations on computing power and a low power capacity due to their miniaturized size, it is difficult to apply security technologies like encryption and authentication that have been directly applied in the previous Internet environment, making the IoT vulnerable to security threats. Because of this weakness, important information that needs to be delivered safely and accurately is exposed to the threat of malicious exploitation, such as data forgery, data leakage, and infringement of personal information. In order to overcome this threat, various security studies are being actively conducted to compensate for the weaknesses in IoT environment devices. In particular, since various devices interact, and share and communicate information collected in the IoT environment, each device should be able to communicate with reliability. With regard to this, various studies have been carried out on techniques for device authentication. This study examines the limitations and problems of the authentication techniques that have been studied thus far, and proposes technologies that can certify IoT devices for safe communication between reliable devices in the Internet environment.

• Smart Media Journal
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• v.11 no.2
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• pp.77-83
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• 2022

The neuromorphic architecture uses a spiking neural network (SNN) model to derive more accurate results as more spike values are accumulated through inference experiments. When the inference result converges to a specific value, even if the inference experiment is further performed, the change in the result is smaller and power consumption may increase. In particular, in an AI-based IoT environment, power consumption can be a big problem. Therefore, in this paper, we propose a technique to reduce the power consumption of AI-based IoT by reducing the inference time by adjusting the inference image exposure time in the neuromorphic architecture environment. The proposed technique calculates the next inferred image exposure time by reflecting the change in inference accuracy. In addition, the rate of reflection of the change in inference accuracy can be adjusted with a coefficient value, and an optimal coefficient value is found through a comparison experiment of various coefficient values. In the proposed technique, the inference image exposure time corresponding to the target accuracy is greater than that of the linear technique, but the overall power consumption is less than that of the linear technique. As a result of measuring and evaluating the performance of the proposed method, it is confirmed that the inference experiment applying the proposed method can reduce the final exposure time by about 90% compared to the inference experiment applying the linear method.

• Journal of Information Technology Applications and Management
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• v.26 no.5
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• pp.27-39
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• 2019

The Internet of Things (IoT) is a new paradigm that is revolutionizing computing. It is intended that all objects around us will be connected to the network, providing "anytime, anywhere" access to information. This study introduces IoT with Kolb's learning style in order to enhance the learning experience especially for inclusive education for primary and secondary schools where delivery of knowledge is not limited to physical, cognitive disabilities, human diversity with respect to ability, language, culture, gender, age and of other forms of human differences. The article also emphasizes the role of learning style as a discovery process that incorporates the characteristics of problem solving and learning. Kolb's Learning Style was chosen as it is widely used in research and in practical information systems applications. A consistent pattern of finding emerges by using a combination of Kolb's learning style and internet of things where specific individual differences, learning approach differences and IoT application differences are taken as a main research framework. Further several suggestions were made by using this combination to IoT architecture and smart environment of internet of things. Based on these suggestions, future research directions are proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2377-2397
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• 2020

Human activity recognition is widely used in smart homes, health care and indoor monitor. Traditional approaches all need hardware installation or wearable sensors, which incurs additional costs and imposes many restrictions on usage. Therefore, this paper presents a novel device-free activities recognition system based on the advanced wireless technologies. The fine-grained information channel state information (CSI) in the wireless channel is employed as the indicator of human activities. To improve accuracy, both amplitude and phase information of CSI are extracted and shaped into feature vectors for activities recognition. In addition, we discuss the classification accuracy of different features and select the most stable features for feature matrix. Our experimental evaluation in two laboratories of different size demonstrates that the proposed scheme can achieve an average accuracy over 95% and 90% in different scenarios.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.283-287
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• 2020

In this paper, we implemented a control for ventilation system based on IoT. It can on/off of system and monitoring current status through the smartphone app. We applied linear regression, one of machine learning algorithm. It autonomously collects data about temperature, humidity in home and works diagnosing system status. Using this proposed control method, the energy efficiency can be improved. It is expected to be used in energy efficiency and convenience.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.548-551
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• 2018

Most vehicles are in the form of maintenance when a problem occurs by the user himself or herself. During maintenance, users are not able to operate the car while it is being serviced, and if the target vehicle is a revenue-generating vehicle, they will have to bear economic losses. Collecting vehicle information in real time, identifying problems that could arise with a vehicle based on the collected big data and providing advance service rather than after-sales service can help secure vehicle operation and reduce economic loss. Thus, in this thesis, a platform was designed to design IoT-based gateways, collect real-time vehicle information, and organize big data to provide vehicle information in real time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1921-1936
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• 2017

Internet of Thing (IoT) and NFC (Near Field Communication) have got a good adaptable structure that it can be easily combined with any wireless network. Since IoT/NFC can be used to communicate wirelessly with all the transactions that can be done remotely without any physical connections. In this paper, we propose an enhanced secure IoT/NFC protocol based on LTE network that enhances the original security level provided by the LTE. Our approach is new in a sense that it covers LTE in contrast to old networks like GSM and 3G, which substantially treated in the literature. Moreover, both GSM and 3G have several drawbacks when they are combined with the NFC technology, which has potential weakness in confidentiality, integrity, and authentication. Hence our new approach will resolve the security of the new LTE system. We expect that our protocol will result in new secure applications for the smart phone markets.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.366-373
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• 2019

The development of monitoring and analysis systems to increase productivity while saving energy is needed as a method to reduce huge amount of energy consumed in the process of producing large forged products. In this paper, we propose a system to monitor and analyze energy usage in real-time collected from gas-meter, wattmeter, and thermometer based on IoT installed in forging factories. The system consists of a data collection server for collecting and processing data from IoT- based platform and existing SCADA equipment and ERP/MES system in forging factories, and an application server for providing services to users. To develop the system, the overall system structure is logically diagrammed, and the databases configuration and implementation modules to efficiently store and manage data are presented. In the future, the system will be utilized to reduce energy consumption by analyzing energy usage pattern and optimizing process works with real-time energy usage and production process data for each facility.