• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.851-853
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• 2013

Recently, location-based service as the developed continuously, interest in positioning technology is increasing. As the most famous indoor positioning technology, WPS is a positioning technology using WiFi, which can complement the limits of the indoor positioning to have a GPS. In this paper, to provide a system for monitoring the position of the inside of the user based on the position information that using the RSSI signal of the wireless AP based WPS technology, they grip the location information of the mobile nodes in the indoor. If using the method proposed, it is expected to be applied to various services it is possible to apply the WPS, this is because it is possible to estimate in real time the location distribution of mobile nodes in the indoor.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.6
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• pp.375-381
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• 2019

Structural health monitoring to determine structural conditions at an early stage and to efficiently manage the energy requirements of buildings using systems that collects relevant data, is under active investigation. Structural monitoring requires cutting-edge technology in which construction, sensing, and ICT technologies are combined. However, the scope of application is limited because expensive sensors and specialized technical skills are often required. In this study, a Raspberry Pi module, one of the most widely used single board computers, a Lora module that is capable of long-distance communication at low power, and a high-performance accelerometer are used to construct a wireless edge computing system that can monitor building response over an extended time period. In addition, the Raspberry Pi module utilizes an edge computing algorithm, and only meaningful data is obtained from the vast amount of acceleration data acquired in real-time. The raw data acquired using Wi-Fi communication are compared to the Laura data to evaluate the accuracy of the data obtained using the system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.707-713
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• 2016

In the IEEE 802.11 Wireless LAN environment, the common Access Point (AP) selection of the existing terminal is based on signal strength. However, the signal strength-based AP selection method does not ensure an optimal data rate. Recently, several AP selection methods to solve this problem have been suggested. However, when we select AP, these have a latency problem and don't consider dense environments of AP. In this paper, we confirm the problem of the conventional AP selection about the signal strength and the throughput through the actual measurement, and propose algorithm that selects AP by scoring link speed and wireless round trip time to compensate the problem. Furthermore, the proposed AP selection algorithm through the actual experiment proves the improved performance as compared with the existing methods.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.51-61
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• 2021

In the era of the 4th industrial revolution symbolized by the Internet of Things, big data and artificial intelligence, various embedded devices are increasing exponentially. These devices have communication functions despite their low specifications, so the possibility of personal information leakage is increasing, and security threats are also increasing. Embedded devices can have security issues at most levels, from hardware to services over the network. In addition, it is difficult to apply general security techniques because it has characteristics of resource constraints such as low specifications and low power, and the related technology has not been standardized. In this study, we present vulnerabilities and possible problems and considerations in applying SDN to embedded devices in consideration of structural characteristics and real-world discovered cases. This study presents vulnerabilities and possible problems and considerations when applying SDN to embedded devices. From a hardware perspective, we consider the problems of Wi-Fi chips and Bluetooth, the problems of open flow implementation, SDN controllers, and examples of structural properties. SDN separates the data plane and the control plane, and provides a standardized interface between the two, enabling efficient communication control. It can respond to the security limitations of existing network technologies that are difficult to respond to rapid changes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.600-608
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• 2020

Machine learning constructs an objective function from learning data, and predicts the result of the data generated by checking the objective function through test data. In machine learning, input data is subjected to a normalisation process through a preprocessing. In the case of numerical data, normalization is standardized by using the average and standard deviation of the input data. In the case of nominal data, which is non-numerical data, it is converted into a one-hot code form. However, this preprocessing alone cannot solve the problem. For this reason, we propose a method that uses ontology to normalize input data in this paper. The test data for this uses the received signal strength indicator (RSSI) value of the Wi-Fi device collected from the mobile device. These data are solved through ontology because they includes noise and heterogeneous problems.

• Journal of Platform Technology
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• v.9 no.4
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• pp.42-50
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• 2021

Recently, the need to introduce smart farms is increasing in order to solve the problems of intensifying competition such as a decrease in rural population due to aging, a decrease in production, and the inflow of foreign agricultural products, and accordingly, the need for education is increasing. This paper is a study on the implementation of an Android-based IoT smart farm for education so that it can be used in a real environment by reducing the farm's smart farm system. To confirm that Android-based education can be applied in a real environment using the IoT smart farm for education, experiments were performed in automatic mode and manual mode using Bluetooth, Wi-Fi, and server/client communication methods. In the automatic mode, the current status can be checked in real time by receiving all data, and in the manual mode, commands are transmitted in real time using the received sensor data and remote control is performed. As a result of the experiment, it was possible to understand the characteristics of each communication method, and it was confirmed that remote monitoring and remote control of the smart farm using the Android App was possible.

• Journal of IKEEE
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• v.26 no.1
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• pp.62-66
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• 2022

Recently, there have been many research efforts based on data-based deep learning technologies to deal with the interference problem between heterogeneous wireless communication devices in unlicensed frequency bands. However, existing approaches are commonly based on the use of complex neural network models, which require high computational power, limiting their efficiency in resource-constrained network interfaces and Internet of Things (IoT) devices. In this study, we address the problem of classifying heterogeneous wireless technologies including Wi-Fi and ZigBee in unlicensed spectrum bands. We focus on a data-driven approach that employs a supervised-learning method that uses received signal strength indicator (RSSI) data to train Deep Convolutional Neural Networks (CNNs). We propose a simple measurement methodology for collecting RSSI training data which preserves temporal and spectral properties of the target signal. Real experimental results using an open-source 2.4 GHz wireless development platform Ubertooth show that the proposed sampling method maintains the same accuracy with only a 10% level of sampling data for the same neural network architecture.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.256-264
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• 2023

Smart farm technology using IoT is one of the technologies that can increase productivity and improve the quality of agricultural products in agriculture, which is facing difficulties due to the decline in rural population, lack of rural manpower due to aging, and increase in diseases and pests due to climate change. . Smart farms using existing IoT simply monitor farms, implement smart plant growers, and have automatic greenhouse opening and closing systems. This paper implements a smart farm system based on MQTT, an industry standard protocol for the Internet of Things, and Node-RED, a representative development middleware for the Internet of Things. First, data is extracted from Arduino sensors, and data is collected and transmitted from IoT devices using the MQTT protocol. Then, Node-RED is used to process MQTT messages and store the sensing data in real time in MongoDB, a representative NoSQL, to store the data. Through this smart farm system, farm managers can use a computer or mobile phone to check sensing information on the smart farm in real time, anytime, anywhere, without restrictions on time and space.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.107-115
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• 2013

Smart appliances with multi-media and telecommunication equipments provide users complicated convenience functions. On the contrary, 8-bit controller-based low performance electronics still cannot afford such multimedia and telecommunication. If we find a way to have low-end electronics connected and provide complicated functions, they can be also made "smart". Fortunately, 8-bit controllers used in low-end appliances have UART, which can be connected to any of BlueTooth, Wi-Fi and ZigBee communication modules which can, in turn, communicate with smart devices. Any communication module can be attached to the low-end electronics due to the variety of smart devices' connectivity at the other side. Although the convenience functions seem complicated, they are actually macros in a script form composed of micro commands which implement the base functions of appliances. Since the kinds of the base functions are not that many, the low-end electronic appliances will become "smart" if their control program can be extended to execute sequentially the micro commands in any combination. Such simple innovation has not seen the world, until now due to the overhead of the additionally required hardware such as display devices and buttons. The high-quality display and touch screen functionalities of smart devices can replace the required hardware, and remove the overhead completely. In fact, the low-end appliances become smart as if an "evolution kit" is newly equipped.

• Convergence Security Journal
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• v.12 no.1
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• pp.55-61
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• 2012

Owing to the development of wireless infrastructure and mobile communication technology, There is growing interest in smart phone using it. The resulting popularity of smart phone has increased the Mobile Malicious AP-related security threat and the access to the wireless AP(Access Point) using Wi-Fi. mobile AP mechanism is the use of a mobile device with Internet access such as 3G cellular service to serve as an Internet gateway or access point for other devices. Within the enterprise, the use of mobile AP mechanism made corporate information management difficult owing to use wireless system that is impossible to wire packet monitoring. In this thesis, we propose mobile AP mechanism-based mobile malicious AP detection and prevention mechanism in radius authentication server network. Detection approach detects mobile AP mechanism-based mobile malicious AP by sniffing the beacon frame and analyzing the difference between an authorized AP and a mobile AP mechanism-based mobile malicious AP detection.