• Electronics and Telecommunications Trends
• /
• v.31 no.1
• /
• pp.68-77
• /
• 2016

최근 들어 5G 이동통신 시스템을 위한 표준화 및 기술개발이 본격화되고 있으며, 기존 이동통신 시스템과 차별화되는 5G 이동통신 시스템의 대표적인 목표 중 하나는 사람이 휴대하는 단말기뿐만 아니라 생활 속 모든 사물을 네트워크에 연결하여 정보를 생성하고 공유하는 초연결 네트워크(Internet of Things: IoT) 구축이다. 시장 조사기관이나 다수의 전문가들은 2020년경에는 전 세계적으로 약 500억개의 디바이스가 네트워크에 연결되는 등 사물 디바이스의 폭발적 증가를 예상하며, 이를 통한 부가가치 창출과 시장이 급격히 성장할 것으로 전망하고 있다. 본고에서는 초다수의 사물 디바이스 수용을 위한 5G massive IoT 기술동향 및 이와 관련하여 현재 진행되는 3GPP 표준화 동향에 대해 기술한다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.11
• /
• pp.310-318
• /
• 2018

Recently, the importance of big data analysis is increasing as a large amount of data is generated by various devices connected to the Internet with the advent of Internet of Things (IoT). Especially, it is necessary to analyze various large-scale IoT streaming sensor data generated in real time and provide various services through new meaningful prediction. This paper proposes a real-time indoor PM10 concentration prediction LSTM model based on streaming data generated from IoT sensor using AWS. We also construct a real-time indoor PM10 concentration prediction service based on the proposed model. Data used in the paper is streaming data collected from the PM10 IoT sensor for 24 hours. This time series data is converted into sequence data consisting of 30 consecutive values from time series data for use as input data of LSTM. The LSTM model is learned through a sliding window process of moving to the immediately adjacent dataset. In order to improve the performance of the model, incremental learning method is applied to the streaming data collected every 24 hours. The linear regression and recurrent neural networks (RNN) models are compared to evaluate the performance of LSTM model. Experimental results show that the proposed LSTM prediction model has 700% improvement over linear regression and 140% improvement over RNN model for its performance level.

• Journal of the Korea Convergence Society
• /
• v.12 no.10
• /
• pp.45-53
• /
• 2021

In our technology-driven world, various methods for teaching in an educational venue or in a simulated environment have been suggested especially for computer and coding education. In particular, IoT related education has been made possible owing to the industrial developments that have occurred in various fields since the Fourth Industrial Revolution. The proposed model allows various IoT systems to be indirectly built; it provides an inexpensive learning method by applying a simulation system in a 3D environment. The model is implemented on Virtual Remote IO based on the Arduino platform, thereby reducing the cost of building an education system. In addition various education-related content can be provided to learners through such an indirectly developed system. Test code was written to check the consistency of an operation between the real system and the virtual system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.6
• /
• pp.1659-1674
• /
• 2024

Conventional maritime communication struggles to provide high data rate services for Internet of Things (IoT) devices due to the variability of maritime environments, making it challenging to ensure consistent connectivity for onboard sensors and devices. To resolve this, we perform mathematical modeling of the maritime channel and compare it with real measurement data. Through the modeled channel, we verify the received beam gain at buoys on the ocean surface. Additionally, leveraging the modeled wave motions, we estimate future angles of the buoy to use the Extended Kalman Filter (EKF) for design beamforming strategies that adapt to the evolving maritime environment over time. We further validate the effectiveness of these strategies by assessing the results from an outage probability perspective. focuses on improving maritime communication by developing a dynamic model of the maritime channel and implementing a Kalman filter-based buoy motion tracking system. This system is designed to enable precise beamforming, a technique used to direct communication signals more accurately. By improving beamforming, the aim is to enhance the quality of communication links, even in challenging maritime conditions like rough seas and varying sea states. In our simulations that consider realistic wave motions, you've observed significant improvements in link quality due to the enhanced beamforming technique. These improvements are particularly notable in environments with high sea states, where communication challenges are typically more pronounced. The progress made in this area is not just a technical achievement; it has broad implications for the future of maritime communication technologies. This paper promises to revolutionize the way we approach communication in maritime environments, paving the way for more reliable and efficient information exchange on the seas.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.9 no.7
• /
• pp.767-772
• /
• 2014

As temporary network, ad-hoc network has been effected by structures and implemented environments of networks. In this paper, transmission performance of lattice structure ad-hoc network, which is expected to use in sensor network and IoT(Internet of Things), is analyzed in point of intrusions and countermeasure for intrusion is suggested. In this paper, computer simulation based on NS-2 is used for performance analysis, VoIP(Voice over Internet Protocol) as a widely used service is chosen for performance measure. MOS(Mean Opinion Score) and call connection rate is used as performance parameter. As results of performance analysis, it is shown that for MOS, random network is better then lattice network at intrusion environments, but for call connection rate, lattice network is better then random network.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.1
• /
• pp.17-28
• /
• 2019

6LoWPAN based on IEEE 802.15.4 is a realistic standard platform for various Internet of Things (IoT) applications. To bootstrap the LoWPAN (Low-power Wireless Personal Area Network), each device must perform 6LoWPAN-ND address registration to assign a unique IPv6 address. Without adequate security mechanisms, 6LoWPAN-ND is vulnerable to a variety of security attacks including corrupted node attacks. Several security mechanisms have been proposed as a supplement to the vulnerability, but the vulnerability exists because it relies solely on IEEE 802.15.4 hop-by-hop security. In this paper, we propose and analyze a vulnerability of 6LoWPAN-ND address registration and a new security mechanism suitable for preventing the attack of damaged node. It also shows that the proposed security mechanism is compatible with the Internet Engineering Task Force (IETF) standard and is more efficient than the mechanism proposed in the IETF 6 lo WG.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.11 no.7
• /
• pp.665-670
• /
• 2016

In this paper, we suggest the design of OP-AMP using MOSFET in the operation of sub-threshold condition as a basic unit of an IoT. The sub-threshold operation of MOSFET is useful for an ultra low power consumption of sensor network system in the IoT, because it cause the supply voltage to be reduced. From the simulation result using 0.35 um CMOS process, the supply voltage, VDD can be reduced with 0.6 V, open-loop gain of 43 dB and the power consumption was evaluated with about $1.3{\mu}W$ and the active size for an integration was measured with $64{\mu}m{\times}105{\mu}m$. It is expected that the proposed circuit is applied to the low power sensor network for IoT.

• Journal of the Institute of Convergence Signal Processing
• /
• v.22 no.4
• /
• pp.199-205
• /
• 2021

The distributing board in directly installed on the ground or the bottom surface of the building, and when vibrations such as earthquakes or external shocks occur, the possibility of damage or malfunction of electric components such as internal power devices, wiring, and protection relays increases. Recently, the need for a seismic type distributing board is increasing, and research and development of a distributing board having a vibration damping function and product launch are being conducted. In this paper, an IoT-based data collection device system capable of measuring vibration and environmental data of distributing board was designed and implemented. When vibration occurred on the distributing board, data was stored and visualized in the MySQL DB through Node-RED for monitoring and data storage using the MQTT protocol for reliable messaging transmission. The test was conducted by attaching the IoT device of the distributing board, and data was collected in real-time and monitored through Node-RED.

• International Journal of Computer Science & Network Security
• /
• v.22 no.12
• /
• pp.185-196
• /
• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.395-398
• /
• 2017

The Smart Ship is considered one of the most discussed and novel topics in developing technological period. In this reason, the amount of running researches on it is evolving so fast. As a proof, the faced drawbacks such as the departure of ships, their safety, exchanging data, traffic and data monitoring system are being solved by presenting advanced technologies and innovations like Cloud, BigData, IoT and etc. Expanding the utilization of these technologies in the Marine world emphasizes not only the departure of the ships in the water but also they focus on solving the problems of the ships connected with the communication to the ports. In this paper, we present an IoT based smart reporting and mooring system for vessels and ports. In the proposed system, the ships automatically send all the data about themselves to the port and after getting the data, ports automatically send the information about possible spaces to moor for the ships using the sensors at the port. The intended system gives an amenity to minimize the time, effort and the cost while mooring the vessels.