• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.846-851
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• 2007

The wireless sensor network is one of the most practical and cost-effective solutions for monitoring systems covering wild and wide area such as wildfire monitoring. However, the RF distance between sensor nodes is very short due to the need of low power consumption of the sensor node, so the number of sensor nodes to be deployed in the target area is more than tens of thousands. In this paper, we design and analyze the deployment issues as well as re-deployment problem occurred when the battery is exhausted. We also propose the needs and solutions for coverage problem in dynamic deployment. By the experimental evaluations, we analyze the packet success ratio between sensor nodes under various environments such as obstacles and variable distances.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1519-1527
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• 2007

In order to combat the security threats that sensor networks are exposed to, a cryptography protocol is implemented at sensor nodes for point-to-point encryption between nodes. Given that nodes have limited resources, symmetric cryptography that is proven to be efficient for low power devices is implemented. Data protection is integrated into a sensor's packet by the means of symmetric encryption with the Dragon stream cipher and incorporating the newly designed Dragon-MAC Message Authentication Code. The proposed algorithm was designed to employ some of the data already computed by the underlying Dragon stream cipher for the purpose of minimizing the computational cost of the operations required by the MAC algorithm. In view that Dragon is a word based stream cipher with a fast key stream generation, it is very suitable for a constrained environment. Our protocol regarded the entity authentication and message authentication through the implementation of authenticated encryption scheme in wireless sensor nodes.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1187-1198
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• 2021

Sea wind isrecently drawing attraction as one of the sources of renewable energy. Thisstudy describes a new method to produce a 10 m resolution sea wind field using Sentinel-1 images and low-resolution NWP (Numerical Weather Prediction) data with artificial intelligence technique. The experiment for the South East coast in Korea, 2015-2020,showed a 40% decreased MAE (Mean Absolute Error) than the generic CMOD (C-band Model) function, and the CC (correlation coefficient) of our method was 0.901 and 0.826, respectively, for the U and V wind components. We created 10m resolution sea wind maps for the study area, which showed a typical trend of wind distribution and a spatially detailed wind pattern as well. The proposed method can be applied to surveying for wind power and information service for coastal disaster prevention and leisure activities.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.57-68
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• 2018

A system to prevent disasters by collecting and analyzing environmental information such as road surface sedimentation, sinkholes, collapse risk of bridges, temperature and humidity around tram station is continuously monitored by monitoring the condition of road surface when constructing tram which is one of the urban railways. In this paper, we propose a wireless network security management system for tram roads based on LPWA that can recognize risk factors of road surface, bridge and tram station of tram in advance and prevent risk. The proposed system consists of a sensor node that detects the state of the tram road surface, a gateway that collects sensor information, and a safety management system that monitors the safety and environmental conditions of the tram road surface, and applies the low power long distance communication technology. As a result of comparing the proposed system with the LTE system in the field test, it was confirmed that there is no significant difference between the sensor information value and the critical alarm level in the monitoring system.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.37-45
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• 2022

With the development of the Internet of Things (IoT), related network infrastructures require new technologies to protect against threats such as external hacking. This study proposes an L-PBFT consensus algorithm that can protect IoT networks based on a blockchain consensus algorithm. We designed a blockchain (private) model suitable for small networks, tested processing performance for ultra-small/low-power IoT devices, and verified stability. As a result of performance analysis, L-PBFT proved that at least the number of nodes complies with the operation of the consensus algorithm(minimum 14%, maximum 29%) and establishes a trust network(separation of secure channels) different from existing security protocols. This study is a 4th industry convergence research and will be a foundation technology that will help develop IoT device security products in the future.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.59-68
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• 2022

We propose the vehicle maintenance support system to alarm consumable replacement reminders to the vehicle owner. Since the delayed replacement of the consumables makes the condition of the vehicle worse, it is crucial to replace consumables in a recommended period. The vehicle maintenance support system alarms the replacement time, which is set by the vehicle owner, based on the mileage of the installed vehicle. It integrates speed information acquired from the Controller Area Network interface for communication between Electronic Control Unit and instrument panel, exposed at the On Board Diagnostics-II port, to calculate the vehicle mileage. By this, there is no additional wiring required for the system. We verify the system has only 0.28% error by comparing the mileage on the system with the instrument cluster on the vehicle. It automatically enters low-power mode consuming 15mW, which is a negligible amount for the typical conditions of the car, to prevent the vehicle battery from discharging when the ignition is off.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2278-2291
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• 2023

Imported ornamental fish should be quarantined because they can have dangerous diseases depending on their habitat. The quarantine requires a lot of time because quarantine officers collect various information on the imported ornamental fish. Inefficient quarantine processes reduce its work efficiency and accuracy. Also, long-time quarantine causes the death of environmentally sensitive ornamental fish and huge financial losses. To improve existing quarantine systems, information on ornamental fish was collected and structured, and a server was established to develop quarantine performance support software equipped with a text search engine. However, the long names of ornamental fish in general can cause many typos and time bottlenecks when we type search words for the target fish information. Therefore, we need a technique that can correct typos. Typical typo character calibration compares input text with all characters in a calibrated candidate text dictionary. However, this approach requires computational power proportional to the number of typos, resulting in slow processing time and low calibration accuracy performance. Therefore, to improve the calibration accuracy of characters, we propose a fusion system of simple Artificial Neural Network (ANN) models and character preprocessing methods that accelerate the process by minimizing the computation of the models. We also propose a typo character generation method used for training the ANN models. Simulation results show that the proposed typo character correction system is about 6 times faster than the conventional method and has 10% higher accuracy.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.49-56
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• 2023

With the development of technology worldwide, bridges are becoming larger, and the number of old bridges is also rapidly increasing. Monitoring the structural health of large, aging bridges is essential to preventing large-scale accidents. In this study, the application of a LoRa low-power wide-area network (LPWAN)-based wireless measurement system was investigated, and a LoRa wireless measurement system was established in the cable-stayed bridge section of Cheonsa Bridge, located in Shinan-gun, Jeollanam-do, Korea. The applicability of the LoRa LPWAN-based wireless monitoring system to large marine bridges was reviewed by comparing the performance and economic feasibility with wire-based monitoring systems that were built and operated by establishing a measurement system for the pylons, cables, and reinforcing girders of the bridge.

• Convergence Security Journal
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• v.23 no.1
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• pp.45-54
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• 2023

Recently, with the development of the Internet of Things, research on protocols that can easily connect devices without a UI to the network has been steadily conducted. To this end, the Wi-Fi Alliance announced Wi-Fi Easy Connect, which can connect to a network using a QR code. However, since Wi-Fi Easy Connect requires a large amount of computation for safety, it is difficult to apply to low-power and miniaturized IoT devices. In addition, Wi-Fi Easy Connect considering scalability is designed to operate in a wired environment, but problems such as duplicate encryption occur because it does not consider a security environment like TLS. Therefore, in this paper, we analyze the Wi-Fi Easy Connect protocol and propose a protocol that can operate efficiently in the TLS environment. It was confirmed that the proposed protocol satisfies the existing security requirements and at the same time reduces about 67% of ECC scalar multiplication operations with a large amount of computation.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.125-125
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• 2020

European Space Agency's Sentinel-1 has an improved spatial and temporal resolution, as compared to previous satellite data such as Envisat Advanced SAR (ASAR) or Advanced Scatterometer (ASCAT). Thus, the assumption used for low-resolution retrieval algorithms used by ENVISAT ASAR or ASCAT is not applicable to Sentinel-1, because a higher degree of land surface heterogeneity should be considered for retrieval. The assumption of homogeneity over land surface is not valid any more. In this study, considering that soil roughness is one of the key parameters sensitive to soil moisture retrievals, various approaches are discussed. First, soil roughness is spatially inverted from Sentinel-1 backscattering over Yanco sites in Australia. Based upon this, Artificial Neural Networks data (feedforward multiplayer perception, MLP, Levenberg-Marquadt algorithm) are compared with Fractal approach (brownian fractal, Hurst exponent of 0.5). When using ANNs, training data are achieved from theoretical forward scattering models, Integral Equation Model (IEM). and Sentinel-1 measurements. The network is trained by 20 neurons and one hidden layer, and one input layer. On the other hand, fractal surface roughness is generated by fitting 1D power spectrum model with roughness spectra. Fractal roughness profile is produced by a stochastic process describing probability between two points, and Hurst exponent, as well as rms heights (a standard deviation of surface height). Main interest of this study is to estimate a spatial variability of roughness without the need of local measurements. This non-local approach is significant, because we operationally have to be independent from local stations, due to its few spatial coverage at the global level. More fundamentally, SAR roughness is much different from local measurements, Remote sensing data are influenced by incidence angle, large scale topography, or a mixing regime of sensors, although probe deployed in the field indicate point data. Finally, demerit and merit of these approaches will be discussed.