• International journal of advanced smart convergence
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• v.7 no.3
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• pp.23-36
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• 2018

In wireless communication, efficient spectrum usage is an issue that has been an attractive research area for many technologies. Recently new technologies innovations allow compact radios to transmit with power efficient communication over very long distances. For example, Low-Power Wide Area Networks (LPWANs) are an attractive emerging platform to connect the Internet-of-Things (IoT). Especially, LoRa is one of LPWAN technologies and considered as an infrastructure solution for IoT. End-devices use LoRa protocol across a single wireless hop to communicate to gateway(s) connected to the internet which acts as a bridge and relays message between these LoRa end-devices to a central network server. The use of the (ISM) spectrum sharing for such long-range networking motivates us to implement spectrum sensing testbed for cognitive radio network based on LoRa and GNU radio. In cognitive radio (CR), secondary users (SUs) are able to sense and use this information to opportunistically access the licensed spectrum band in absence of the primary users (PUs). In general, PUs have not been very receptive of the idea of opportunistic spectrum sharing. That is, CR will harmfully interfere with operations of PUs. Subsequently, there is a need for experimenting with different techniques in a real system. In this paper, we implemented spectrum sensing for cognitive radio networks based on LoRa and GNU Radio, and further analyzed corresponding performances of the implemented systems. The implementation is done using Microchip LoRa evolution kits, USRPs, and GNU radio.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1771-1776
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• 2017

Recently, IoT(Internet of Things) has been utilized in various fields provide a service to users by configuring a smart environment in a particular place. However, since the existing system does not change the operation and the task of the device according to the change of the surrounding environment, the user must operate passively every time the environment and the situation change. In this paper, we propose Situation-specific Task Control System based on real-time data classification. Sensor data is sent to the server and classified into real-time and non-real-time data, and then inserted into the decision tree to identify tasks according to the situation. In addition, the danger situation is divided into two stages, such as gas leakage and fire, and a warning message is sent. Therefore, it is possible to reduce the waste of electric power and the occurrence of malfunction, and it can be expected that the service with increased work efficiency will be provided.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.615-616
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• 2017

Recently, research are being conducted to provide an automated environment utilizing various sensors in a place where management is use. However, in an existing automation system environment because the measured sensor data is processed in a batch in the server, than the currently action task there arises a problem that a conflict occurs between task when a task that should operate preferentially occurs. In this paper, we propose a system that provides automation using Sensor Data Identification Algorithm to solve these problems. The algorithm distinguishes between real-time and non-real-time tasks and automatically control tasks what happens after priority is applied. Through this, it is expected that it can reduce manager intervention and reduce unnecessary work operation and power consumption and construct an efficient automation environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.309-315
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• 2017

Recently it has drawn much attention on the technologies about Internet of Things (IoT) which connects objects with constrained resource and heterogenous communication module in order to communicate information via internet. We propose a real-time sensor monitoring system based on IPv6 over Bluetooth Low Energy (BLE), which is included in Bluetooth 4.2 Specification. Since this system uses a publish-subsribe based IoT protocol, so called Message Queueing Telemetry Transport (MQTT), neither transforming network data nor any proxy server is needed in order to transmit data. Through the web client connected to this system, you can monitor sensor data sent by BLE device in real-time, intermediated via MQTT broker and then delivered to the client via HTTP and websocket protocol. In this paper we evaluated network capacity and availability of the implemented test platform. Thus by using this system it is possible to make development cost low and to construct IoT network with heterogenous devices easily.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.5-14
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• 2018

With the advance of the 4th industrial revolution, Internet of Things (IoT) technology is actively being studied. In the era of the IoT, a decentralized operation is required to reduce load on servers and enable autonomous IoT data communication rather than focusing on centralized operation of being server client structures. This paper analyzes the security of a blockchain, a new form of distributed database platform that supports integrity and permanence of data. To achieve this, we divide the blockchain's major operations into a consensus process, network communication process, and key management process, and then describe possible attacks and countermeasures in each process. We also describe the attack occurred in typical cryptocurrency platforms such as Bitcoin and Ethereum.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1307-1313
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• 2018

In recent years, there have been frequent occurrences of collapsing buildings and tilting accidents due to frequent earthquakes and aging of buildings. Various methods have been proposed to prevent disasters on these buildings. In this paper, we propose a system that provides an indication of anomalous phenomena such as collapse and tilting of buildings by real-time monitoring of IoT(Internet of Things) based architectural anomalies. The MEMS sensor is based on the inclinometer sensor and the accelerometer sensor, transmits the detected data to the server in real time, accumulates the data, and provides the service to cope when the set threshold value is different. It is possible to evacuate and repair the collapse and tilting of the building by warning the occurrence of the upper threshold event such as the collapse and tilting of the building.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.137-142
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• 2021

The Internet of Things (IoT) paradigm is at the forefront of present and future research activities. The huge amount of sensing data from IoT devices needing to be processed is increasing dramatically in volume, variety, and velocity. In response, cloud computing was involved in handling the challenges of collecting, storing, and processing jobs. The fog computing technology is a model that is used to support cloud computing by implementing pre-processing jobs close to the end-user for realizing low latency, less power consumption in the cloud side, and high scalability. However, it may be that some resources in fog computing networks are not suitable for some kind of jobs, or the number of requests increases outside capacity. So, it is more efficient to decrease sending jobs to the cloud. Hence some other fog resources are idle, and it is better to be federated rather than forwarding them to the cloud server. Obviously, this issue affects the performance of the fog environment when dealing with big data applications or applications that are sensitive to time processing. This research aims to build a fog topology job scheduling (FTJS) to schedule the incoming jobs which are generated from the IoT devices and discover all available fog nodes with their capabilities. Also, the fog topology job placement algorithm is introduced to deploy jobs into appropriate resources in the network effectively. Finally, by comparing our result with the state-of-art first come first serve (FCFS) scheduling technique, the overall execution time is reduced significantly by approximately 20%, the energy consumption in the cloud side is reduced by 18%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.433-439
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• 2021

In this paper, we propose a method to implement an IoT-based sensor network for each workplace of a shipyard. Here, at the most common welding workplace in shipyards, the shipbuilding blocks are used as a communication medium to transmit information such as the worker's location, welding progress, and working hour to a server using LoRa and powerline communication. To achieve the data communication, inductive couplers and hybrid modems have been manufactured and installed on wire feeders and pin jigs to establish a sensor network. As a result of field test, the proposed system shows a success rate of data transmission and a rate of successful recognition of worker's location of about 98% or more. In addition, the process management system platform can record and display the work process data generated at the field in real time. The proposed system can be a starting point for enhancing the competitiveness of Korean shipbuilding industry through the establishment of a smart shipyard.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.223-229
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• 2022

During the winter season, when the weather gets colder every year, electricity consumption increases rapidly. The occurrence of fires is increasing due to a short circuit in electrical facilities of buildings such as markets, bathrooms, and apartments with high population density while using a lot of electricity. The cause of these short circuit fires is mostly due to the aging of the wires, the usage increases, and the excessive load cannot be endured, and the wire sheath is melted and caused by nearby ignition materials. In this paper, the load and overheat generated in the electric wire are measured through a complex sensor composed of an overload sensor, a VoC sensor, and an overheat sensor. Based on this, big data analysis is carried out to develop a platform capable of predicting, alerting, and blocking electric fires in real time, and a simulator capable of simulated fire experiments.

• Journal of Internet of Things and Convergence
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• v.8 no.4
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• pp.41-47
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• 2022

Smoothing is a transmission plan that converts video data stored at a variable bit rate into a fixed bit rate. Algorithms for smoothing include CBA, which aims to minimize the number of transmission rate increases, MCBA, which minimizes the number of transmission rate changes, and MVBA algorithms that minimize the amount of transmission rate change. This paper compares the proposed algorithm with the CBA algorithm with various video data, buffer size, and performance evaluation factors as a follow-up to the proposed smoothing algorithm that minimizes (maximizes) the transmission rate increase (decrease) when the server requires more bandwidth The evaluation factors used were compared with the number of changes in the fps rate, the minimum fps, the average fps, fps variability, and the number of frames to be discarded. As a result of the comparison, the proposed algorithm showed superiority in comparing the number of fps rate changes and the number of frames discarded.