• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.121-129
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• 2021

In addition to yellow dust occurring in China, fine dust has become a hot topic in Korea through news and media. Although there is fine dust generated from the outside, the purchase rate of air purifier products is increasing as external fine dust flows into the inside. The air purifier uses a filter internally, and the sensor notifies the user through the LED alarm whether the filter is replaced. However, there is currently no product measuring how much the filter rate is reduced and determining the pressure of the blower to operate. Therefore, in this paper, data are generated directly using Arduino, fine dust sensor, and differential pressure sensor. In addition, a program was developed using Python programming to calculate how old the filter is and to analyze the wind power of the blower according to the filter rate by calculating the measured dust and pressure values.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1347-1356
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• 2022

In this paper, we investigate the properties of CoGe thin film-based galvanic cells as a function of their dimension (cell length, width, etc.) and show their application as sensors to Arduino-based IoT sensor networks to detect water contact. Because these CoGe thin film-based galvanic cells do not require mechanical strains or temperature gradients unlike piezoelectric and thermoelectric energy harvesters, we think that these thin film-based galvanic cells are more suitable for self-powered sensor networks demanding sustainable and robust energy harvesters. In the past, a sputter-deposited CoGe thin film has not been intensively investigated for energy harvesting appilcations. Thus, in this study, we perform a feasibility study of galvanic cells composed of a sputter-deposited CoGe thin film to see if they can be applied as potential self-powered sensors. We believe that this paper will be of great help in developing even more enhanced sensor networks.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.273-281
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• 2019

The energy consumed by buildings among the total national energy consumption is more than 10% of the total. For this reason, Korea has adopted the zero energy building policy since 2025, and research on the energy saving technology of buildings has been demanded. Analysis of buildings' energy consumption patterns shows that lighting, heating and cooling energy account for more than 60% of total energy consumption, which is directly related to solar power acquisition and window opening and closing operation. In this paper, we have developed a low - power IoT sensor module for window system to transfer acquired information to building energy management system. This module transmits the external environment and window opening / closing status information to the building energy management system in real time, and constructs the network to actively take energy saving measures. The power used in the module is designed as an independent power source using solar power among the harvest energy. The topology of the power supply is a Buck converter, which is charged at 4V to the lithium ion battery through MPPT control, and the efficiency is about 85.87%. Communication is configured to be able to transmit in real time by applying WiFi. In order to reduce the power consumption of the module, we analyzed the hardware and software aspects and implemented a low power IoT sensor module.

• Journal of the Korean Geosynthetics Society
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• v.23 no.2
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• pp.43-52
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• 2024

Recent abnormal climate conditions have increased the risk of slope collapses, which frequently result in significant loss of life and property due to the absence of early prediction and warning dissemination. In this paper, we develop a slope condition analysis system using IoT sensors and AI-based camera to assess the condition of slopes. To develop the system, we conducted hardware and firmware design for measurement sensors considering the ground conditions of slopes, designed AI-based image analysis algorithms, and developed prediction and warning solutions and systems. We aimed to minimize errors in sensor data through the integration of IoT sensor data and AI camera image analysis, ultimately enhancing the reliability of the data. Additionally, we evaluated the accuracy (reliability) by applying it to actual slopes. As a result, sensor measurement errors were maintained within 0.1°, and the data transmission rate exceeded 95%. Moreover, the AI-based image analysis system demonstrated nighttime partial recognition rates of over 99%, indicating excellent performance even in low-light conditions. Through this research, it is anticipated that the analysis of slope conditions and smart maintenance management in various fields of Social Overhead Capital (SOC) facilities can be applied.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.6
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• pp.60-71
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• 2019

As IoT systems such as smart farms and smart cities become popular, a large amount of data collected from many sensor nodes is sent to a server in the Internet, which causes network traffic explosion, delay in delivery, and increase of server's workload. To solve these problems, the concept of fog computing has been proposed to store data between IoT systems and servers. In this study, we implemented a software platform of the fog node and applied it to the prototype smart farm system in order to check whether the problems listed above can be solved when using the fog node. When the fog node is used, the time taken to control an IoT device is lower than the response time of the existing IoT device-server case. We confirmed that it can also solve the problem of the Internet traffic explosion and the workload increase in the server. We also showed that the intelligent control of IoT system is feasible by having the data visualization in the server and real time remote control, emergency notification in the fog node as well as data storage which is the basic capability of the fog node.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.7
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• pp.227-234
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• 2015

USN-based real-time monitoring systems, which receive raw data from sensor nodes and store the processed information in traditional servers, recently get to be replaced by IoT(Internet of Things)/WoT(Web of Things)-based ones. Especially, Social Web of Things(SWoT) paradigm can make use of cloud storage over Social Network Service(SNS) and enable the possibility of integrated access, management and sharing. This paper proposes an improved SWoT-based real-time monitoring system which makes up for weak points of existing systems, and implements monitoring service integrating a legacy sensor network and commercial SNS without requiring additional servers. Especially, the proposed system can reduce emergency propagation time by employing PUSH messages.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.169-178
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• 2023

Wireless sensor network is wieldy use for IoT application. The sensor node consider as physical device in IoT architecture. This all sensor node are operated with battery so the power consumption is very high during the data communication and low during the sensing the environment. Without proper planning of data communication the network might be dead very early so primary objective of the cluster based routing protocol is to enhance the battery life and run the application for longer time. In this paper we have comprehensive of twenty research paper related with clustering based routing protocol. We have taken basic information, network simulation parameters and performance parameters for the comparison. In particular, we have taken clustering manner, node deployment, scalability, data aggregation, power consumption and implementation cost many more points for the comparison of all 20 protocol. Along with basic information we also consider the network simulation parameters like number of nodes, simulation time, simulator name, initial energy and communication range as well energy consumption, throughput, network lifetime, packet delivery ration, jitter and fault tolerance parameters about the performance parameters. Finally we have summarize the technical aspect and few common parameter must be fulfill or consider for the design energy efficient cluster based routing protocol.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.942-949
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• 2016

Efficient routing protocols designed for Wireless Sensor Networks (WSN) can be extended and applied to Internet of Things (IoT) data routing, as IoT can be considered to be an extension from WSN. When the size of the data in IoT is often bigger than in conventional WSNs, existing cluster routing protocol such as LEACH may cause high data loss rate due to its incomplete load balancing. We present an enhanced LEACH-based protocol which can minimize the data loss which is an important performance measure in IoT. In our proposed protocol, the base station estimates the location of nodes by the trilateration technique to make sure optimal number of cluster heads and members in a deterministic manner. We evaluate our proposed protocol via computer simulations in terms of data loss rate and average network lifetime.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.87-96
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• 2019

Low power issue is one of the most critical problems in the Internet of Things (IoT), which are powered by battery. To solve this problem, various approaches have been presented so far. In this paper, we propose a method to reduce the power consumption by reducing the numbers of accesses into the flash memory consuming a large amount of power for on-chip software execution. Our approach is based on using cooperative logging structure to distribute the sampling overhead in single sensor node to adjacent nodes in case of rare-event applications. The proposed algorithm to identify event occurrence is newly introduced with negative feedback method by observing difference between past data and recent data coming from the sensor. When an event with need of flash access is determined, the proposed approach only allows access to write the sampled data in flash memory. The proposed event detection algorithm (EDA) result in 30% reduction of power consumption compared to the conventional flash write scheme for all cases of event. The sampled data from the sensor is first traced into the random access memory (RAM), and write access to the flash memory is delayed until the page buffer of the on-chip flash memory controller in the micro controller unit (MCU) is full of the numbers of the traced data, thereby reducing the frequency of accessing flash memory. This technique additionally reduces power consumption by 40% compared to flash-write all data. By sharing the sampling information via LoRa channel, the overhead in sampling data is distributed, to reduce the sampling load on each node, so that the 66% reduction of total power consumption is achieved in several IoT edge nodes by removing the sampling operation of duplicated data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.139-143
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• 2019

Measurement of flow rate is required in various fields. Water meters are often used at home, and flow meters are used in water and sewage plants, petrochemical industries and so on.. A system is needed to monitor the flow rate in real time and notify immediately when flow rate is abnormal. Recently, with the development of the IoT it is possible to construct such devices at low cost. WeMos can be programmed with Arduino IDE as a mini wifii IoT module. The flow sensor can output a digital pulse proportional to the flow rate. In this paper, we developed the flow monitoring and warning system using WeMos and IoT technology. When the system operates, it calculates the flow rate, sends the value as JSON format to the server, monitors the flow rate as graph from the remote with the smartphone. We also implement the system to promptly send alert message to the smart phone using Pushbullet when the flow rate is abnormal.