• Journal of Information Technology Services
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• v.15 no.3
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• pp.195-209
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• 2016

IoT (Internet of Things) is a collective term referring to application services that provide information through sensors/devices connected to the internet. The real world application of IoT is expanding fast along with growing number of sensors/devices. However, since IoT application relies on vertical combination of sensors/devices networks, information sharing within IoT services remains unresolved challenge. Consequently, IoT sensors/devices demand high construction and maintenance costs, rendering the creation of new IoT services potentially expensive. One solution is to launch an IoT open market for information sharing similar to that of App Store for smart-phones. Doing so will efficiently allow novel IoT services to emerge across various industries, because developers can purchase licenses to access IoT resources directly via an open market. Sharing IoT resource information through an open market will create an echo-system conducive for easy utilization of resources and communication between IoT service providers, resource owners, and developers. This paper proposes the new business model of IoT open market for information sharing, and the requirements for ensuring security and standardization of open markets.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.172-172
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• 2023

The use of low-cost IoT sensors for flow measurement in open channels has gained significant attention due to their potential to provide continuous and real-time data at a low cost. However, the accuracy and reliability of these sensors in real-world scenarios are not well understood. This study aims to compare the performance of low-cost IoT sensors in the laboratory and real-world conditions to evaluate their accuracy and reliability. Firstly, a low-cost IoT sensor was integrated with an IoT platform to acquire real-time flow rate data. The IoT sensors were calibrated in the laboratory environment to optimize their accuracy, including different types of low-cost IoT sensors (HC-SR04 ultrasonic sensor & YF-S201 sensor) using an open channel prototype. After calibration, the IoT sensors were then applied to a real-world case study in the Dorim-cheon stream, where they were compared to traditional flow measurement methods to evaluate their accuracy.The results showed that the low-cost IoT sensors provided accurate and reliable flow rate data under laboratory conditions, with an error range of less than 5%. However, when applied to the real-world case study, the accuracy of the IoT sensors decreased, which could be attributed to several factors such as the effects of water turbulence, sensor drift, and environmental factors. Overall, this study highlights the potential of low-cost IoT sensors for flow measurement in open channels and provides insights into their limitations and challenges in real-world scenarios.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.209-218
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• 2022

Industrial IoT applications, including smart factories, require two problem-solving to build data monitoring systems required by services from distributed IoT sensors (smart sensors). One is to overcome proprietary protocols, data formats, and hardware differences and to uniquely identify and connect IoT sensors, and the other is to overcome the problem of changing the server-side data storage structure and sensor data transmission format according to the addition or change of service or IoT sensors. The IEEE 1451.4 standard-based or IPMI specification-based smart sensor technology supports the development of plug-and-play sensors that solve the first problem. However, there is a lack of research that requires a second problem-solving, which requires support for the plug-in of IoT sensors into remote services. To propose a solution for the integration of these two problem-solving, we present a IoT sensor platform, a service system architecture, and a service plugin protocol for the MQTT-based IIoT application environment.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.4
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• pp.103-110
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• 2018

Services that enhance user convenience by using various IoT devices are increasing with the development of Internet of Things(IoT) technology. Also, since the price of IoT sensors has become cheaper, companies providing services by collecting and utilizing data from various sensors are increasing. The smart IoT home system is a representative use case that improves the user convenience by using IoT devices. To improve user convenience of Smart IoT home system, this paper proposes a method for the control of related devices based on data analysis. Internal environment measurement data collected from IoT sensors, device control data collected from device control actuators, and user judgment data are learned to predict the current home state and control devices. Especially, differently from previous approaches, it uses deep neural network to analyze the data to determine the inner state of the home and provide information for maintaining the optimal inner environment. In the experiment, we compared the results of the long-term measured data with the inferred data and analyzed the discrimination performance of the proposed method.

• Journal of Advanced Navigation Technology
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• v.19 no.4
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• pp.330-337
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• 2015

A service in the environments of internet of things (IoT) exist various types with automation facilities and sensors. There can configure so many communication protocols to networking facilities and sensors. To provide efficient various kind of service, a middleware platform, is based on the internet protocol network, is needed a unified access with devices, controlling and monitoring huge kind of facilities and sensors, to provide a efficient IoT service and application configurations. In this paper, we propose a middleware that an application and service interact with automation facilities and monitor sensors. The proposed middleware is designed with adapter pattern that one of the software engineering design pattern. The adapter pattern is to ensure communication with each sensor and to make sure of service scalability. Finally, the proposed component middleware shows that variety sensors can be easily configure the service in the IoT environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.31-37
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• 2018

When an IoT system is constructed, a dashboard is also developed to monitor the values of sensors in the IoT System. Much time and money, however, are spent in developing the dashboard software. This paper presents design and implementation details of a dashboard maker called as YellowPeach, which helps to create a dashboard easily and fast without programming. Using YellowPeach, the user can author a dashboard by putting predefined charts to display values of sensors in it, and store the dashboard as a JSON file. Also an web application has been developed to run the dashboard on the web browser. The dashboard viewer web application connects on MQTT-based IoT system, receives values from the sensors, and displays the values on charts in real-time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.151-156
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• 2016

The IoT technology and sensors used for collecting the environment information has rapidly increased the number and type. With the increasing need for this type of sensor effective system for selecting and testing the sensor nodes for the IoT to develop products and services. In this study, we design and implement IoT sensor testing system for IoT service and product. In order to support rapid prototyping, the proposed system provides testing and management tools for IoT sensor nodes. We analyze the requirements of the proposed system and design the system based on the functional component-specific design. Finally, we implement testing application to verify the functional elements of the proposed system.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.9-17
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• 2023

Recently, IoT technology has been widely used in many industries. Also research on integrating IoT technology with IoT sensors is actively underway. One of the important challenges in IoT is to support low-latency communication. With the development of communication networks and protocols, a variety of protocols are being used, and their performance is improving. In this paper, we compare the performance and analyze the characteristics of some of the major communication protocols in IoT application, namely MQTT, HTTP, and HTTPS. IoT sensors acquired data by connecting an Arduino equipped with ESP8266 and a temperature and humidity sensor (DHT11). The server measured the performance by building servers for each protocol using AWS EC2. We analyzed the packets transmitted between the Arduino and the server during the data transmission. We measured the amount of data and transfer time. The measurement results showed that MQTT had the lowest data transmission time and data amount among the three protocols.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.75-83
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• 2018

Predictive IoT Sensor Algorithm is a technique of data science that helps computers learn from existing data to predict future behaviors, outcomes, and trends. This algorithm is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. Sensors and computers collect and analyze data. Using the time series prediction algorithm helps to predict future temperature. The application of this IoT in industrial environments like power plants and factories will allow organizations to process much larger data sets much faster and precisely. This rich source of sensor data can be networked, gathered and analyzed by super smart software which will help to detect problems, work more productively. Using predictive IoT technology - sensors and real-time monitoring - can help organizations exactly where and when equipment needs to be adjusted, replaced or how to act in a given situation.

• Current Photovoltaic Research
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• v.9 no.3
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• pp.106-109
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• 2021

In order to perform photovoltaic (PV) operation and management (O&M) efficiently, individual PV module monitoring is becoming more important. In this research, we developed wireless IoT sensor which can monitor individual photovoltaic modules. This IoT sensor can detect the output voltage, current and module temperature of individual modules and provide monitored data by wireless communication. Measured voltage error was 1.23%, and it shows 16.6 dBM, 0.42sec and 7.1 mA for voltage, transmittance output, response time and mean power consumption, respectively. IoT sensors were demonstrated in the test field with real climate environment condition and each of 5 sensors showed precise results of voltage, current and temperature. Also, sensors were compared with commercial power-optimizers and showed result difference within 5%.