• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.114-122
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• 2018

In this paper, we propose new water pressure measurement system to measure the water pressure of water pipe laid underground beneath the manhole efficiently. For this purpose, we installed water pressure sensor(IoT) which has built-in bluetooth module at valve of water pipe. The proposed system can be managed through collected data which measured at sensor and then transmitted to smart phone through bluetooth connectivity and re-transmitted to server on this system. By checking out water pressure data stored in server from remote location, the persons in charge can confirm the leakage of water pipe or propriety of water pressure in management area. By this procedure, they can detect the existence of condition of water pipe and manage water pressure of water pipe efficiently.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.29-35
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• 2018

Safety accidents are frequently occurring in day care centers in recent years. The number of types of safety accidents is bumping into, falling, burning, school bus accident, insertion... etc., and the number of children who have died due to such accidents is increasing steadily every year. Therefore, it is urgent to prevent accidents at day care centers. IoT (Internet of Things) is managed by connecting various sensors and related products from the living space to the Internet in order to prevent them from being dangerous. In particular, IoT products can be automatically controlled by smart phones and sensors anytime and anywhere, thus saving energy, time, convenience and prompt accuracy. This paper proposes a research model to prevent and respond to disasters by using SK LoRa communication network and Arduino, which are Internet access networks for building disaster management in schools, kindergartens and day care centers. And various sensors needed for building disaster management express various safety states in the building and suggests a system that can control the residential environment by transmitting and receiving data to smart phone.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.147-154
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• 2017

This paper aims to build a home security system based on IoT to monitor a home on a mobile phone. The system consists of data gathering sensors, camera, gateway and Xively platform. The Raspberry Pi collects data from the three sensors and sends the data to Xively, and sends the video stream of home to a client in a smart phone through a internet. The servers are composed of Xively, socket server in Raspberry Pi and E-mail server in Google. The proposed system transmits e-mail, text message, and video stream when there are motion, fire, and gas leakage, and can control the gas valve through Raspberry Pi. The experimental results show that a user gets 'emergency E-mail' and text message and watches the video stream of the home through WIFI or LTE on a smart phone.

• Smart Media Journal
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• v.9 no.3
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• pp.41-45
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• 2020

Recently, artificial intelligence (AI) and the Internet of things (IoT), which are represented by machine learning and deep learning among IT technologies related to the Fourth Industrial Revolution, are applied to our real life in various fields through various researches. In this paper, IoT and AI using object recognition technology are applied to classify clothing. For this purpose, the image dataset was taken using webcam and raspberry pi, and GoogLeNet, a convolutional neural network artificial intelligence network, was applied to transfer the photographed image data. The clothing image dataset was classified into two categories (shirtwaist, trousers): 900 clean images, 900 loss images, and total 1800 images. The classification measurement results showed that the accuracy of the clean clothing image was about 97.78%. In conclusion, the study confirmed the applicability of other objects using artificial intelligence networks on the Internet of Things based platform through the measurement results and the supplementation of more image data in the future.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.377-383
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• 2018

Internet of Things (IoT) is producing various data as the smart environment comes. The IoT data collection is used as important data to judge systems's status. Therefore, it is important to monitor the anomaly state of the sensor in real-time and to detect anomaly data. However, it is necessary to convert the IoT data into a normalized data structure for anomaly detection because of the variety of data structures and protocols. Thus, we can expect a good quality effect such as accurate analysis data quality and service quality. In this paper, we propose an anomaly detection system based on big data from collected sensor data. The proposed system is applied to ensure anomaly detection and keep data quality. In addition, we applied the machine learning model of support vector machine using anomaly detection based on time-series data. As a result, machine learning using preprocessed data was able to accurately detect and predict anomaly.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.177-186
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• 2021

This paper aims to show that cooperative robots, which have only been used in manufacturing sites, are expanding their scope of use in daily living spaces due to the expansion of non-face-to-face services. By combining robots and IoT technologies in terms of diversifying services in daily life and customized service areas, it is expected that the general public will also have easy access to smart technologies, and these technologies will be used in more areas. The robot barista system will provide customers with the services they want, monitoring, maintenance, and management of the system, making this paper convenient for customers, as well as managers who run stores, maintenance and repair, and engineers who design the system. This paper attempts to demonstrate this through a structure called Robopresso.

• Smart Media Journal
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• v.12 no.2
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• pp.42-55
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• 2023

The combination of blockchain (BC), artificial Intelligence (AI), quantum computing (QC), and the Internet of Things (IoT) can potentially transform various industries and domains, including healthcare, logistics, and finance. In this paper, we look at the trends and developments in integrating these emerging technologies and the potential benefits and challenges that come with them. We present a conceptual framework for integrating BC, AI, QC, and IoT and discuss the framework's key characteristics and challenges. We also look at the most recent cutting-edge research and developments in integrating these technologies, as well as the key challenges and opportunities that come with them. Our analysis highlights the potential benefits of integrating the technologies and looks to increased security, privacy, and efficiency to provide insights into the future of these technologies.

• Smart Media Journal
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• v.12 no.10
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• pp.85-92
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• 2023

In December 2014, Livestock and Livestock Products Traceability Act was established, allowing consumers to receive livestock traceability information. While the Livestock Traceability System provides consumers with transparent and fair information about their food, it has brought increased workload and penalty burdens to stakeholders in the livestock industry. In this paper, we propose an IoT system for inventory management based on traceability numbers to enable sellers to conveniently provide livestock traceability information to consumers. We analyzed the protocol for managing data from electronic scales and conducted functional testing and verification on mobile devices. Furthermore, we implemented the design and system functionality, taking into account UI/UX on Android OS-based devices to synchronize and interconnect traceability and product information with electronic scales. We anticipate that the proposed approach will minimize user inconvenience and raise production efficiency in the existing market.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.120-123
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• 2015

The use of smart devices worldwide has been increasing day by day and its applications based on IoT have been also extended. But the power control system requires complicated control and processing information from the various sensors in practice. One of the best ways to save the power consumption is to manage electrical equipment individually on the Internet. In this paper, remote power control system for managing the power through the relay switch module via Python server was implemented by using Raspberry Pi. The proposed power control system can be used anywhere over the Internet.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1459-1466
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• 2017

Recently, the development of the smart home field provides a range of services to install and keep the smart home appliance in a user's residential environment pleasantly. However, the conventional system method is not convenient enough to use properly because users have to select a device and manually operate the device on their own. In this paper, we propose a system to set the priority of the devices selected by the user and proceed with the task. When a user selects a device, the system recommends an optimal device associated with the device. The system compares and sets the priority of each device, carrying out the task one by one according to the set priority. Therefore, the proposed system is expected to provide users with increased convenience and more efficient task management.