• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.514-516
• /
• 2022

Busan Metropolitan City runs Community Health Center which aims to health care service based on the community, besides the established health medical service towards people with low-income. 71 centers are run in 2021, therefore, this papear explores the way of digital transition of these centers. Digital Technologies possibly adopted inside the centers are: First, smart devices to advance the management system of chronical diseases based on health index; Second, IoT with mobile tech to manage health index; Third, AI Robot to care lone elderly people and to warn the emergency.

• Journal of Broadcast Engineering
• /
• v.21 no.3
• /
• pp.298-306
• /
• 2016

With the advent of Internet of Things (IoT) technology that allows the communications between things and devices over the Internet, a lot of researches on the IoT services, such as smart home or healthcare, have been progressed. In the existing machine-to-machine (M2M) communications, however, since the underlying link-layer technologies, such as Bluetooth or ZigBee, do not use the Internet Protocol (IP) communication, those technologies are not suitable to provide the IoT services. Accordingly, this paper discusses how to provide the Internet services in the M2M communication, and propose an implementation of the Constrained Application Protocol (CoAP) over 6LoWPAN for providing IoT services in the BLE networks. Based on the implementation, we compared the performance between HTTP and CoAP for IoT communications. From the experimental results, we can see that the CoAP protocol gives better performance than the HTTP protocol with two times higher throughput, 21% faster transmission time, and 22% smaller amount of generated packets.

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

• Electronics and Telecommunications Trends
• /
• v.34 no.5
• /
• pp.58-70
• /
• 2019

In this paper, we present the R&D status of ETRI's Trusted Reality (TR) project and its core technologies. ETRI's TR project focuses on the next-generation paradigm of smart phones, ETRI-TR Smart Glasses, which aims to provide the same features as those of smart phones without the involvement of any handheld device. Furthermore, they are characterized by additional features enabled by trustworthy VR/AR/MR/XR, such as privacy masking/unmasking, distributed structure of thin-client computing/networking among TR-Glasses, TR-LocalEdge, and TR-RemoteEdge, with novel see-through eyes-direct communication between IoT real/virtual objects and human eyes. Based on these core technologies of the ETRI's TR project, the human-held ETRI-TR Smart Glasses is expected to aid in the realization of XR vision with particularly more XR's safe_privacy on social life in the near future.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.5
• /
• pp.63-71
• /
• 2019

Recently, there has been a lot of research on the construction of smart factory in the 4th Industrial Revolution era. Among the various technologies involved in the deployment of smart factory, one of the key technologies is the IoT protocol sector that handles the transmission and reception of data. In this regard, the MQTT protocol is generally used most commonly, but the existing MQTT technology lacks the concept of priorities of messages, so it is somewhat insufficient to be applied to an industrial field requiring real-time property. Priority handling of urgent messages is critical, especially in emergency situations, such as the emergency shutdown of the entire relevant facility following the failure of a particular facility. To improve this, research on priority-based MQTT is being conducted somewhat, but these studies have problems with actual field use because they are a variant of the MQTT standard. Therefore, this study conducts and verifies studies related to MQTT, which can prioritize messages while adhering to existing MQTT standards.

• Journal of Digital Contents Society
• /
• v.18 no.6
• /
• pp.1175-1182
• /
• 2017

Recent trend in the manufacturing industry is focused on the convergence with IoT and Big Data, by emergence of the 4th Industrial Revolution. To realize a smart factory, the proposed system based on MTConnect technology collects and integrates various status information of machines from many production facilities including heterogeneous devices. Also it can distribute the acquisited status of heterogeneous manufacturing machines to the remote devices. As a key technology of a flexible automated production line, the proposed system can provide much possibility to manage important information such as error detection and processing state management in the unmanned automation line.

• KIISE Transactions on Computing Practices
• /
• v.22 no.7
• /
• pp.320-325
• /
• 2016

By developing the IoT(Internet of Things) technology, devices for smart home environment have rapidly increased. With respect to mobiles, these applications are used to control and manage the various smart devices effectively. However, the existing mechanisms only provide simple information, and hence a difficulty to search or control the smart devices persists, since there is no meaningful relationship between them. In this research, we suggest an interface which visualizes the device's data and controls them effectively, based on the user's device using pattern. As a solution for this problem, we classify the user pattern based on a timeline for the associated circumstance, and visualize the device's data to make a group or to control individually in an easier approach. Also, all meaningful information could be confirmed by summarizing all the data of smart devices.

• KIPS Transactions on Computer and Communication Systems
• /
• v.9 no.4
• /
• pp.89-100
• /
• 2020

In order to reduce the time and cost used in insurance processing, studies have been actively carried out to apply blockchain smart contract technology to car insurance. However, by using traffic data that is insufficient to prove accidents, existing studies are being exposed to the risk of insurance fraud, such as forgery and overstated damage by malicious insurers. To solve this problem, we propose an accident data-based reliability estimation model by using both various types of data through sensors, RSUs, and IoT devices embedded in automobiles and smart contracts. In particular, the regression model was applied in consideration of the weight estimation according to the type of traffic accident data and the reliability estimation model trained according to various accident situations. The proposed model is expected to effectively reduce fraud and insurance litigation while providing transparency in the insurance process and streamlining it is well.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.12
• /
• pp.2348-2354
• /
• 2016

In recent days, IoT (Internet of Things) technology has been widely used in the field of agriculture, which enables the collection of environmental data and biometric data into the database. The availability of big data on agriculture results in the increase of the machine learning based analysis. Through the analysis, it is possible to forecast agricultural production and the diseases of livestock, thus helping the efficient decision making in the management of smart farm. Herein, we use the environmental and biometric data of Smart Pig farm to derive the accurate relationship model between the environmental information and the daily weight increase of swine and verify the accuracy of the derived model. To this end, we applied the M5P tree algorithm of machine learning which reveals that the wind speed is the major factor which affects the daily weight increase of swine.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.11
• /
• pp.1-8
• /
• 2020

In this paper, we proposed a smart greenhouse system that can easily grow plants indoors without professional knowledge by using the criteria of factors affected by common plants (temperature, humidity, soil humidity), and implemented a system that can check the greenhouse state in real time and control the device remotely through mobile applications. Based on Raspberry pie and Arduino, the system measures the state of greenhouse in real time through sensors and automatically controls the device. After growing and experimenting with plants in a greenhouse for a certain period of time, it was confirmed that the environment suitable for each plant was maintained. Therefore, the smart greenhouse system in this paper is expected to improve plant cultivation efficiency and user convenience and also increase beginners' access to plants.