• The Journal of Society for e-Business Studies
• /
• v.22 no.4
• /
• pp.103-115
• /
• 2017

Globally, frequency and scale of natural disasters are growing, also the damage is increasing. In view of the damage by natural disasters for several years, it is true that Korea is not free from such damages. In this paper, we propose a process to efficiently manage recovery resources in case of disaster damage. We utilize the IoT technology to detect the resource status in real time, and configure the process so that the state and movement of the recovery resource can be grasped in real time through the resource activity recognition module. In addition, we designed the database that is necessary to actualize it, and developed and experimented resource activity recognition module using smart-phone sensors. This will contribute to building a quick and efficient disaster response system.

• Journal of Biomedical Engineering Research
• /
• v.41 no.1
• /
• pp.55-61
• /
• 2020

Recently, there have been many research on fever management using u-healthcare technology. Especially, fever of infants requires continuous monitoring of body temperature by parents. For infants between 4 weeks and under 5 years old, it is recommended to use an electronic thermometer or chemical thermometer in the axilla, or to use an infrared thermometer. However, in order to overcome the reality of not being able to waste significant time on continuous monitoring, there have been demands of patch type thermometers with the internet of things (IoT) and wireless communication technologies. Existing IoT thermometers are difficult to attach to infants' body because they do not take into account its size, and their interoperability is not guaranteed because they do not comply with standards in communication. Therefore, in this study, a patch-type thermometer with a diameter of 20 mm and a weight of 2.9 g was developed to manage the fever of infants, while it communicates wirelessly with Bluetooth Low Energy (BLE) communication protocol and complies with IEEE 11073 PHD(Personal Health Device) at the same time. We verified its performance under the requirements of thermometers regulated by the Korean Ministry of Food and Drug Safety.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.33 no.2
• /
• pp.113-119
• /
• 2020

The IoT-based sensor network is one of the methods that can be efficiently applied to maintain the facilities, such as bridges, at a low cost. In this study, based on LoRa LPWAN, one of the IoT communications, sensor board for cable tension monitoring, data acquisition board for constructing sensor network along with existing measurement sensors, are developed to create bridge structural health monitoring system. In addition, we designed and manufactured a smart sensor node for LoRa communication and established a sensor network for monitoring. Further, we constructed a test bed at the Yeonggwang Bridge to verify the performance of the system. The test bed verification results suggested that the LoRa LPWAN-based sensor network can be applied as one of the technologies for monitoring the bridge structure soundness; this is excellent in terms of data rate, accuracy, and economy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.668-670
• /
• 2017

Visible Light Communication, which is promising as a next generation near field wireless communications, has been increased study and application case due to the development of LED technology. However, there are few application cases to IoT service due to the necessity of separate equipment for communication and limitation of light transmission to obstacles. In this paper, it propose a portable VLC transceiver module that can be connected to USB OTG and dedicated application for control to realization position possible necessary technique. The string input from the dedicated application is sent to the VLC module via USB OTG to transmit and receive data between the modules. As string transmission experiment result, it is confirmed that ASCII code transmission between VLC transceiver modules is possible through control of the implemented dedicated application.

• KIPS Transactions on Computer and Communication Systems
• /
• v.3 no.10
• /
• pp.377-382
• /
• 2014

Analysis techniques of the data over time from the mobile environment and IoT, is mainly used for extracting patterns from the collected data, to find meaningful information. However, analytical methods existing, is based to be analyzed in a state where the data collection is complete, to reflect changes in time series data associated with the passage of time is difficult. In this paper, we introduce a method for analyzing multi-block streaming data(AM-MBSD: Analysis Method for Multi-Block Stream Data) for the analysis of the data stream with multiple properties, such as variability of pattern and large capacitive and continuity of data. The multi-block streaming data, define a plurality of blocks of data to be continuously generated, each block, by using the analysis method of the proposed method of analysis to extract meaningful patterns. The patterns that are extracted, generation time, frequency, were collected and consideration of such errors. Through analysis experiments using time series data.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.6
• /
• pp.1263-1270
• /
• 2021

Recently, in the food culture life, the trend of consumers cooking is changing, and the use rate of induction cookware is increasing. Therefore, in this study, we propose the development of a functional auxiliary device to improve the safety of induction cookware to improve the convenience of cooking according to the increase in the cooking population. The proposed device is linked with IoT through the app. Through the app, the device can control the induction heating power adjustment and time reservation. In addition, an ultrasonic sensor is used to prevent the container from overflowing during cooking, and the user can safely use induction through the fine dust sensor. The implemented device conducts research assuming the actual cooking situation. Finally, it was confirmed that the user's fatigue was reduced during cooking through the device and the user's safety was improved in emergency situations such as overcooking or overflowing of water.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.12
• /
• pp.1904-1913
• /
• 2021

With the proliferation of smart phones and the development of IoT technology, it has become possible to collect personal data for public purposes. However, users are afraid of voluntarily providing their private data due to privacy issues. To remedy this problem, mainly three techniques have been studied: data disturbance, traditional encryption, and homomorphic encryption. In this work, we perform simulations to compare them in terms of accuracy, message length, and computation delay. Experiment results show that the data disturbance method is fast and inaccurate while the traditional encryption method is accurate and slow. Similar to traditional encryption algorithms, the homomorphic encryption algorithm is relatively effective in privacy preserving because it allows computing encrypted data without decryption, but it requires high computation costs as well. However, its main cost, arithmetic operations, can be processed in parallel. Also, data analysis using the homomorphic encryption needs to do decryption only once at any number of data.

• Journal of the Institute of Convergence Signal Processing
• /
• v.22 no.3
• /
• pp.99-103
• /
• 2021

Recently, convolutional neural networks (CNNs) have been widely utilized due to their outstanding performance in various computer vision fields. However, due to their computational-intensive and high memory requirements, it is difficult to deploy CNNs on hardware platforms that have limited resources, such as mobile devices and IoT devices. To address these limitations, a neural network compression research is underway to reduce the size of neural networks while maintaining their performance. This paper proposes a CNN compression technique that dynamically adjusts the thresholds of pruning, one of the neural network compression techniques. Unlike the conventional pruning that experimentally or heuristically sets the thresholds that determine the weights to be pruned, the proposed technique can dynamically find the optimal thresholds that prevent accuracy degradation and output the light-weight neural network in less time. To validate the performance of the proposed technique, the LeNet was trained using the MNIST dataset and the light-weight LeNet could be automatically obtained 1.3 to 3 times faster without loss of accuracy.

• International conference on construction engineering and project management
• /
• 2024.07a
• /
• pp.637-644
• /
• 2024

Building Information Modeling (BIM) technology has been widely adopted in the construction industry. However, a challenge encountered in the operational phase is that building object data cannot be updated in real time. The concept of Digital Twin is to digitally simulate objects, environments, and processes in the real world, employing real-time monitoring, simulation, and prediction to achieve dynamic integration between the virtual and the real. This research considers an example related to indoor air quality for realizing the concept of Digital Twin and solving the problem that the digital twin platform cannot be updated in real time. In indoor air quality monitoring, the ventilation rate and the presence of occupants significantly affects carbon dioxide concentration. This study uses the indoor carbon dioxide concentration recommended by the Taiwan Environmental Protection Agency as a reference standard for air quality measurement, providing a solution to the aforementioned challenges. The research develops a digital twin platform using Unity, which seamlessly integrates BIM and IoT technology to realize and synchronize virtual and real environments. Deep learning techniques are applied to process camera images and real-time monitoring data from IoT sensors. The camera images are utilized to detect the entry and exit of individuals indoors, while monitoring data to understand environmental conditions. These data serve as a basis for calculating carbon dioxide concentration and determining the optimal indoor air exchange volume. This platform not only simulates the air quality of the environment but also aids space managers in decision-making to optimize indoor environments. It enables real-time monitoring and contributes to energy conservation.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.9
• /
• pp.347-356
• /
• 2015

Due to the rapid development of IoT(Internet of Things) technology, traditional taxis are connected through dispatchers and location systems. Typically, modern taxis have embedded with GPS(Global Positioning System), which aims for obtaining the route information. By analyzing the frequency of taxi trip events, we can find the frequent route for a given query time. However, a scalability problem would occur when we convert the raw location data of taxi trip events into the analyzed frequency information due to the volume of location data. For this problem, we propose a NoSQL based top-K query system for taxi trip events. First, we analyze raw taxi trip events and extract frequencies of all routes. Then, we store the frequency information into hash-based index structure of MongoDB which is a document-oriented NoSQL database. Efficient top-K query processing for frequent route is done with the top of the MongoDB. We validate the efficiency of our algorithms by using real taxi trip events of New York City.