• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.2
• /
• pp.271-278
• /
• 2021

This paper is a study on the implementation of smart filter system that recognizes the external environment and automatically removes pollutants according to pollution level. Recently, the occurrence of various pollutants in indoor and outdoor space has adversely affected the human body. Especially, various fine dust generated in the atmosphere becomes worse in closed residential space or office space. Although air pollution can be temporary lowered through ventilation, it is difficult to respond to fine dust changes in real time, and such problems become serious in the space where many people reside, such as at home or industry. Therefore, it is necessary to measure the pollution level of fine dust inside the residential space in real time and to reduce the pollution of indoor ventilation through automatic ventilation with the outside. To improve these problems, this paper proposes the implementation of smart filter system for external environment recognition. The structure of smart filter system that automatically measures air quality inside and outside, removes pollutants, implements the function, and confirms the operability by manufacturing prototypes. Finally, the effectiveness of the smart filter system for solving fine dust problems was examined.

• Journal of the Korea Convergence Society
• /
• v.11 no.12
• /
• pp.23-30
• /
• 2020

In this study, the relationship between natural gas (NG) data and gas-related environmental elements was performed using machine learning algorithms to predict the level of gas leakage risk without directly measuring gas leakage data. The study was based on open data provided by the server using the IoT-based remote control Picarro gas sensor specification. The naturel gas leaks into the air, it is a big problem for air pollution, environment and the health. The proposed method is multivariate outlier removing method based Random Forest (RF) classification for predicting risk of NG leak. After, unsupervised k-means clustering, the experimental dataset has done imbalanced data. Therefore, we focusing our proposed models can predict medium and high risk so best. In this case, we compared the receiver operating characteristic (ROC) curve, accuracy, area under the ROC curve (AUC), and mean standard error (MSE) for each classification model. As a result of our experiments, the evaluation measurements include accuracy, area under the ROC curve (AUC), and MSE; 99.71%, 99.57%, and 0.0016 for MOL_RF respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.6
• /
• pp.74-87
• /
• 2020

Overloaded trucks are the main source that threatens road safety and directly affects the reduction of pavement life. The On-board truck scale is the only equipment that could prevent overloading by measuring and adjusting the loading weight before driving. Legislation is needed to encourage its installation so that the driver can prevent overloading. In this study, an on-board truck scale system was installed on 30 dump trucks for transporting construction waste, such as soil and aggregates, which are major loads of 36.55% for overloading, and the trucks were monitored remotely. The overload prevention effect was analyzed by comparing driving data for 1 month before distribution of the weight display app that can recognize the weight to the driver and 1 month after distribution. After installation, overloading could be 6.1% reduced, and the transportation efficiency could be increased by checking the weight provided from the On-board truck scale system.

• Journal of Platform Technology
• /
• v.9 no.4
• /
• pp.79-89
• /
• 2021

In this paper, the fine dust (PM10) and ultrafine dust (PM2.5) measurement platforms are designed to be mobile and fixed using oneM2M, the international standard for IoT. The fine dust measurement platform is composed and designed with a fine dust measurement device, agent, oneM2M platform, oneM2M IPE, and monitoring system. The main difference between mobile and fixed is that the mobile uses the MQTT protocol for interconnection between devices and services without blind spots based on LTE connection, and the fixed uses the LoRaWAN protocol with low power and wide communication range. Not only fine dust, but also temperature, humidity, atmospheric pressure, volatile organic compounds (VOC), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), and noise data related to daily life were collected. The collected sensor values were managed using the common API provided by oneM2M through the agent and oneM2M IPE, and it was designed into four resource types: AE and container. Six functions of operability, flexibility, convenience, safety, reusability, and scalability were analyzed through the fine dust measurement platform design.

• Journal of Broadcast Engineering
• /
• v.27 no.6
• /
• pp.872-884
• /
• 2022

With the development of the IoT industry, different types of time series data are being generated in various industries, and it is evolving into research that reproduces and utilizes it through re-integration. In addition, due to data processing speed and issues of the utilization system in the actual industry, there is a growing tendency to compress the size of data when using time series data and integrate it. However, since the guidelines for integrating time series data are not clear and each characteristic such as data description time interval and time section is different, it is difficult to use it after batch integration. In this paper, two integration methods are proposed based on the integration criteria setting method and the problems that arise during integration of time series data. Based on this, integration framework of a heterogeneous time series data was constructed that is considered the characteristics of time series data, and it was confirmed that different heterogeneous time series data compressed can be used for integration and various machine learning.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.27 no.1
• /
• pp.54-61
• /
• 2023

With the development of IoT technologies and artificial intelligent, diverse digital image equipments are being used in industrial sites. Because image data can be easily damaged by noise while it's obtained with a camera or a sensor and the damaged image has a bad effect on the process of image processing, noise removal is being demanded as preprocessing. In this thesis, for the restoration of image damaged by the noise of random impulse, a switching filter algorithm based on noise estimation was suggested. With the proposed algorithm, noise estimation and error distraction were carried out according to the similarity of the pixel values in the local mask of the image, and a filter was chosen and switched depending on the ratio of noise existing in the local mask. Simulations were conducted to analyze the noise removal performance of the proposed algorithm, and as a result of magnified image and PSNR comparison, it showed superior performance compared to the existing method.

• International journal of advanced smart convergence
• /
• v.11 no.3
• /
• pp.187-196
• /
• 2022

In this paper, we propose an example of designing and constructing a roof-type solar power plant structure equipped with a Pseudo-BIPV (Building-Integrated Photovoltaic) shape suitable for use as a roof of a small warehouse with a sandwich-type panel structure. As the characteristics of the roof-type solar power generation facility to be installed in the small warehouse proposed in this study, the shape of the roof is not a general A type, but a right-angled triangle shape with the slope is designed to face south. We chose a structure in which an inverter for one power plant and a control facility are linked by grouping several roofs of buildings. In addition, the height of the roof structure is less than 20 cm from the floor, and it has a shape similar to that of the BIPV, so it is building-friendly because it is almost in close contact with the roof. At the same time, the roof creates a reflective light source due to the white color. By linking this roof with a double-sided solar panel, we designed it to obtain both the advantage of the roof-friendliness and the advantage of efficiency improvement for the electric power generation based on the double-sided panel. Compared to the existing solar power generation facilities using A-shaped cross-sectional modules, the power generation efficiency of roofs in this case is increased by more than 11%, which we can confirm, through the comparison analysis of monitoring data between power plants in the same area. Therefore, if the roof-type solar structure suitable for the small warehouse we have presented in this paper is used, the facilities of electric power generation is eco-friendly. Further it is easier to obtain facility certification compared to the BIPV, and improved capacity of the power generation can be secured at low material cost. It is believed that the roof-type solar power generation facility we proposed can be usefully used for warehouse or factory-based smart housing. Sensor devices for monitoring, CCTV monitoring, or safety and environment management, operating in connection with the solar power generation facilities, are linked with the Internet of Things (IoT) solution, so they can be monitored and controlled remotely.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.478-480
• /
• 2022

Smart Railway as a next generation railway technology is expected to have rapid evolution with developments of information and communications tehchology. Especially, smart railway will be progressed more evolved transportation means for railway operation and costomer service based with spread of commercial 5G communication. So, it is very important to investigate and analyze trends of smart railway related tehcnology of 5G mobile communication for samrt railway infra structure, server technolgy for AI, big data, deep learning, information security technology, sensor and IoT. In this paper, 5G based communicaion technology and application techology related smart railway is described and trends of new techlogy on this communication tehnology is investigated. The results of this study can be used for smart railway study and implementation, research and development for smart railway communicaion technology, etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.213-215
• /
• 2021

With the development of IoT technology, various technologies such as artificial intelligence and automation are being grafted into industrial sites, and accordingly, the importance of data processing is increasing. In particular, a system based on a digital image may cause a malfunction due to noise in the image due to a sensor defect or a communication environment problem. Therefore, research on image processing has been continued as a pre-processing process, and an effective noise reduction technique is required depending on the type of noise and the characteristics of the image. In this paper, we propose a modified spatial weight filter to protect edge components in the impulse noise reduction process. The proposed algorithm divides the filtering mask into four regions and calculates the standard deviation of each region. The final output was filtered by applying a spatial weight to the region with the lowest standard deviation value. Simulation was conducted to evaluate the performance of the proposed algorithm, and it showed superior impulse noise reduction performance compared to the existing method.

• Journal of Environmental Health Sciences
• /
• v.48 no.1
• /
• pp.44-51
• /
• 2022

Background: Air pollution is increasing together with industrialization and urbanization. In order to reduce air pollution, public transportation is recommended rather than private cars, and the number of passengers using public transportation is increasing accordingly. This study observes the concentration of indoor pollutants in city buses over time. Through this means, we intend to suggest a plan to manage the indoor air quality in city buses. Objectives: The concentration of indoor pollution in public transportation was investigated from April 2021 to January 2022. Based on this, we evaluated the exposure to indoor pollutants. Methods: Six city bus lines in an industrial city were selected for the research, and indoor pollution was measured through IoT (Internet of Things)-based sensor-type measuring devices. The concentration of pollutants was measured every minute, and statistical data were constructed based on the measurement results. Results: In all the city buses studied, the average concentration of pollutants were below the guidelines. However, some measurement results showed cases of exceeding the guidelines. As a result of the analysis by time zone, there were more cases in which pollutants exceeded the standard value during rush hour compared to at other times. A risk assessment for PM₁₀ was performed by evaluating the excess mortality risk from exposure and the risk from inhalation exposure. Conclusions: All measured indoor pollutants in the city buses did not exceed the guidelines. Also, the risk assessment results were found to be within the level of safety. However, if a city bus is used for a long time, there is a possibility that there may be an impact on the human body due to inhalation exposure, so additional management is required.