• Title/Summary/Keyword: Indoor method

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Evaluation Method for Improvement of Indoor Air Quality Using Mass Balance (물질수지를 이용한 실내공기질 개선정도 평가)

  • Kim, Young-Hee;Kim, Moon-Hyeon;Yang, Won-Ho
    • Journal of Environmental Science International
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    • v.15 no.10
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    • pp.913-918
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    • 2006
  • Despite the wide distribution of air pollutants, the concentrations of indoor air pollutants may be the dominant risk factor in personal exposure due to the fact that most people spend an average of 80% of their time in enclosed buildings. Researches for improvement of indoor air quality have been developed such as installation of air cleaning device, ventilation system, titanium dioxide$(TiO_2)$ coating and so on. However, it is difficult to evaluate the magnitude of improvement of indoor air quality in field study because indoor air quality can be affected by source generation, outdoor air level, ventilation, decay by reaction, temperature, humidity, mixing condition and so on. In this study, evaluation of reduction of formaldehyde and nitrogen dioxide emission rate in indoor environments by $TiO_2$ coating material was carried out using mass balance model in indoor environment. we proposed the evaluation method of magnitude of improvement in indoor air quality, considering outdoor level and ventilation. Since simple indoor concentration measurements could not properly evaluate the indoor air quality, outdoor level and ventilation should be considered when evaluate the indoor net quality.

An Analysis about Recognition of Indoor Air Quality of Workers at Dental Clinics in Jeollanamdo Area

  • Choi, Mi-Suk
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.11
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    • pp.137-142
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    • 2018
  • The purpose of this study is to contribute to the improvement of indoor air quality management in dental clinic by investigating the level of indoor air quality recognition among dental clinic workers. The questionnaire survey was conducted for about 4 weeks from May 20 to June 20, 2018 in dental clinics located in Jeollanamdo area and 143 were used as the analysis data. The method of indoor air quality management in dental clinic was preferred to "natural ventilation" method and the number of natural ventilation was 1 to 2 times per day and the results of survey on indoor environment satisfaction showed that satisfaction level was lowest in noise and smell items. The types of subjective symptoms experienced by workers working at dental clinics are "cough", "eye burn", and "headache" and a survey on the degree of the relationship between subjective symptoms and indoor air quality showed that 94.4% (135) of respondents answered "very relevant" and "slightly related". As a result of multiple regression analysis, the variables affecting the indoor air quality satisfaction of the dental clinic staff were analyzed as the items such as lighting, noise, main work, number of patients, comparing indoor and outdoor air quality and among them, "comparing indoor and outdoor air quality" was analyzed as having a great influence. To improve the indoor air quality satisfaction of dental clinic worker adequate ventilation, designate the person responsible for the indoor air quality management and periodic measurement efforts will be necessary.

Ceiling-Based Localization of Indoor Robots Using Ceiling-Looking 2D-LiDAR Rotation Module (천장지향 2D-LiDAR 회전 모듈을 이용한 실내 주행 로봇의 천장 기반 위치 추정)

  • An, Jae Won;Ko, Yun-Ho
    • Journal of Korea Multimedia Society
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    • v.22 no.7
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    • pp.780-789
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    • 2019
  • In this paper, we propose a new indoor localization method for indoor mobile robots using LiDAR. The indoor mobile robots operating in limited areas usually require high-precision localization to provide high level services. The performance of the widely used localization methods based on radio waves or computer vision are highly dependent on their usage environment. Therefore, the reproducibility of the localization is insufficient to provide high level services. To overcome this problem, we propose a new localization method based on the comparison between ceiling shape information obtained from LiDAR measurement and the blueprint. Specifically, the method includes a reliable segmentation method to classify point clouds into connected planes, an effective comparison method to estimate position by matching 3D point clouds and 2D blueprint information. Since the ceiling shape information is rarely changed, the proposed localization method is robust to its usage environment. Simulation results prove that the position error of the proposed localization method is less than 10 cm.

Automated Construction of IndoorGML Data Using Point Cloud (포인트 클라우드를 이용한 IndoorGML 데이터의 자동적 구축)

  • Kim, Sung-Hwan;Li, Ki-Joune
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.6
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    • pp.611-622
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    • 2020
  • As the advancement of technologies on indoor positioning systems and measuring devices such as LiDAR (Light Detection And Ranging) and cameras, the demands on analyzing and searching indoor spaces and visualization services via virtual and augmented reality have rapidly increasing. To this end, it is necessary to model 3D objects from measured data from real-world structures. In addition, it is important to store these structured data in standardized formats to improve the applicability and interoperability. In this paper, we propose a method to construct IndoorGML data, which is an international standard for indoor modeling, from point cloud data acquired from LiDAR sensors. After examining considerations that should be addressed in IndoorGML data, we present a construction method, which consists of free space extraction and connectivity detection processes. With experimental results, we demonstrate that the proposed method can effectively reconstruct the 3D model from point cloud.

Generation of Indoor Network by Crowdsourcing (크라우드 소싱을 이용한 실내 공간 네트워크 생성)

  • Kim, Bo Geun;Li, Ki-Joune;Kang, Hae-Kyong
    • Spatial Information Research
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    • v.23 no.1
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    • pp.49-57
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    • 2015
  • Due to high density of population and progress of high building construction technologies, the number of high buildings has been increasing. Several information services have been provided to figure out complex indoor structures of building such as indoor navigations and indoor map services. The most fundamental information for these services are indoor network information. Indoor network in building provides topological connectivity between spaces unlike geometric information of buildings. In order to make indoor network information, we have to edit network manually or derive network properties based on the geometric data of buildings. This process is not easy for complex buildings. In this paper, we suggest a method to generate indoor network automatically based on crowdsourcing. From the collected individual trajectories, we derive indoor network information with crowdsourcing. We validate our method with a sample set of trajectory data and the result shows that our method is practical if the indoor positioning technology is reasonably accurate.

A Study on Improving Indoor Positioning Accuracy Using Map Matching Algorithm (맵 매칭 알고리즘을 이용한 실내 위치 추정 정확도 개선에 대한 연구)

  • Kwangjae Sung
    • Journal of the Semiconductor & Display Technology
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    • v.22 no.2
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    • pp.50-55
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    • 2023
  • Due to the unavailability of global positioning system (GPS) indoors, various indoor pedestrian positioning methods have been designed to estimate the position of the user using received signal strength (RSS) measurements from radio beacons, such as wireless fidelity (WiFi) access points and Bluetooth low energy (BLE) beacons. In indoor environments, radio-frequency (RF) signals are unpredictable and change over space and time because of multipath associated with reflection and refraction, shadow fading caused by obstacles, and interference among different devices using the same frequencies. Therefore, the outliers in the positional information obtained from the indoor positioning method based on RSS measurements occur often. For this reason, the performance of the positioning method can be degraded by the characteristics of the RF signal. To resolve this issue, a map-matching (MM) algorithm based on maximum probability (MP) estimation is applied to the indoor positioning method in this study. The MM algorithm locates the aberrant position of the user estimated by the positioning method within the limits of the adjacent pedestrian passages. Empirical experiments show that the positioning method can achieve higher positioning accuracy by leveraging the MM algorithm.

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A Comparison of Deep Learning Models for IQ Fingerprint Map Based Indoor Positioning in Ship Environments

  • Yootae Shin;Qianfeng Lin;Jooyoung Son
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.4
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    • pp.1122-1140
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    • 2024
  • The importance of indoor positioning has grown in numerous application areas such as emergency response, logistics, and industrial automation. In ships, indoor positioning is also needed to provide services to passengers on board. Due to the complex structure and dynamic nature of ship environments, conventional positioning techniques have limitations in providing accurate positions. Compared to other indoor positioning technologies, Bluetooth 5.1-based indoor positioning technology is highly suitable for ship environments. Bluetooth 5.1 attains centimeter-level positioning accuracy by collecting In-phase and Quadrature (IQ) samples from wireless signals. However, distorted IQ samples can lead to significant errors in the final estimated position. Therefore, we propose an indoor positioning method for ships that utilizes a Deep Neural Network (DNN) combined with IQ fingerprint maps to overcome the challenges associated with accurate location detection within the ship. The results indicate that the accuracy of our proposed method can reach up to 97.76%.

Location Tracking in Indoor Symbolic Space with RFID Sensors (RFID 센서를 이용한 실내 기호공간에서의 위치추적)

  • Kang, Hye-Young;Hwang, Jung-Rae;Li, Ki-Joune
    • Spatial Information Research
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    • v.19 no.3
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    • pp.53-62
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    • 2011
  • Spatial information services in indoor space are an im portant application area of GIS as in outdoor space. Unlike in outdoor space, a position in indoor space is specified by a symbolic code such as room number, rather than coordinate. Therefore tracking in indoor space is no longer a prediction of coordinates but a symbolic estimation on the current position of a moving object. In this paper, we propose a framework for tracking moving objects in indoor symbolic space with RFID sensors. First, we introduce the concepts of indoor symbolic space and tracking in indoor symbolic space, and define the accessibility graph for trackable indoor symbolic space. Second, we propose a deployment method of RFID readers and a construction algorithm of accessibility graph for trackable indoor symbolic space. Third, a tracking method is proposed for moving objects in symbolic indoor space with RFID sensors. Finally, we present an implementation exmaple and the result of experiment with real data to validate the proposed method.

Temporal Variation of Indoor Air Quality in Daycare Centers (어린이집에서 이산화탄소와 미세먼지의 장기간 시간적인 변이를 활용한 실내환경수준 평가)

  • Kim, Yoonjee;Lee, Sewon;Ban, Hyunkyung;Cha, Sangmin;Kim, Geunbae;Lee, Kiyoung
    • Journal of Environmental Health Sciences
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    • v.43 no.4
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    • pp.267-272
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    • 2017
  • Objectives: The purposes of the study were to analyze the temporal variation of carbon dioxide ($CO_2$) and particulate matter (PM) in daycare centers and evaluate the appropriateness of the official test method of one-time measurement. Methods: Indoor air quality in 46 daycare centers in the Seoul Metropolitan Area was measured as specified in the official test method of Indoor Air Quality Management law. In addition, indoor air quality in the 46 daycare centers was measured over 37 days using a real-time monitor (AirGuard K). Results: The daily means of $CO_2$ and PM in the 46 daycare centers were $1042.74{\pm}134.45ppm$ and $67.60{\pm}18.25{\mu}g/m^3$, respectively. Indoor air quality in the daycare centers showed significant temporal fluctuation. Measurements for single days were significantly different from the 37-day average exposure. Relative error of short term exposure decreased with an increase in the number of sampling days. The noncompliance rate for $CO_2$ using the official testing method was 2.17%, and none exceeded the $PM_{10}$ standard of $100{\mu}g/m^3$. With monitoring over 37 days, the daily noncompliance rate for $CO_2$ was 50.4% and the daily noncompliance rate for PM was 13.8%. Conclusions: When the official test method evaluates the indoor air at daycare centers one day per year, the results may not represent actual indoor air quality over a longer period of time. Real-time monitoring devices could be an alternative for managing indoor air quality.

BLE Signals-based Machine Learning for Determining Indoor Presence (BLE 신호 기반 기계학습을 이용한 재실 여부 결정 방법)

  • Kim, Seong-Chang;Kim, Jin-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.12
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    • pp.1855-1862
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    • 2022
  • Various indoor location-based services can be provided through indoor presence determination and indoor positioning technology using Beacon. However, since the BLE signal advertised by the beacon has an unstable RSSI due to problems such as multi-path fading, it is difficult to guarantee the accuracy of indoor presence determination. In this paper, data were collected while the classroom door was open to ensure accuracy in various situations. Based on the collected data, we propose an indoor presence determination method considering the characteristics of the signal. The proposed method uses support vector machine, showed about 10% accuracy improvement compared to the results using raw RSSI only. This method has the advantage of being able to accurately determine indoor presence with only one receiver. It is expected that the proposed method can implement a low-cost system for determining indoor presence with high accuracy.