• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.1-9
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• 2007

3D data are in great demand for pedestrian navigation recently. For pedestrian navigation, we needs to reconstruct 3D model in detail from people's eye. In order to present spatial features in detail for pedestrian navigation, it is indispensable to develop 3D model not only in outdoor environment but also in indoor environment such as underground shopping complex. However, it is very difficult to acquire 3D data efficiently by mobile mapping without GPS. In this research, 3D shape was acquired by Laser scanner, and texture by CCD(Charge Coupled Device) sensor. Continuous changes position and attitude of sensors were measured by IMU(Inertial Measurement Unit). Moreover, IMU was corrected by relative orientation of CCD images without GPS(Global Positioning System). In conclusion, Reliable, quick, and handy method for acquiring 3D data for indoor environment is proposed by a combination of a digital camera and a laser scanner with IMU.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.95-104
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• 2020

In this paper, we propose the real time indoor air quality monitoring and controlling platform on cloud using IoT sensor data such as PM10, PM2.5, CO2, VOCs, temperature, and humidity which has direct or indirect impact to indoor air quality. The system is connected to air ventilator to manage and optimize the indoor air quality. The proposed system has three main parts; First, IoT data collection service to measure, and collect indoor air quality in real time from IoT sensor network, Second, Big data processing pipeline to process and store the collected data on cloud platform and Finally, Big data analysis and visualization service to give real time insight of indoor air quality on mobile and web application. For the implication of the proposed system, IoT sensor kits are installed on three different public day care center where the indoor pollution can cause serious impact to the health and education of growing kids. Analyzed results are visualized on mobile and web application. The impact of ventilation system to indoor air quality is tested statistically and the result shows the proper optimization of indoor air quality.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1254-1257
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• 2017

LoRa는 저전력 및 장거리 작동을 위해 설계된 새로운 ISM 대역 무선 기술이며, LoRaWAN은 LoRa에서 정의된 광역 네트워크 프로토콜이다. 본 논문에서는 실제 환경에서 LoRaWAN 기술의 통신 성능을 검증하는 것을 목표로 한다. 이를 위해, 캠퍼스 내에 LoRaWAN 실험을 위한 실제 테스트 베드를 구축했다. 사용자들이 사용하는 실제 환경을 만들기 위해 통신 게이트웨이를 실내에 설치하였고, 캠퍼스의 실내외 다수 위치에서 데이터를 P2P 방식으로 게이트웨이에게 전송한다. 실험에서는 대역폭, 코딩 속도, 확산 계수 및 전송 전력을 변화시켰으며, 성능 검증을 위해 신호대잡음비와 패킷 전송률을 측정하여 결과를 분석한다.

• Journal of Digital Convergence
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• v.16 no.1
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• pp.147-152
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• 2018

Recently, as the demand for transmission of ultra-high quality media data such as UHD, AR, and VR increases, various technologies for this have been actively developed and IEEE 802.11ad standard have been commercialized. In this paper, a test bed is constructed to analyze the indoor wireless environment using the IEEE 802.11ad standard based on mmWave, and the experimental results of various indoor wireless environments are introduced and analyzed. We compared the data from the module by data transmission, such as signal to noise ratio(SNR) and throughput. And we measured the beam pattern and width of the module and compared the effects on the indoor environment of the corridor and the office. This shows that the signal reflection of the wall shows higher SNR values and is more suitable to use for indoor than outdoor. It is confirmed that the loss when not in line of sight(LoS) is not enough to compensate the wall reflected signal. As a result, it is judged to be suitable for the indoor use of the mmWave LAN and can be usefully used for further experiments.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.1-10
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• 2024

The radio propagation characteristics of the 6, 10, and 17 GHz frequency bands in multiple paths in an indoor lobby environment were analyzed. The line-of-sight (LOS) and non-LOS (NLOS) paths were measured from a distance of 2-16 m (0.5 m intervals) from the transmitting to the receiving antenna positions. For basic transmission losses, three parameters were compared using the floating intercept path loss model corresponding to the path. For a root mean square delay spread, the measurement results were compared for cumulative probabilities of 10, 50, and 90%. Propagation loss and propagation delay occurred in all measured frequencies owing to the existence of pillars and an unusual lobby structure. Thus, a measurement scenario for an indoor lobby environment and the provision of standard measurement data was proposed. The results may facilitate research on the radio propagation characteristics of 5G and millimeter-wave bands in indoor lobby environments with various structures.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.459-461
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• 2022

In this paper, we propose a measurement system for measuring radioactivity detected in an indoor environment. This is to measure and prevent radiation generated in various spaces such as general house, workplace, and research institutes. Multi-radioactivity sensors are used to measure multiple spaces simultaneously. The measured radioactivity data is transmitted to the PC in real time through ZigBee and monitored. Even with a small amount of radioactivity, it is considered that it must be installed in a place where radiation exposure is expected, such as a laboratory or workplace, for prevention from chronic radiation syndrome.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• 한국정보교육학회:학술대회논문집
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• 2007.01a
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• pp.267-273
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• 2007

초등학교는 교실에서 생활하는 학생 수가 다른 건물에 비해 매우 많은 편이나 이를 관리할만한 적당한 환기 시스템도 갖추고 있지 못하다. 실내 환경 상태가 건강과 직결되면서 사회적 관심을 불러일으키고 있으나 그 환경에 노출된 학생들은 스스로 위해 요인을 인지하고 회피할 수 있도록 하는 환경 개선교육을 경험하지 못하고 있는 실정이다. 실제 측정된 데이터와 자료를 분석하여 일상생활에 관련된 주변 환경의 유해성 정보 및 어린이 건강호보를 위한 교육이 활발히 이루어진다면 실내 환경의 중요성 인식과 어린이 건강을 위한 환경 조성에 기여할 것이다. 이를 위해 본 연구에서는 관련 자료를 정리 분석하고 실제적인 실내 환경 교육 시스템을 설계 개발하여 수업현장에 적용해보고자 한다.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.532-533
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• 2008

본 논문에서는 하루에 수백만 명이 이용하는 지하철 역사내의 환경 관리를 유비쿼터스(Ubiquitous) 기술을 적용하여 실질적이고 효과적으로 실행하는 방안을 제안하고자 한다. 지하철 역사는 지하라는 특수한 환경이기 때문에 외부의 신선한 공기를 유입하여 역사내의 공기질을 쾌적하게 유지해야할 필요가 있다. 또한 실내 공기질을 오염시키는 환경가스나 미세먼지 등의 오염도에 대해서도 지속적으로 감시하여야 한다. 이를 위해 설치가 간편하고 소형의 측정 장치를 지하역사내의 주요 지점에 설치하여 오염물질을 측정하고 그 결과 데이터를 모으는 집중기(Collector)를 운영하여 최종적으로 측정 데이터를 중앙 서버까지 전송할 수 있다면 지하철 관리자에 의한 지하역사내의 오염물질을 효과적으로 관리 감독하는 종합적인 지하철 환경 관리시스템의 운영이 가능할 것으로 판단된다.

• Korean Journal of Construction Engineering and Management
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• v.22 no.3
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• pp.40-51
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• 2021

MLS (Mobile Laser Scanning) which is a scanning method done by moving the LiDAR (Light Detection and Ranging) is widely employed to capture indoor PCD (Point Cloud Data) for floor plan generation in the AEC (Architecture, Engineering, and Construction) industry. The movement and rotation of LiDAR in the scanning phase cause deformation (i.e. skew) of PCD and impose a significant impact on quality of output. Thus, a de-skewing method is required to increase the accuracy of geometric representation. De-skewing methods which use position and pose information of LiDAR collected by IMU (Inertial Measurement Unit) have been mainly developed to refine the PCD. However, the existing methods have limitations on de-skewing PCD without IMU. In this study, a novel algorithm for de-skewing 2D PCD captured from MLS without IMU is presented. The algorithm de-skews PCD using scan matching between points captured from adjacent scan positions. Based on the comparison of the deskewed floor plan with the benchmark derived from TLS (Terrestrial Laser Scanning), the performance of proposed algorithm is verified by reducing the average mismatched area 49.82%. The result of this study shows that the accurate floor plan is generated by the de-skewing algorithm without IMU.