• Title/Summary/Keyword: Sensor 3D data model

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An Open Standard-based Terrain Tile Production Chain for Geo-referenced Simulation

  • Yoo, Byoung-Hyun
    • Korean Journal of Remote Sensing
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    • v.24 no.5
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    • pp.497-506
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    • 2008
  • The needs for digital models of real environment such as 3D terrain or cyber city model are increasing. Most of applications related with modeling and simulation require virtual environment constructed from geospatial information of real world in order to guarantee reliability and accuracy of the simulation. The most fundamental data for building virtual environment, terrain elevation and orthogonal imagery is acquired from optical sensor of satellite or airplane. Providing interoperable and reusable digital model is important to promote practical application of high-resolution satellite imagery. This paper presents the new research regarding representation of geospatial information, especially for 3D shape and appearance of virtual terrain. and describe framework for constructing real-time 3D model of large terrain based on high-resolution satellite imagery. It provides infrastructure of 3D simulation with geographical context. Web architecture, XML language and open protocols to build a standard based 3D terrain are presented. Details of standard-based approach for providing infrastructure of real-time 3D simulation using high-resolution satellite imagery are also presented. This work would facilitate interchange and interoperability across diverse systems and be usable by governments, industry scientists and general public.

The collecting of 3dimensional data from the way of pulse generating at the M/C (펄스지령법에 의한 머시닝센터상의 3차원 형상정보 수집)

  • 강효석;임한석;김선호;안중환
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.04b
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    • pp.396-399
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    • 1995
  • In this study, Acquisition system is proposed to acquire 3 dimensional data of the free surface model using direct pulse control to machining center. Todo this, I/F to connect between manual operating handle and computer is made, and 3 dimensional shape measuring algorithm using Z-map is applied. The 3 dimensional shape data of the free surface model measured by laser displacement sensor and electric touch probe are achieved directly. Performance of the proposed system is evaluated through measurement of various shape model.

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Geometric Modeling and Data Simulation of an Airborne LIDAR System (항공라이다시스템의 기하모델링 및 데이터 시뮬레이션)

  • Kim, Seong-Joon;Min, Seong-Hong;Lee, Im-Pyeong;Choi, Kyung-Ah
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.3
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    • pp.311-320
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    • 2008
  • A LIDAR can rapidly generate 3D points by densely sampling the surfaces of targets using laser pulses, which has been efficiently utilized to reconstruct 3D models of the targets automatically. Due to this advantage, LIDARs are increasingly applied to the fields of Defense and Security, for examples, being employed to intelligently guided missiles and manned/unmanned reconnaissance planes. For the prior verification of the LIDAR applicability, this study aims at generating simulated LIDAR data. Here, we derived the sensor equation by modelling the geometric relationships between the LIDAR sub-modules, such as GPS, IMU, LS and the systematic errors associated with them. Based on this equation, we developed a program to generate simulated data with the system parameters, the systematic errors, the flight trajectories and attitudes, and the reference terrain model given. This program had been applied to generating simulated LIDAR data for urban areas. By analyzing these simulated data, we verified the accuracy and usefulness of the simulation. The simulator developed in this study will provide economically various test data required for the development of application algorithms and contribute to the optimal establishment of the flight and system parameters.

Development of Gas Type Identification Deep-learning Model through Multimodal Method (멀티모달 방식을 통한 가스 종류 인식 딥러닝 모델 개발)

  • Seo Hee Ahn;Gyeong Yeong Kim;Dong Ju Kim
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.12
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    • pp.525-534
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    • 2023
  • Gas leak detection system is a key to minimize the loss of life due to the explosiveness and toxicity of gas. Most of the leak detection systems detect by gas sensors or thermal imaging cameras. To improve the performance of gas leak detection system using single-modal methods, the paper propose multimodal approach to gas sensor data and thermal camera data in developing a gas type identification model. MultimodalGasData, a multimodal open-dataset, is used to compare the performance of the four models developed through multimodal approach to gas sensors and thermal cameras with existing models. As a result, 1D CNN and GasNet models show the highest performance of 96.3% and 96.4%. The performance of the combined early fusion model of 1D CNN and GasNet reached 99.3%, 3.3% higher than the existing model. We hoped that further damage caused by gas leaks can be minimized through the gas leak detection system proposed in the study.

Inter-clustering Cooperative Relay Selection Schemes for 5G Device-to-device Communication Networks

  • Nasaruddin, Nasaruddin;Yunida, Yunida;Adriman, Ramzi
    • Journal of information and communication convergence engineering
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    • v.20 no.3
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    • pp.143-152
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    • 2022
  • The ongoing adoption of 5G will increase the data traffic, throughput, multimedia services, and power consumption for future wireless applications and services, including sensor and mobile networks. Multipath fading on wireless channels also reduces the system performance and increases energy consumption. To address these issues, device-to-device (D2D) and cooperative communications have been proposed. In this study, we propose two inter-clustering models using the relay selection method to improve system performance and increase energy efficiency in cooperative D2D networks. We develop two inter-clustering models and present their respective algorithms. Subsequently, we run a computer simulation to evaluate each model's outage probability (OP) performance, throughput, and energy efficiency. The simulation results show that inter-clustering model II has the lowest OP, highest throughput, and highest energy efficiency compared with inter-clustering model I and the conventional inter-clustering-based multirelay method. These results demonstrate that inter-clustering model II is well-suited for use in 5G overlay D2D and cellular communications.

Toward Accurate Road Detection in Challenging Environments Using 3D Point Clouds

  • Byun, Jaemin;Seo, Beom-Su;Lee, Jihong
    • ETRI Journal
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    • v.37 no.3
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    • pp.606-616
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    • 2015
  • In this paper, we propose a novel method for road recognition using 3D point clouds based on a Markov random field (MRF) framework in unstructured and complex road environments. The proposed method is focused on finding a solution for an analysis of traversable regions in challenging environments without considering an assumption that has been applied in many past studies; that is, that the surface of a road is ideally flat. The main contributions of this research are as follows: (a) guidelines for the best selection of the gradient value, the average height, the normal vectors, and the intensity value and (b) how to mathematically transform a road recognition problem into a classification problem that is based on MRF modeling in spatial and visual contexts. In our experiments, we used numerous scans acquired by an HDL-64E sensor mounted on an experimental vehicle. The results show that the proposed method is more robust and reliable than a conventional approach based on a quantity evaluation with ground truth data for a variety of challenging environments.

Emotion Recognition using Short-Term Multi-Physiological Signals

  • Kang, Tae-Koo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.3
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    • pp.1076-1094
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    • 2022
  • Technology for emotion recognition is an essential part of human personality analysis. To define human personality characteristics, the existing method used the survey method. However, there are many cases where communication cannot make without considering emotions. Hence, emotional recognition technology is an essential element for communication but has also been adopted in many other fields. A person's emotions are revealed in various ways, typically including facial, speech, and biometric responses. Therefore, various methods can recognize emotions, e.g., images, voice signals, and physiological signals. Physiological signals are measured with biological sensors and analyzed to identify emotions. This study employed two sensor types. First, the existing method, the binary arousal-valence method, was subdivided into four levels to classify emotions in more detail. Then, based on the current techniques classified as High/Low, the model was further subdivided into multi-levels. Finally, signal characteristics were extracted using a 1-D Convolution Neural Network (CNN) and classified sixteen feelings. Although CNN was used to learn images in 2D, sensor data in 1D was used as the input in this paper. Finally, the proposed emotional recognition system was evaluated by measuring actual sensors.

SHM benchmark for high-rise structures: a reduced-order finite element model and field measurement data

  • Ni, Y.Q.;Xia, Y.;Lin, W.;Chen, W.H.;Ko, J.M.
    • Smart Structures and Systems
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    • v.10 no.4_5
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    • pp.411-426
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    • 2012
  • The Canton Tower (formerly named Guangzhou New TV Tower) of 610 m high has been instrumented with a long-term structural health monitoring (SHM) system consisting of over 700 sensors of sixteen types. Under the auspices of the Asian-Pacific Network of Centers for Research in Smart Structures Technology (ANCRiSST), an SHM benchmark problem for high-rise structures has been developed by taking the instrumented Canton Tower as a host structure. This benchmark problem aims to provide an international platform for direct comparison of various SHM-related methodologies and algorithms with the use of real-world monitoring data from a large-scale structure, and to narrow the gap that currently exists between the research and the practice of SHM. This paper first briefs the SHM system deployed on the Canton Tower, and the development of an elaborate three-dimensional (3D) full-scale finite element model (FEM) and the validation of the model using the measured modal data of the structure. In succession comes the formulation of an equivalent reduced-order FEM which is developed specifically for the benchmark study. The reduced-order FEM, which comprises 37 beam elements and a total of 185 degrees-of-freedom (DOFs), has been elaborately tuned to coincide well with the full-scale FEM in terms of both modal frequencies and mode shapes. The field measurement data (including those obtained from 20 accelerometers, one anemometer and one temperature sensor) from the Canton Tower, which are available for the benchmark study, are subsequently presented together with a description of the sensor deployment locations and the sensor specifications.

User Authentication Using Accelerometer Sensor in Wrist-Type Wearable Device (손목 착용형 웨어러블 기기의 가속도 센서를 사용한 사용자 인증)

  • Kim, Yong Kwang;Moon, Jong Sub
    • KIPS Transactions on Computer and Communication Systems
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    • v.6 no.2
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    • pp.67-74
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    • 2017
  • This paper proposes a method of user authentication through the patterns of arm movement with a wrist-type wearable device. Using the accelerometer sensor which is built in the device, the 3-axis accelerometer data are collected. Then, the collected data are integrated and the periodic cycle are extracted. In the cycle, the features of frequency are generated with the accelerometer. With the frequency features, 2D Gaussian mixture are modelled. For authenticating an user, the data(the accelerometer) of the user at some point are tested with confidence interval of the Gaussian distribution. The model showed a valuable results for the user authentication with an example, which is average 92% accuracy with 95% confidence interval.

Virtual Target Overlay Technique by Matching 3D Satellite Image and Sensor Image (3차원 위성영상과 센서영상의 정합에 의한 가상표적 Overlay 기법)

  • Cha, Jeong-Hee;Jang, Hyo-Jong;Park, Yong-Woon;Kim, Gye-Young;Choi, Hyung-Il
    • The KIPS Transactions:PartD
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    • v.11D no.6
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    • pp.1259-1268
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    • 2004
  • To organize training in limited training area for an actuai combat, realistic training simulation plugged in by various battle conditions is essential. In this paper, we propose a virtual target overlay technique which does not use a virtual image, but Projects a virtual target on ground-based CCD image by appointed scenario for a realistic training simulation. In the proposed method, we create a realistic 3D model (for an instructor) by using high resolution Geographic Tag Image File Format(GeoTIFF) satellite image and Digital Terrain Elevation Data (DTED), and extract the road area from a given CCD image (for both an instructor and a trainee). Satellite images and ground-based sensor images have many differences in observation position, resolution, and scale, thus yielding many difficulties in feature-based matching. Hence, we propose a moving synchronization technique that projects the target on the sensor image according to the marked moving path on 3D satellite image by applying Thin-Plate Spline(TPS) interpolation function, which is an image warping function, on the two given sets of corresponding control point pair. To show the experimental result of the proposed method, we employed two Pentium4 1.8MHz personal computer systems equipped with 512MBs of RAM, and the satellite and sensor images of Daejoen area are also been utilized. The experimental result revealed the effective-ness of proposed algorithm.