• Journal of Sensor Science and Technology
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• v.22 no.5
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• pp.364-368
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• 2013

Vibrational energy harvester based on piezoelectricity has been expected to be the dominant energy harvesting technology due to the advantages of high conversion efficiency, light weight and small size, night operation, etc. Its commercialization is just around the corner but the integration with power management electronics should be solved in advance. In this paper, therefore, fully-integrated design environment for piezoelectric energy harvesting systems is presented to assist co-design with the power management electronics. The proposed design environment is capable of analyzing the energy harvester including the package-induced damping effects and simulating the device and its power management electronics simultaneously. When the developed design environment was applied to the fabricated device, the simulated resonant frequency matched well with the experimental result with a difference of 2.97% only. Also, the complex transient response was completed in short simulation time of 3,001 seconds including the displacement distribution over the device geometry. Furthermore, a full-bridge power management circuit was modeled and simulated with the energy harvester simultaneously. Therefore the proposed, fully-integrated design environment is accurate and fast enough for the contribution on successful commercialization of piezoelectric energy harvester.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.59-67
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• 2005

Building information is primary source in many applications such as mapping, telecommunication, car navigation and virtual city modeling. While aerial CCD images which are captured by passive sensor(digital camera) provide horizontal positioning in high accuracy, it is far difficult to process them in automatic fashion due to their inherent properties such as perspective projection and occlusion. On the other hand, LIDAR system offers 3D information about each surface rapidly and accurately in the form of irregularly distributed point clouds. Contrary to the optical images, it is much difficult to obtain semantic information such as building boundary and object segmentation. Photogrammetry and LIDAR have their own major advantages and drawbacks for reconstructing earth surfaces. The purpose of this investigation is to automatically obtain spatial information of 3D buildings by fusing LIDAR data with aerial CCD image. The experimental results show that most of the complex buildings are efficiently extracted by the proposed method and signalize that fusing LIDAR data and aerial CCD image improves feasibility of the automatic detection and extraction of buildings in automatic fashion.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.3
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• pp.219-229
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• 2018

This paper proposes Kalman Filter-based relative navigation algorithms for proximity tasks such as rendezvous/docking/cluster-operation of spacecraft using PSD Sensors and Infrared Beacon Modules. Numerical simulations are performed for comparative analysis of the performance of each relative-navigation technique. Based on the operation principle and optical modeling of the PSD Sensor and the Infrared Beacon Module used in the relative navigation algorithm, a measurement model for the Kalman filter is constructed. The Extended Kalman Filter(EKF) and the Unscented Kalman Filter(UKF) are used as probabilistic relative navigation based on measurement fusion to utilize kinematics and dynamics information on translational and rotation motions of satellites. Relative position and relative attitude estimation performance of two filters is compared. Especially, through the simulation of various scenarios, performance changes are also investigated depending on the number of PSD Sensors and IR Beacons in target and chaser satellites.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.74-82
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• 2019

The revolution of industry 4.0 is enabling us to build an intelligent connection society called smart cities. The use of renewable energy in particular solar energy is extremely important for modern society due to the growing power demand in smart cities, but its difficult to monitor and manage in each buildings since need to be deploy low energy sensors and information need to be transfer via wireless sensor network (WSN). The Internet of Things (IoT) / low-power wide-area (LPWA) is an emerging WSN technology, to collect and monitor data about environmental and physical electrical / electronics devices conditions in real time. However, providing power to IoT sensor end devices and other public electrical loads such as street lights, etc is an important challenging role because the sensor are usually battery powered and have a limited life time. In this paper, we proposes an efficient solar energy-based power management scheme for smart city based on IoT technology using LoRa wide-area network (LoRaWAN). This approach facilitates to maintain and prevent errors of solar panel based energy systems. The proposed solution maximizing output the power generated from solar panels system to distribute the power to the load and the grid. In this paper, we proved the efficiency of the proposed system with Simulink based system modeling and real-time emulation.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.915-922
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• 2006

Recently, the requirements of the embedded software are getting diverse as the diversity of embedded software application fields increases. The systematic development methods are issued to deal with the dependency between hardware and software. However, the existing development methods have not considered the software's close connection to hardware and the high-level reusability for common requirements of several similar domains. In this paper, we propose a design method of development process model of product lines to support an efficient development method for embedded software. For this, we firstly suggest a domain scoping method and an IDEF0(Integration DEFinition)-based business model for extracting the efficient requirements. Next, we present a component deriving method based on the service architecture and an architecture design method after considering the hardware dependency. And we explain the artifacts of MSDFS(Multi Sensor Data Fusion System) at each design step in order to show how the proposed model can be applied to the embedded software development.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.727-736
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• 2019

In this paper, we present how to create a point cloud for a target area using multiple unmanned aerial vehicle images and to remove the gaps and overlapping points between datasets. For this purpose, first, IBA (Incremental Bundle Adjustment) technique was applied to correct the position and attitude of UAV platform. We generate a point cloud by using MDR (Multi-Dimensional Relaxation) matching technique. Next, we register point clouds based on observation vectors between stereo images by doing this we remove gaps between point clouds which are generated from different stereo pairs. Finally, we applied an occupancy grids based integration algorithm to remove duplicated points to create an integrated point cloud. The experiments were performed using UAV images, and our experiments show that it is possible to remove gaps and duplicate points between point clouds generated from different stereo pairs.