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Author: search.filters.author.Nagatsuma, TsutomuHas files: No

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    International Deployment of Visual IoT for Disaster Mitigation
    (2023-01-01)
    Murata, Ken T.
    ;
    Kikuta, Kazutaka
    ;
    Nagatsuma, Tsutomu
    ;
    Imanaka, Hideo
    ;
    Pavarangkoon, Praphan
    This paper proposes a novel methodology that utilizes a newly developed visual Internet of Things (IoT) system for resilient natural disaster mitigation. This system enables the detection of disasters through remote control functions integrated with visual IoT sensors and artificial intelligence (AI)-based image processing of images captured by these sensors. The system is designed using commercial off-the-shelf (COTS) components to reduce installation costs, making it feasible for deployment worldwide, including in developing countries. In 2023, the proposal for this system was presented to the ITUD with the aim of widespread implementation in developing nations. The paper introduces innovative methodologies for visual IoT in international disaster mitigation, accompanied by use cases and detailed technological insights.
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    An Image Stabilization Technique for Long-durational Outdoor Footages Obtained by Visual IoT Systems
    (2021-01-01)
    Murakami, Yuki
    ;
    Murata, Ken T.
    ;
    Kikuta, Kazutaka
    ;
    Niimi, Michiharu
    ;
    Kawanabe, Tomohiro
    Disaster mitigation is a significant issue where modern wireless network systems are expected to play a crucial role. It is believed that Visual IoT is one of the key techniques because of its monitoring abilities of urban and rural areas. The outdoor Visual IoT systems generally transfer a large number of footage every day. To detect information from large-size footage datasets, automatic time subtractions between frames are effective. However, to extract even tiny difference between frames, camera shake causes a serious damage. In this study we first survey long-durational footage transmitted from outdoor cameras installed in a city to examine that the stabilization techniques based on feature keypoints are effective to camera shake. Based on this survey we define a matching index to judge if the stabilization is of use or not for every couple of frames. The index is implemented with help of a camera calibration library in OpenCV using AKAZE feature. We then propose a method to stabilize footage continuously obtained by outdoor Visual IoT systems. Using the matching index, we examine one-day footage to find that stabilization is occasionally not applicable in case when the matching index is relatively larger or smaller than 1 (when matching is complete) or the number of matching pairs using AKAZE keypoints are too few. According to the results we set a threshold value of the matching index. We finally perform this technique to footage recorded on a couple of strongly windy days. The efficiency is numerically and visually confirmed on each footage successfully.
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    The variation of critical frequency of E layer over Chumphon, Thailand
    (2013-12-09)
    Wongcharoen, Poramintra
    ;
    Kenpankho, Prasert
    ;
    Sepsirisuk, Kasemsuk
    ;
    Supnithi, Pornchai
    ;
    Noppanakeepong, Suthichai
    In this research paper presents the observed critical frequency of E layer (foE) over Chumphon, Thailand which is located at nearly the magnetic equator (lat. 10.72° long. 99.37° dip. 3°) during September 2004 to August 2005. The foE is one of essential parameters in the International Reference Ionsphere (IRI) model. We investigate the variation of the observed foE by comparing to the Sun spot number, ionospheric index, and 10.7 cm. flux. Due to essentially of accurate IRI model can be used to applied in communication such as it may be implied tendency of phenomena in E layer effect on high frequency communication over Chumphon, Thailand. © 2013 IEEE.
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    The variation of equatorial spread-F occurrences observed by ionosondes at Thailand longitude sector
    (2013-11-15)
    Rungraengwajiake, Sarawoot
    ;
    Supnithi, Pornchai
    ;
    Tsugawa, Takuya
    ;
    Maruyama, Takashi
    ;
    Nagatsuma, Tsutomu
    The equatorial spread-F (ESF) is a phenomenon of ionopheric irregularities which are mainly generated by the generalized Rayleigh-Taylor (R-T) instability mechanism in conjunction with the other physical mechanisms, originated at the bottom side of the F-layer in the equatorial region after sunset. It degrades the quality of signals that propagate through these irregularities, especially in the navigation satellite system, which requires the high integrity signals. In this work, we analyze the ESF statistics obtained from the FM/CW ionosonde stations over Thailand longitude sector. One is at Chumphon (10.72 N, 99.37 E, dip latitude 3.0), located near the geomagnetic equator, and the other station is located at Chiangmai (18.76 N, 98.93 E, dip latitude 12.7). Both stations are as part of the South-East Asia Low Latitude Ionospheric Network (SEALION) project. The ionograms are obtained at every 15 min from September 2004 to August 2005, which has the monthly mean of solar 10.7 cm flux (F10.7) from ∼80 to ∼110. In addition, we compare the diurnal patterns between the ESF occurrences and the variation of virtual height of the F-layer bottom side (h'F) of these two stations. The results show that the ESF occurrences at Chumphon stations are higher than Chiangmai station in all seasons. The high ESF occurrences of both stations mostly occur in equinoctial months corresponded with the rapid rising of the monthly mean h'F in the post-sunset. However, some inconsistent results are still observed, implying the role of other factors such as gravity waves and planetary waves to ESF occurrences. © 2012 COSPAR. Published by Elsevier Ltd. All rights reserved.
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    TEC prediction with neural network for equatorial latitude station in Thailand
    (2012-01-01)
    Watthanasangmechai, Kornyanat
    ;
    Supnithi, Pornchai
    ;
    Lerkvaranyu, Somkiat
    ;
    Tsugawa, Takuya
    ;
    Nagatsuma, Tsutomu
    This paper describes the neural network (NN) application for the prediction of the total electron content (TEC) over Chumphon, an equatorial latitude station in Thailand. The studied period is based on the available data during the low-solar-activity period from 2005 to 2009. The single hidden layer feed-forward network with a back propagation algorithm is applied in this work. The input space of the NN includes the day number, hour number and sunspot number. An analysis was made by comparing the TEC from the neural network prediction (NN TEC), the TEC from an observation (GPS TEC) and the TEC from the IRI-2007 model (IRI-2007 TEC). To obtain the optimum NN for the TEC prediction, the root-mean-square error (RMSE) is taken into account. In order to measure the effectiveness of the NN, the normalized RMSE of the NN TEC computed from the difference between the NN TEC and the GPS TEC is investigated. The RMSE, and normalized RMSE, comparisons for both the NN model and the IRI-2007 model are described. Even with the constraint of a limited amount of available data, the results show that the proposed NN can predict the GPS TEC quite well over the equatorial latitude station. Copyright © The Society of Geomagnetism and Earth, Planetary and Space Sciences (SGEPSS).