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Author: search.filters.author.Murata, Ken T.

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    Automatic Smoke/Forest Fire Detecting System based on Visual IoT
    (2025-01-01)
    Tungpimolrut, Kanokvate
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    Karnjana, Jessada
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    Chatpoj, Montri
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    Kitbutrawat, Nathavuth
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    Pavarangkoon, Praphan
    In this paper, a visual IoT system or IP camera system for early detection of smoke/forest fire has been investigated. The overall system implementation including hardware and software as well as system installation in targeted areas in Chiangmai, Thailand have been also described. The dataset construction, the preliminary model development and testing have been conducted based on YOLOv5. The model improvement based on Fast Segment Anything Model with YOLOv11 has been proposed to improve False Positive. The results show good performance of Mean Square Error.
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    International Deployment of Visual IoT for Disaster Mitigation
    (2023-01-01)
    Murata, Ken T.
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    Kikuta, Kazutaka
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    Nagatsuma, Tsutomu
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    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.
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    Kikuta, Kazutaka
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    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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    Performance Evaluation of High-Performance and Flexible Protocol on Data Mover Challenge
    (2020-10-21)
    Pavarangkoon, Praphan
    ;
    Murata, Ken T.
    ;
    Yamamoto, Kazunori
    ;
    Fujita, Naoyuki
    ;
    Ohkawa, Hirofumi
    Data mover challenge (DMC) for Supercomputing Asia organized by the National Supercomputing Centre (NSCC), Singapore is a competition for data transfer node (DTN) architecture. This challenge invites experts from academia and industry to test their software and products on advanced 100G research and education networks. The theme for DMC20 is data for science, which focuses on moving the large amounts of data between multiple sites with DTNs and between high performance computing (HPC) centers around the world. In this paper, we present performance evaluation of data transfer protocol, called high-performance and flexible protocol (HpFP), on DMC20. The data transfer tests are done using high-performance copy (HCP), which is an enhanced HpFP-based file transfer tool. The results show that the HpFP outperforms the traditional protocol on scenario with high packet loss. Tuning parameters and problems are discussed to improve the performance of our file transfer tool as well.