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Intelligent SLAM Algorithm Fusing Low-Cost Sensors at Risk of Building Collapses

Computers, Materials & Continua 2023年第1期74卷 1657-1671页

作者： dahyeon kim Junho Ahn Computer Information Technology Korea National University of TransportationChungju27469Korea

When firefighters search inside a building that is at risk of collapse due to abandonment or disasters such as fire,they use old architectural drawings or a simple monitoring method involving a video device attached to a ***,using these methods,the disaster situation inside a building at risk of collapse is difficult to detect and ***,we investigate the generation of digital maps for a disaster site to accurately analyze internal *** this study,a robot combined with a low-cost camera and twodimensional light detection and ranging(2D-lidar)traverses across a floor to estimate the location of obstacles while drawing an internal map of the *** propose an algorithm that detects the floor and then determines the possibility of entry,tracks collapses,and detects obstacles by analyzing patterns on the *** robot’s location is estimated,and a digital map is created based on Hector simultaneous localization and mapping(SLAM).Subsequently,the positions of obstacles are estimated based on the range values detected by 2D-lidar,and the position of the obstacles are identified on the map using the map update method in semantic *** equipment are implemented using low-specification devices,and the experiments are conducted using a low-cost robot that affords near-real-time *** experiments are conducted in various actual internal environments of *** terms of obstacle detection performance,almost all obstacles are detected,and their positions identified on the map with a high accuracy of 89%.

关键词： Intelligence SLAM vision 2D-lidar low-cost algorithm

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Vision-based Recognition Algorithm for Up-To-Date Indoor Digital Map Generations at Damaged Buildings

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Computers, Materials & Continua 2022年第8期72卷 2765-2781页

作者： dahyeon kim Chulsu kim Junho Ahn Computer Information Technology Korea National University of TransportationChungju27469Korea Department of Railway Vehicle System Engineering Korea National University of TransportationUiwang16106Korea

When firefighters are engaged in search and rescue missions inside a building at a risk of collapse,they have difficulty in field command and rescue because they can only simplymonitor the situation inside the building utilizing old building drawings or *** propose an efficient solution for fast search and rescue work of firefighters,this study investigates the generation of up-to-date digital maps for disaster sites by tracking the collapse situation,and identifying the information of obstacles which are risk factors,using an artificial intelligence algorithm based on low-cost *** research separates the floor by using the mask regional convolutional neural network(R-CNN)algorithm,and determines whether the passage is collapsed or ***,in the case of a passage that can be searched,the floor pattern of the obstacles that exist on the floor that has not collapsed is analyzed,and obstacles are searched utilizing an image processing ***,we can detect various unknown as well as known ***,the locations of obstacles can be estimated using the pixel values up to the bounding box of an existing detected *** conduct experiments using the public datasets collected by Carnegie Mellon university(CMU)and data collected by manipulating a low-cost robot equipped with a smartphone while roaming five buildings in a *** collected data have various floor patterns for objectivity and obstacles that are different from one *** on these data,the algorithm for detecting unknown obstacles of a verified study and estimating their sizes had an accuracy of 93%,and the algorithm for estimating the distance to obstacles had an error rate of *** this process,we tracked collapsed passages and composed up-to-date digital maps for disaster sites that include the information of obstacles that interfere with the search and rescue work.

关键词： Vision artificial intelligence robot map generation damaged building

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Systematic Security Guideline Framework through Intelligently Automated Vulnerability Analysis

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Computers, Materials & Continua 2024年第3期78卷 3867-3889页

作者： dahyeon kim Namgi kim Junho Ahn Computer Information Technology Korea National University of TransportationChungju27469Korea Department of AI Computer Science and Engineering Kyonggi UniversitySuwon16227Korea

This research aims to propose a practical framework designed for the automatic analysis of a product’s comprehensive functionality and security vulnerabilities,generating applicable guidelines based on real-world *** existing analysis of software security vulnerabilities often focuses on specific features or *** partial and arbitrary analysis of the security vulnerabilities makes it challenging to comprehend the overall security vulnerabilities of the *** key novelty lies in overcoming the constraints of partial *** proposed framework utilizes data from various sources to create a comprehensive functionality profile,facilitating the derivation of real-world security *** guidelines are dynamically generated by associating functional security vulnerabilities with the latest Common Vulnerabilities and Exposure(CVE)and Common Vulnerability Scoring System(CVSS)scores,resulting in automated guidelines tailored to each *** guidelines are not only practical but also applicable in real-world software,allowing for prioritized security *** proposed framework is applied to virtual private network(VPN)software,wherein a validated Level 2 data flow diagram is generated using the Spoofing,Tampering,Repudiation,Information Disclosure,Denial of Service,and Elevation of privilege(STRIDE)technique with references to various papers and examples from related *** analysis resulted in the identification of a total of 121 *** successful implementation and validation demonstrate the framework’s efficacy in generating customized guidelines for entire systems,subsystems,and selected modules.

关键词： Framework automation vulnerability analysis security guidelines

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Intelligent Risk-Identification Algorithm with Vision and 3D LiDAR Patterns at Damaged Buildings

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Intelligent Automation & Soft Computing 2023年第5期36卷 2315-2331页

作者： dahyeon kim Jiyoung Min Yongwoo Song Chulsu kim Junho Ahn Computer Information Technology Korea National University of TransportationChungju27469Korea Department of Railway Vehicle System Engineering Korea National University of TransportationUiwang16106Korea

Existingﬁreﬁghting robots are focused on simple storage orﬁre sup-pression outside buildings rather than detection or *** a large number of robots using expensive equipment is *** study aims to increase the efﬁciency of search and rescue operations and the safety ofﬁreﬁgh-ters by detecting and identifying the disaster site by recognizing collapsed areas,obstacles,and rescuers on-site.A fusion algorithm combining a camera and three-dimension light detection and ranging(3D LiDAR)is proposed to detect and loca-lize the interiors of disaster *** algorithm detects obstacles by analyzingﬂoor segmentation and edge patterns using a mask regional convolutional neural network(mask R-CNN)features model based on the visual data collected from a parallelly connected camera and 3D *** as objects are detected using you only look once version 4(YOLOv4)in the image data to localize persons requiring *** point cloud data based on 3D LiDAR cluster the objects using the density-based spatial clustering of applications with noise(DBSCAN)clustering algorithm and estimate the distance to the actual object using the center point of the clustering *** proposed artiﬁcial intelligence(AI)algorithm was veriﬁed based on individual sensors using a sensor-mounted robot in an actual building to detectﬂoor surfaces,atypical obstacles,and persons requiring ***,the fused AI algorithm was comparatively veriﬁed.

关键词： Three-dimension light detection and ranging vision risk identiﬁcation damaged building robot

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