Life Search - A Smartphone Application for Disaster Education and Rescue

Takagi, Y.; Yamada, Kyosuke; Goto, A; Yamada, Masashi; Naka, Takatoshi; Miyazaki, Shuichi

doi:10.1109/nicoint.2017.34

Cited by 3 publications

(2 citation statements)

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“…This part refers to certain papers investigating the existing search-rescue technologies for outdoor injured human target, and discussing the pros and cons. For the above-mentioned severe mountain-forest outdoor environment, the conventional constrained method of pre-wearing auxiliary positioning device is not an ideal choice (like the portable radio station, wearable GPS personal terminal), which usually suffer from some inevitable deficiencies including increasing body load and vulnerability to extreme mountain-forest environments ( 11 – 13 ). Especially for soldiers, carrying equipment would easily expose themselves to the enemy.…”

Section: Related Workmentioning

confidence: 99%

UAV multispectral multi-domain feature optimization for the air-to-ground recognition of outdoor injured human targets under cross-scene environment

Xia

Zhu³

et al. 2023

Front. Public Health

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ObjectiveUAV-based multispectral detection and identification technology for ground injured human targets, is a novel and promising unmanned technology for public health and safety IoT applications, such as outdoor lost injured searching and battlefield casualty searching, and our previous research has demonstrated its feasibility. However, in practical applications, the searched human target always exhibits low target-background contrast relative to the vast and diverse surrounding environment, and the ground environment also shifts randomly during the UAV cruise process. These two key factors make it difficult to achieve highly robust, stable, and accurate recognition performance under the cross-scene situation.MethodsThis paper proposes a cross-scene multi-domain feature joint optimization (CMFJO) for cross-scene outdoor static human target recognition.ResultsIn the experiments, we first investigated the impact severity of the cross-scene problem and the necessity to solve it by designing 3 typical single-scene experiments. Experimental results show that although a single-scene model holds good recognition capability for its scenes (96.35% in desert scenes, 99.81% in woodland scenes, and 97.39% in urban scenes), its recognition performance for other scenes deteriorates sharply (below 75% overall) after scene changes. On the other hand, the proposed CMFJO method was also validated using the same cross-scene feature dataset. The recognition results for both individual scene and composite scene show that this method could achieve an average classification accuracy of 92.55% under cross-scene situation.DiscussionThis study first tried to construct an excellent cross-scene recognition model for the human target recognition, named CMFJO method, which is based on multispectral multi-domain feature vectors with scenario-independent, stable and efficient target recognition capability. It will significantly improve the accuracy and usability of UAV-based multispectral technology method for outdoor injured human target search in practical applications and provide a powerful supporting technology for public safety and health.

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Section: Related Workmentioning

confidence: 99%

UAV multispectral multi-domain feature optimization for the air-to-ground recognition of outdoor injured human targets under cross-scene environment

Xia

Zhu³

et al. 2023

Front. Public Health

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“…Recent work by Kumar [5] discussed educational programs to help youngsters understand how to deal with natural disasters. Takagi [12] developed a smartphone application that illustrates rescue strategies during natural disasters. While NGOs plan an important role in educating communities, teachers can plan a crucial role in educating students about disasters.…”

Section: Framework For the Education On Emergency Sheltersmentioning

confidence: 99%

Integrating Shelter Design and Disaster Education in Architectural Curriculum

Krishnan¹,

Long

2019 ASEE Annual Conference &Amp; Exposition Proceedings

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Sudarshan Krishnan specializes in the area of lightweight structures. His current research focuses on the structural design and behavior of cable-strut systems and transformable structures. His accompanying interests include the study of elastic and geometric structural stability. He teaches courses on the planning, analysis and design of structural systems. He has also developed a new course on deployable structures and transformable architecture. As an architect and structural designer, he has worked on a range of projects that included houses, hospitals, recreation centers, institutional buildings, and conservation of historic buildings/monuments.

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Automatic Air-to-Ground Recognition of Outdoor Injured Human Targets Based on UAV Bimodal Information: The Explore Study

Zhu

Zhao

et al. 2022

Applied Sciences

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The rapid air-to-ground search of injured people in the outdoor environment has been a hot spot and a great challenge for public safety and emergency rescue medicine. Its crucial difficulties lie in the fact that small-scale human targets possess a low target-background contrast to the complex outdoor environment background and the human attribute of the target is hard to verify. Therefore, an automatic recognition method based on UAV bimodal information is proposed in this paper. First, suspected targets were accurately detected and separated from the background based on multispectral feature information only. Immediately after, the bio-radar module would be released and would try to detect their corresponding physiological information for accurate re-identification of the human target property. Both the suspected human target detection experiments and human target property re-identification experiments show that our proposed method could effectively realize accurate identification of ground injured in outdoor environments, which is meaningful for the research of rapid search and rescue of injured people in the outdoor environment.

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Life Search - A Smartphone Application for Disaster Education and Rescue

Cited by 3 publications

References 0 publications

UAV multispectral multi-domain feature optimization for the air-to-ground recognition of outdoor injured human targets under cross-scene environment

UAV multispectral multi-domain feature optimization for the air-to-ground recognition of outdoor injured human targets under cross-scene environment

Integrating Shelter Design and Disaster Education in Architectural Curriculum

Automatic Air-to-Ground Recognition of Outdoor Injured Human Targets Based on UAV Bimodal Information: The Explore Study

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