Evaluation of Augmented Reality for Rapid Assessment of Earthquake-Induced Building Damage

2007 ◽  
Vol 21 (5) ◽  
pp. 303-310 ◽  
Author(s):  
Vineet R. Kamat ◽  
Sherif El-Tawil
Keyword(s):  
Augmented Reality ◽  
Rapid Assessment ◽  
Building Damage

scholarly journals RAPID ASESMEN KERUSAKAN BANGUNAN PASCA GEMPA BUMI DI SEKITAR MASJID AT-TAQARRUB, TRIENGGADING, PIDIE JAYA, ACEH

2020 ◽  
Vol 2 (1) ◽  
pp. 30-33
Author(s):  
Aldrin Febriansyah
Keyword(s):  
Building Materials ◽  
Rapid Assessment ◽  
Residential Area ◽  
Building Damage ◽  
Structural Components ◽  
High Rise

The earthquake that occurred on 7 December 2016 with a magnitude of 6.4 SR in Pidie Jaya District, Aceh has resulted in many material and immaterial losses. Where many facilities and infrastructure are damaged, buildings are not multi-storey to high-rise buildings. One of them is a residential area around the At-Taqarrub mosque, which is in the Keude area, Trienggading sub-district, Pidie Jaya district. At-Taqarrub Mosque is one of the worship facilities that is heavily damaged and cannot be repaired. In the area only the At-Taqarrub mosque was the only building that collapsed, while the surrounding buildings were still standing with various kinds of damage. This journal is to find out the results of rapid assessment of the level of damage to buildings against structures and building materials around the At-Taqarrub mosque. The method used is the method of mapping and direct survey of the surrounding buildings and then determine the level of damage to the structural components and building architecture. The results of this study indicate various levels of post-earthquake building damage that occur and provide recommendations for buildings damaged in the earthquake in Pidie Jaya in particular and throughout Indonesia in general.

Towards a rapid automatic detection of building damage using remote sensing for disaster management

2014 ◽  
Vol 23 (1) ◽  
pp. 53-66 ◽  
Author(s):  
Thi-Thanh-Hiên Pham ◽  
Philippe Apparicio ◽  
Christopher Gomez ◽  
Christiane Weber ◽  
Dominique Mathon
Keyword(s):  
Disaster Management ◽  
Spatial Resolution ◽  
Rapid Assessment ◽  
Building Damage ◽  
Visual Interpretation ◽  
Content Type ◽  
Emergency Situations ◽  
Optical Images ◽  
Damage Maps ◽  
Damage Mapping

Purpose – Satellite and airborne images are increasingly used at different stages of disaster management, especially in the detection of infrastructure damage. Although semi- or full automatic techniques to detect damage have been proposed, they have not been used in emergency situations. Damage maps produced by international organisations are still based on visual interpretation of images, which is time- and labour-consuming. The purpose of this paper is to investigate how an automatic mapping of damage can be helpful for a first and rapid assessment of building damage. Design/methodology/approach – The study area is located in Port-au-Prince (Haiti) stricken by an earthquake in January 2010. To detect building damage, the paper uses optical images (15 cm of spatial resolution) coupled with height data (LiDAR, 1 m of spatial resolution). By undertaking an automatic object-oriented classification, the paper identifies three categories of building damages: intact buildings, collapsed buildings and debris. Findings – Data processing for the study area covering 11 km2 took about 15 hours. The accuracy of the classification varies from 70 to 79 per cent depending to the methods of assessment. Causes of errors are numerous: limited spectral information of the optical images, resolution difference between the two data, high density of buildings but most importantly, certain types of building collapses could not be detected by vertically taken images (the case of data in this study). Originality/value – The automatic damage mapping developed in this paper proves to be reliable and could be used in emergency situations. It could also be combined with manual visual interpretation to accelerate the planning of humanitarian rescues and reconstruction.

scholarly journals Transfer Learning for Improving Seismic Building Damage Assessment

2022 ◽  
Vol 14 (1) ◽  
pp. 201
Author(s):  
Qigen Lin ◽  
Tianyu Ci ◽  
Leibin Wang ◽  
Sanjit Kumar Mondal ◽  
Huaxiang Yin ◽  
...  
Keyword(s):  
Damage Assessment ◽  
Historical Data ◽  
Data Transfer ◽  
Rapid Assessment ◽  
Model Performance ◽  
Building Damage ◽  
Assessment Model ◽  
Training Data ◽  
Superior Performance ◽  
The Impact

The rapid assessment of building damage in earthquake-stricken areas is of paramount importance for emergency response. The development of remote sensing technology has aided in deriving reliable and precise building damage assessments of extensive areas following disasters. It is well documented that convolutional neural network methods have superior performance in earthquake building damage assessment compared with traditional machine learning methods. However, deep learning models require a large number of samples, and sufficient numbers of samples are usually not available in the newly earthquake-stricken areas rapidly enough. At the same time, the historical samples inevitably differ from the new earthquake-affected areas due to the discrepancy of regional building characteristics. For this purpose, this study proposes a data transfer algorithm for evaluating the impact of a single historical training sample on the model performance. Then, beneficial samples are selected to transfer knowledge from the historical data for facilitating the calibration of the new model. Four models are designed with two earthquake damage building datasets and the performance of the models is compared and evaluated. The results show that the data transfer algorithm proposed in this work improves the reliability of the building damage assessment model significantly by filtering samples from the historical data that are suitable for the new task. The performance of the model built based on the data transfer method on the test set of new earthquakes task is approximately 8% higher in overall accuracy compared with the model trained directly with the new earthquake samples when the training data for the new task is only 10% of the historical data and is operating under the objective of four classes of building damage. The proposed data transfer algorithm has effectively enhanced the precision of the seismic building damage assessment in a data-limited context. Thus, it could be applicable to the building damage assessment of new disasters.

scholarly journals Mobile augmented reality in support of building damage and safety assessment

2016 ◽  
Vol 16 (1) ◽  
pp. 287-298 ◽  
Author(s):  
W. Kim ◽  
N. Kerle ◽  
M. Gerke
Keyword(s):  
Augmented Reality ◽  
Damage Assessment ◽  
Safety Assessment ◽  
Structural Integrity ◽  
Building Damage ◽  
Mobile Augmented Reality ◽  
Data Types ◽  
Mobile Ar ◽  
Structural Engineers ◽  
Disaster Event

Abstract. Rapid and accurate assessment of the state of buildings in the aftermath of a disaster event is critical for an effective and timely response. For rapid damage assessment of buildings, the utility of remote sensing (RS) technology has been widely researched, with focus on a range of platforms and sensors. However, RS-based approaches still have limitations to assess structural integrity and the specific damage status of individual buildings. Structural integrity refers to the ability of a building to hold the entire structure. Consequently, ground-based assessment conducted by structural engineers and first responders is still required. This paper demonstrates the concept of mobile augmented reality (mAR) to improve performance of building damage and safety assessment in situ. Mobile AR provides a means to superimpose various types of reference or pre-disaster information (virtual data) on actual post-disaster building data (real buildings). To adopt mobile AR, this study defines a conceptual framework based on the level of complexity (LOC). The framework consists of four LOCs, and for each of these, the data types, required processing steps, AR implementation and use for damage assessment are described. Based on this conceptualization we demonstrate prototypes of mAR for both indoor and outdoor purposes. Finally, we conduct a user evaluation of the prototypes to validate the mAR approach for building damage and safety assessment.

scholarly journals Mobile Augmented Reality in support of building damage and safety assessment

2015 ◽  
Vol 3 (4) ◽  
pp. 2599-2627
Author(s):  
W. Kim ◽  
N. Kerle ◽  
M. Gerke
Keyword(s):  
Augmented Reality ◽  
Damage Assessment ◽  
Safety Assessment ◽  
Structural Integrity ◽  
Building Damage ◽  
Mobile Augmented Reality ◽  
Data Types ◽  
Mobile Ar ◽  
Structural Engineers ◽  
Disaster Event

Abstract. Rapid and accurate assessment of the state of buildings in the aftermath of a disaster event is critical for an effective and timely response. For rapid damage assessment of buildings, the utility of remote sensing (RS) technology has been widely researched, with focus on a range of platforms and sensors. However, RS-based approach still have limitations to assess structural integrity and the specific damage status of individual buildings. Consequently, ground-based assessment conducted by structural engineers and first responders is still required. This paper demonstrates the concept of mobile Augmented Reality (mAR) to improve performance of building damage and safety assessment in situ. Mobile AR provides a means to superimpose various types of reference or pre-disaster information (virtual data) on actual post-disaster building data (real building). To adopt mobile AR, this study defines a conceptual framework based on Level of Complexity (LOC). The framework consists of four LOCs, and for each of these the data types, required processing steps, AR implementation, and use for damage assessment, are described. Based on this conceptualization we demonstrate prototypes of mAR for both indoor and outdoor purposes. Finally, we conduct a user evaluation of the prototypes to validate the mAR approach for building damage and safety assessment.

Evaluation of Three-Dimensional Shape Signatures for Automated Assessment of Post-Earthquake Building Damage

2013 ◽  
Vol 29 (3) ◽  
pp. 897-910 ◽  
Author(s):  
Wei Liu ◽  
Pinliang Dong ◽  
Jianbo Liu ◽  
Huadong Guo
Keyword(s):  
Rapid Assessment ◽  
Computational Cost ◽  
Three Dimensional ◽  
Building Damage ◽  
Light Detection And Ranging ◽  
Building Models ◽  
Urban Models ◽  
Dimensional Shape ◽  
Shape Signatures ◽  
Three Dimensional Shape

This paper proposes two new measures of three-dimensional shape signatures based on the slope and aspect of three-dimensional triangles, and evaluates the performance of three-dimensional shape signatures derived from distance, area, angle, volume, slope, and aspect for assessing post-earthquake building damage using simulated building models with flat, pent, gable and hip roofs. Three scenarios of post-earthquake building damage are tested using simulated light detection and ranging (LiDAR) points generated on the building roofs. Dissimilarity, sensitivity, and computational cost of the three-dimensional shape signatures are also discussed. The results show that a combination of three-dimensional shape signatures derived from slope and aspect can provide better detection of post-earthquake building damage compared with those derived from distance, area, angle, and volume. The paper demonstrates a promising method for rapid assessment of post-earthquake building damage using existing three-dimensional urban models and post-earthquake LiDAR data.

Zone-axis ALCHEMI for the rapid assessment of site occupancies in garnets

1986 ◽  
Vol 44 ◽  
pp. 706-707
Author(s):  
M.T. Otten ◽  
P.R. Buseck
Keyword(s):  
Single Crystals ◽  
Rapid Assessment ◽  
Site Occupancy ◽  
Zone Axis ◽  
Synthetic Compounds ◽  
X Ray ◽  
Large Group ◽  
Crystallographic Planes

ALCHEMI (Atom Location by CHannelling-Enhanced Microanalysis) is a TEM technique for determining site occupancies in single crystals. The method uses the channelling of incident electrons along specific crystallographic planes. This channelling results in enhanced x-ray emission from the atoms on those planes, thereby providing the required site-occupancy information. ALCHEMI has been applied with success to spinel, olivine and feldspar. For the garnets, which form a large group of important minerals and synthetic compounds, the channelling effect is weaker, and significant results are more difficult to obtain. It was found, however, that the channelling effect is pronounced for low-index zone-axis orientations, yielding a method for assessing site occupancies that is rapid and easy to perform.

Amp Up Your Treatment With Augmented Reality

ASHA Leader ◽  
2013 ◽  
Vol 18 (9) ◽  
pp. 14-14 ◽  
Keyword(s):  
Augmented Reality

Amp Up Your Treatment With Augmented Reality

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