A Smart Integrated Vest for the Canine Companion of the K9 Units

Search and rescue operations can range from small, confined spaces, such as collapsed buildings, to large area searches during missing person operations. K9 units are tasked with intervening in such emergencies and assist in the optimal way to ensure a successful outcome for the mission. They are required to operate in unknown situations were the lives of the K9 handler and the canine companion are threatened as they operate with limited situational awareness. Within the context of the INGENIOUS project, we developed a K9 vest for the canine companion of the unit, aiming to increase the unit’s safety while operating in the field, assist the K9 handler in better monitoring the location and the environment of the K9 and increase the information provided to the Command and Control Center during the operation.

Identifying Damaged Buildings in Aerial Images Using the Object Detection Method

The collapse of buildings caused by the earthquake seriously threatened human lives and safety. So, the quick detection of collapsed buildings from post-earthquake images is essential for disaster relief and disaster damage assessment. Compared with the traditional building extraction methods, the methods based on convolutional neural networks perform better because it can automatically extract high-dimensional abstract features from images. However, there are still many problems with deep learning in the extraction of collapsed buildings. For example, due to the complex scenes after the earthquake, the collapsed buildings are easily confused with the background, so it is difficult to fully use the multiple features extracted by collapsed buildings, which leads to time consumption and low accuracy of collapsed buildings extraction when training the model. In addition, model training is prone to overfitting, which reduces the performance of model migration. This paper proposes to use the improved classic version of the you only look once model (YOLOv4) to detect collapsed buildings from the post-earthquake aerial images. Specifically, the k-means algorithm is used to optimally select the number and size of anchors from the image. We replace the Resblock in CSPDarkNet53 in YOLOv4 with the ResNext block to improve the backbone’s ability and the performance of classification. Furthermore, to replace the loss function of YOLOv4 with the Focal-EOIU loss function. The result shows that compared with the original YOLOv4 model, our proposed method can extract collapsed buildings more accurately. The AP (average precision) increased from 88.23% to 93.76%. The detection speed reached 32.7 f/s. Our method not only improves the accuracy but also enhances the detection speed of the collapsed buildings. Moreover, providing a basis for the detection of large-scale collapsed buildings in the future.

Development and analysis of a bio-inspired wire-driven variable stiffness double spring based tapered multi-section flexible robot

Purpose The purpose of this paper is to develop a tendon actuated variable stiffness double spring based continuously tapered multi-section flexible robot and study its capability to achieve the desired bending and compression for inspection in cluttered environments. Design/methodology/approach Spring-based continuum manipulators get compressed while actuated for bending. This property can be used for the advantage in cluttered environments if one is able to control both bending and compression. Here, this paper uses a mechanics based model to achieve the desired bending and compression. Moreover, this study tries to incorporate the tapered design to help in independent actuation of the distal sections with minimal effects on proximal sections. This study is also trying to incorporate the double spring based design to minimize the number of spacers in the robot body. Findings The model was able to produce desired curvature at the tip section with less than 4.62% error. The positioning error of the manipulator is nearly 3.5% which is at par with the state-of-the-art manipulators for search and rescue operations. It was also found that the use of double spring can effectively reduce the number of spacers required. It can be helpful in smooth robot to outer world interaction without any kink. From the experiments, it has been found that the error of the kinematic model decreases as one moves from high radius of curvature to low radius of curvature. Error is maximum when the radius of curvature is infinity. Practical implications The proposed manipulator can be used for search operations in cluttered environments such as collapsed buildings and maintenance of heavy machineries in industries. Originality/value The novelty of this paper lies in the design and the proposed kinematics inverse kinematics for a spring-based continuously tapered multi-section manipulator.

Irregularity of the Distribution of Masonry Infill Panels and Its Effect on the Seismic Collapse of Reinforced Concrete Buildings

On 16 April 2016, an earthquake of Mw 7.8 shook the coast of Ecuador, causing the destruction of buildings and a significant number of casualties. Following a visit by the authors to the city of Portoviejo during the debris removal and recovery stage, it was noted that several reinforced concrete buildings located on corners had collapsed in the central part of the city. These buildings were characterized by the presence of masonry at the edges of the buildings but not between the two mostly open-plan facades on the corner for practical reasons. This article reviews the effect of masonry infill panels on the seismic response of reinforced concrete structures. For this, a model that contains the geometric and mechanical characteristics typical of collapsed buildings was generated and subjected to nonlinear analysis, with both static and dynamic increments. The results show the clear influence of the masonry infill panels on the structural response through the torsional behavior that is reflected in the evolution of the floor rotations. Finally, dynamic incremental analysis is used to obtain the collapse fragility curve of the building, and a new damage measure based on floor rotations is proposed.

Identifying geometric configuration of earthquake-resistant buildings

Indonesia is an earthquake-prone area because it is located at the world's most active tectonic plates and hundreds of local faults. Obviously, there have been many earthquake victims caused by collapsed buildings, hence the need for earthquake-resistant construction. However, there is not much guidance for architects to design earthquake-resistant buildings. This research proposes guidance for architects on how to design building forms relatively able to resist earthquakes. The simulation experiment method involving 32 building models in various forms was employed. The experimental results were then analyzed with modal analysis in ETABS and SVA for architectural design. Based on the analysis report, some guidelines were proposed: 1). Avoid buildings that are too slender, use the slenderness ratio H/D ≤ 2, 2). Avoid soft stories where the ratio of the top column height (h) to the bottom column height (h1) ≤ 0.8, 3). Use symmetrical shapes with 1 or 2 axes and avoid shapes with random compositions, 4). Use the additive and subtractive mass transformation ≤ 15%, 5).Strengthen the structural elements, install shear walls, or use dilatation to minimize potential torsional irregularities and non-parallel system irregularities of L, T, U, +, and Z forms6). Avoid using non-axial asymmetrical forms.

The dynamic response of coseismic liquefaction-induced ruptures associated with the 2019 Mw 5.8 Mirpur, Pakistan, earthquake using HVSR measurements

The Mirpur area of Pakistan was severely damaged by extensive coseismic liquefaction following an earthquake of Mw 5.8 on 24 September 2019. Villages within 6 km of the epicenter were adversely affected due to extensive coseismic liquefaction-induced surface and shallow subsurface deformations. The earthquake affected all types of buildings and key infrastructure (e.g., the Upper Jhelum Canal and the main Jhelum–Jatlan road). Field observations and associated effects are presented, including horizontal-to-vertical spectral ratio (HVSR) data sets acquired from three sites to evaluate the site response characteristics of the liquefaction-affected soil profiles. As a result, rupture events strongly influenced spectral features (amplitude and frequency) and site-specific 1D shear-wave velocity profiles at sites S1 and S2. The dynamic behavior of HVSRs across ruptures at sites S1 and S2 corresponds to varied levels of seismic amplification, demonstrating the impact of liquefaction-induced ruptures of seismic origin on the site response that have not been reported previously in the literature. The consistent HVSR pattern of well-established high-frequency peaks at site S3 adjacent to partially damaged to completely collapsed buildings of different types further indicates the susceptibility of potential liquefaction hazard. These results agree with the surface liquefaction signatures in the field, revealed by inverted electrical resistivity tomography models in terms of liquified sand plugs, clay lenses and associated fractures, and increasing trends of radon concentration in the soil with decrease in the distance toward ruptures. Additionally, the successful application of HVSR as a cost-effective and speedy tool attests to the potential of the proposed approach in furnishing complementary information for better assessment of liquefaction hazards in the developing world, where financial constraints are a major issue. This can help with seismic hazard analysis and mitigation in the Mirpur area and may have applications in other seismically active regions of the world.

AUTOMATED DETECTION OF COLLAPSED BUILDINGS WITH USE OF OPTICAL AND SAR IMAGES, CASE STUDY: IZMIR EARTHQUAKE ON OCTOBER 30TH, 2020

In this study, we have analysed the optical and SAR images both to detect the collapsed building automatically with the use of the cloud-based programming environment Google Colab Cloud environment. We have used the existing digital map of buildings which were provided by Here Maps Company, for each building feature, the histograms were generated both for optical and SAR images, the unmatched histograms on the optical image were mainly the destroyed buildings and newly established tent areas for the people who lost their homes. In the method, the most recent (before and after) optical images of the earthquake zone are taken. Some pre-processing steps were performed including principal component analysis, K-Means clustering. Then, the statistical values of area overlap with the building vectors are calculated and the threshold values are determined. SAR images are used to refine the results. he used optical satellite images are Worldview images with 30 cm GSD, and for SAR images, Sentinel 1 C band and ICEYE X band SAR images are used. Sentinel 1 and ICEYE images are provided from ESA.

Disaster scene reconstruction: modeling, simulating, and planning in an urban disaster environment

Urban disasters are characterized by buildings collapsing. The rubble of collapsed buildings forms a chaotic, unplanned and unmapped environment in which emergency first responders must find the surviving occupants who are now trapped and hidden in the dangerous rubble. The more knowledge that search teams have pertaining to the resulting environment the better they are equipped to plan and rescue survivors. Our research demonstrates that simulations can be used to inspect urban disaster-related terrain remotely and safely within hours of the actual disaster. The Disaster Scene Reconstruction system allows for the creation of accurate 3D models and a simulation providing custom functionality --such as virtual structural inspection and--providing first responders the ability to plan actions in the simulated environment. The goal of this research is to demonstrate that the functionality we developed can be used to provide accurate information to users and potentially assist search and rescue planning efforts.

Disaster scene reconstruction: modeling, simulating, and planning in an urban disaster environment

Urban disasters are characterized by buildings collapsing. The rubble of collapsed buildings forms a chaotic, unplanned and unmapped environment in which emergency first responders must find the surviving occupants who are now trapped and hidden in the dangerous rubble. The more knowledge that search teams have pertaining to the resulting environment the better they are equipped to plan and rescue survivors. Our research demonstrates that simulations can be used to inspect urban disaster-related terrain remotely and safely within hours of the actual disaster. The Disaster Scene Reconstruction system allows for the creation of accurate 3D models and a simulation providing custom functionality --such as virtual structural inspection and--providing first responders the ability to plan actions in the simulated environment. The goal of this research is to demonstrate that the functionality we developed can be used to provide accurate information to users and potentially assist search and rescue planning efforts.