Post-disaster Rescue Research Articles

Unmanned Aerial Vehicle Computation Task Scheduling Based on Parking Resources in Post-Disaster Rescue

Natural disasters bring huge loss of life and property to human beings. Unmanned aerial vehicles (UAVs) own the advantages of high mobility, high flexibility, and rapid deployment, and are important equipment during post-disaster rescue. However, UAVs usually have restricted battery and computing power. They are not fit for performing compute-intensive tasks during rescue. Since there are widespread parking resources in a city, multiple parked vehicles working together to compute the applications from UAVs in a post-disaster rescue is investigated to ensure the quality of experience (QoE) of the UAVs. To execute uploaded task effectively, surviving parked vehicles within the monitoring range of an UAV are arranged into a cluster as much as possible. Then, the task execution cost is analyzed. Furthermore, a deep reinforcement learning (DRL)-based offloading policy is constructed, which interacts with the environment in an intelligent way to achieve optimization goals. The simulation experiments show that the proposed offloading scheme has a higher task completion rate and a lower task execution cost than other baselines schemes.

Study on typhoon disaster assessment by mining data from social media based on artificial neural network

Typhoon disaster is a major threat to the economy and personnel safety in coastal areas. After the disaster, the objective assessment of typhoon disaster economic losses can provide an important reference for the post-disaster rescue and reconstruction and improve the scientific decision making. In this study, social media data, disaster causing factors, disaster bearing carriers (exposure and vulnerability) and other factors in traditional disasters were combined to achieve rapid disaster assessment. Convolutional neural networks were used to train a text classifier and perform automatic text classification of social media data. The correlations were discussed between various texts and disaster economic losses. It was found that there was a strong correlation between the geographical distribution of texts describing disaster damage and disaster economic losses. A back-propagation neural network was used for supervised learning to realize disaster loss assessment. To prove the reliability and applicability of the evaluation model, typhoons “Mangkhut” and “Lekima” were selected as study cases to realize the whole process from information collection to final assessment. The introduction of social media data modified the assessment results obtained by traditional methods and reduced the difference between the estimated disaster loss value and the actual value.

Compact Real-Time Control System for Autonomous Vehicle

Due to global warming, there is an increase in the number of natural disasters occurring around the world. With more disasters happening, post disaster search and rescue personnel are putting their life on the line more often in scouting out the post disaster site and sending in first aid supplies while waiting for rescue vehicles like fire trucks and ambulance to arrive. In Malaysia alone, the use of compact Autonomous Landed Vehicle (ALV) for this purpose is limited. There are many compact ALV that are being developed with microcontrollers and microprocessors such as Arduino and Raspberry Pi as the central control system, but they are fragile and can be damaged easily when used in harsh environments. In addition, multiple microcontrollers and microprocessors are needed for the ALV as parallel processing and limited gates are some of the common problems with microprocessors and microcontrollers. In this paper, a central control system using an FPGA is proposed together with the design of a prototype for the ALV. The ALV consists of three systems: Propulsion System, Sensor System, and Remote-Control System. These systems are integrated together with the Altera DE-115 board as the central control unit of the ALV. Verilog Hardware Description language (Verilog HDL) is used for designing the control system for the ALV. The proposed system is stable, low cost, allows parallel processing and the compact size of the ALV allows smooth manoeuvring through small areas of post disaster sites to scout out the area and send in first aid supplies to the victims.

Numerical investigation of novel 3D-SPA for gripping analysis in multi-environment

The soft pneumatic actuator (SPA) has strong flexibility and good compliance, allowing its assembly into a multi-functional soft gripper that can be applied to object grasping and handling, post-disaster rescue, rehabilitation training, and in other fields. However, many actuators have limited grasping modes and can only bend in a single direction. And most of the soft grippers are studied in free space for grasping. Herein, a novel 3D-SPA with internal bellows chambers, inspired by the structure of the bird claws and the human fingers, is presented. Based on Yeoh hyperelasticity theory and virtual work principle, the mechanical theoretical model between different input air pressure Pin and the bending angle θ of the actuator is established, and the spatial conversion relationship of obstacle avoidance motion is given. The influence of the length and number of the chamber, the radius of the circular section, the shape of the cross section and the length of the joint on the bending performance and stress distribution of the actuator are studied in detail, respectively. Two soft grippers with different structures, composed of 3D-SPA, have a variety of bending configurations on different planes, which improves the inclusiveness of grasping objects with different shapes and sizes. Finally, the process of object grasping in free space and obstacle avoidance grasping and handling in obstacle space are studied respectively. The validity of the proposed mechanical model and spatial transformation relationship are verified. The investigation results reveal that the developed scheme assists the robot’s obstacle avoidance and grasping, which can be integrated into industrial robotic arms and AGVs for mobile operations and applied to rehabilitation training to help patients gradually recover hand joint function.

RISK ASSESSMENT OF GEOLOGICAL DISASTERS ALONG THE G213 MAOXIAN-WENCHUAN SECTION BASED ON GF-6 DATA

Abstract. China is a country prone to natural disasters, and roads are easily damaged in natural disasters. As the infrastructure of people's production and life and the lifeline of post-disaster rescue, roads play a very important role. There are many previous studies on geological disasters risk assessment, but few special researches on highway geological disasters risk assessment, especially quantitative risk assessment combined with remote sensing images. Therefore, the risk assessment of geological disasters along the road is of great significance for the prevention and control of geological disasters and the protection of life and property safety. Based on GF-6 data and other geographic data, this study used the comprehensive evaluation method to realize the geological disasters risk assessment of the Maoxian-Wenchuan section along the G213 line, and analysed and discussed the causes and spatial distribution of geological disasters along the G213 line. Our study presents several key findings, (1) The order of impact degree of each impact factor is road network density, soil erosion, slope, human activities, vegetation coverage, rainfall, and slope aspect, among them, the road network density factor plays a leading role, and the aspect factor is the least impact factor; (2) The geological disasters risk in the study area is divided into five categories: extremely low risk, low risk, medium risk, high risk, and extremely high risk. In general, the geological disasters risk of the research road section is relatively high, and the risk area division is consistent with the historical disaster point data. The research results can provide reference for the smooth development and implementation of road geological disasters risk assessment in the mountainous areas in southwestern China.

Distinction of Human and Mechanical Vibrations within Similar Frequency Bands Based on Wavelet Entropy Using Ultrawideband Radar

Construction machinery is necessary in postdisaster emergency rescue missions involving the destruction of ruins. However, their mechanical vibrations can interfere with the detection of human survivors using ultrawideband (UWB) radar. Traditional methods detect and identify humans by determining maximum energy and checking respiratory frequency. However, they lose effectiveness because mechanical vibration is associated with a frequency band which is similar to the human respiration band, but it has higher energy. This study proposes a novel method to distinguish human vibrations from mechanical vibrations. After preprocessing, wavelet entropy decomposition was implemented on the radar data. An improved, censored mean-level detector, constant false-alarm rate algorithm was utilized to automatically identify the position of human and mechanical vibrations. A novel feature is then extracted by calculating the half-height width of the target’s wavelet entropy. Finally, the results of two independent sample t-tests prove that there is a significant statistical difference between the feature values of humans and the mechanical vibrations (p < 1.9 × 10−6), thus proving the effectiveness of the method. We envisage that the proposed method can be used in postdisaster rescue missions to improve the accuracy and speed of identifying human targets. Therefore, more survivors may be rescued.

Deterministic and Probabilistic Seismic Hazard Analysis of Tindharia, Darjeeling Sikkim Himalaya, India

Abstract The simulation of appropriate ground motion is the main objective in earthquake-resistant designing to mitigate the impact of landslides and structural damages. The seismic hazard studies serve as the basis for quantifying the hazard associated within the particular area over a given time period. In this study, the detailed site specific hazard analysis of Tindharia site as well as Darjeeling Sikkim Himalaya (DSH) region has been carried out to assure the safety of human and infrastructure against seismic risk. The study area is mountainous region on north western side of India, falls in seismic zone IV and V, and is one of the most seismically active regions with vulnerable earthquakes along with fatal landslides. The future large earthquakes are likely to occur in the region due to constant movement of Indian plate towards Eurasian plate. Therefore, the heightened seismic risk increases the demand for seismic studies near the Himalayan belt. Thus, the assessment of associated seismic hazard in the study area has been carried out by deterministic and probabilistic seismic hazard approaches. From the results, the seismo-tectonic map of a 300km radial distance of the study area is developed. The deterministic hazard distribution in terms of peak ground acceleration (PGA) and the PGA and peak spectral acceleration (PSA) hazard maps for 2% and 10% probability of exceedance in 50 years at different time periods have been generated. The updated hazard maps developed in this study play pivotal roles in mitigation measures with better pre-disaster prevention by earthquake resistant design and in preparedness and post disaster rescue in the study area.

Fault-tolerant motion planning for a hexapod robot with single-leg failure using a foot force control method

Hexapod robots are widely used for resource exploration, post-disaster rescue, and military equipment. They typically travel on rugged and complex roads. The robot itself has a high probability of failure owing to mechanical failure, driving motor failure, or external environmental interference. To improve the adaptability of the robot to a complex environment, a motion control method for fault-tolerant gait was designed. The trajectory generator based on zero-moment point information can generate a smooth desired trajectory for the body’s center of mass, thereby improving the robot’s zero-moment point trajectory tracking effect and motion stability. The force-distribution algorithm based on torque optimization selects the minimum square sum of the driving force as the objective function and reduces the number of constraint equations through QR decomposition to increase the speed at which the expected contact force at the foot is calculated. A CoppeliaSim and MATLAB/Gurobi joint simulation platform were built to simulate and verify the fault-tolerant motion planning of the hexapod robot and foot contact force control algorithm. The feasibility and effectiveness of the fault-tolerant motion planning and foot force control algorithm applied to a hexapod robot with a single-foot failure are verified.

Task Offloading for Post-Disaster Rescue in Unmanned Aerial Vehicles Networks

Natural disasters often cause huge and unpredictable losses to human lives and properties. In such an emergency post-disaster rescue situation, unmanned aerial vehicles (UAVs) are effective tools to enter the damaged areas to perform immediate disaster recovery missions, owing to their flexible mobilities and fast deployment. However, UAVs typically have very limited battery and computational capacities, which makes them harder to perform heavy computation tasks during the complicated disaster recovery process. This paper addresses the issue of the battery and computation resource limitation with a fog computing based UAV system. Specifically, we first introduce the vehicular fog computing (VFC) system in which the unmanned ground vehicles (UGVs) perform the computation tasks offloaded from UAVs. To avoid the transmission competitions yet enable cooperations among UAVs and UGVs, a stable matching algorithm is developed to transform the computation task offloading problem into a two-sided matching problem. An iterative algorithm is then developed which matches each UAV with the most suitable UGV for offloading. Finally, extensive simulations are carried out to demonstrate that the proposed scheme can effectively improve utilities of UAVs and reduce average delay through comparison with conventional schemes.

Disaster Risk Reduction Lessons from February 7, 2021 Flash Flood in Uttarakhand Province of India

204 people were killed, while two hydropower projects located in close proximity to Rini (13.2 MW) and Tapoban (520 MW) were severely damaged in Dhauliganga flood of February 7, 2021, in the Indian Himalaya. In addition, it caused massive loss of farm animals, agricultural land, property and infrastructure. This incidence occurred during the winter season when the discharge of glacier fed rivers is minimal, and the region did not experience rains around the time of the flood. Based on a detailed review of post-disaster search and rescue efforts, and bottlenecks faced by disaster managers, authors recommend (i) scientific documentation of past catastrophic events, (ii) detailed assessment of the risk posed by various hazards, (iii) legally binding disaster risk assessment, and a reduction mandate for major infrastructure projects, (iv) robust, reliable and redundant warning generation and dissemination infrastructure, (v) diversification of assets, and (vi) creating a dedicated cadre of Disaster Risk Reduction (DRR) professions.

Escalating post-disaster rescue missions through ad-hoc victim localization exploiting Wi-Fi networks

The number of disasters, accidents, and casualties in disasters is increasing, however, technological advancement has yet to ripe benefits to emergency rescue operations. This contrast is even more prominent in the Global South. The consequences are a huge loss of wealth and resources, but more importantly, the loss of lives. Locating victims of disasters as quickly as possible while speeding up rescue operations can lessen these losses. Traditional approaches for effective victim localization and rescue often requires the establishment of additional infrastructure during the construction period. Which in the context of countries of the global south such as - Bangladesh, is not followed for most of the industrial and household constructions. In this paper, we conduct a study to better understand the challenges of victim localization in emergency rescue operations and to overcome them using “whatever” resources available at hand without needing prior infrastructure facilities and pre-calibration. We design and develop a solution for this purpose and deployed it in several emulated disaster-like scenarios. We analyze and discuss the results obtained from our experiments. Finally, we point out the design implications of an infrastructure-independent and extensive emergency rescue system.

Numerical investigation of a bioinspired multi-segment soft pneumatic actuator for grasping applications

Soft robotic gripper is useful for grasping applications, such as pick-and-place tasks, post-disaster rescue and health monitoring of civil infrastructure. Inspired by the versatility of the human hand and bird claws, this paper designed a bioinspired actuator made of multi-segment fibre-reinforced pneumatic bending actuator and bellow-shape pneumatic rotational actuator joints. A numerical model was established to investigate the bending performance and stress distribution of the designed actuator under different input pressures. The influences of bottom layer thickness, chamber number at the actuator joints, and bending segment length on the overall bending performance of the designed soft actuator have been comprehensively investigated. In addition, the stress distribution of the actuator joints has been studied for understanding the mechanical performance of the actuator joints. Finally, a soft gripper made of two designed actuators has been demonstrated for grasping objects with different shapes and weights. The findings found in this investigation are helpful for the design and fabrication of robotic grasper, which can be further integrated on an industrial robotic arm and flying robotic platform for grasping and prosthetic hand applications.

Modeling and Analysis of Postdisaster Aviation Medical Rescue Process Using SPN-MC

Analyzing the time characteristics of the aviation medical rescue process after sudden natural disasters is an extremely important guarantee for efficient rescue. In view of the problem of the significant increase in the complexity and uncertainty of the postdisaster aviation medical rescue process under time constraints, this study sorted out and analyzed the postdisaster aviation medical rescue process. The dynamic discrete modeling of the postdisaster aviation medical rescue process was carried out in combination with the stochastic Petri net (SPN) theory, and the effectiveness of the process of postdisaster aviation medical rescue was analyzed by using the isomorphism relationship between SPN and Markov chain (MC). Finally, the Sichuan Jiuzhaigou Earthquake event was taken as a case study to carry out the performance analysis and sensitivity analysis of the postdisaster aviation medical rescue process model. The results showed that information accumulation tends to occur in the process of flight planning, flight preparation, flight information transmission, and field information feedback. On-site rescue, casualty transfer, preflight preparation, and personnel preparation take a relatively long time. In the actual rescue process, emergency decision-makers and rescue crews should focus on optimizing and improving these links. The route formulation and airspace application as the main factors affecting the operation time of the postdisaster aviation medical rescue process system should be used as the key to process optimization so as to improve the efficiency of postdisaster aviation medical rescue.

Optimal control of the multi-module vibration-driven locomotion robot

The vibration-driven robot utilizes the periodic inertia force from the oscillator to realize locomotion. Because its movement does not rely on wheels or legs, the robot's body can be designed very neatly for working in restricted circumstances such as pipeline inspection and post-disaster rescue. Because high mobility is essential in these applications, the issue of actuation design to maximize the robot's average locomotion velocity emerges. Distinct from parameter optimization at given actuation patterns, the present paper represents the actuation design as the problem of optimal control and constructs an evolutionary algorithm to solve it. First, taking advantage of the periodicity, the internal actuation is represented as the Fourier series with the unknown period, harmonic coefficients, and phase shifts. Then, the multi-objective evolutionary algorithm based on decomposition (MOEA/D) is employed to optimize the unknown multi-parameters. Numerical results show that the optimal actuation of the one-module robot with isotropic friction is consistent with existing theoretical solutions, which verifies the correctness and practicability of our general scheme. Further explorations of the multi-module robot reveal that the optimal actuation continuously degenerates from the three-phase pattern to the two-phase when the friction ratio gradually attenuates to zero. Most importantly, although the optimal actuation phase shift between adjacent robot modules has been commonly accepted as half of the actuation period, the proposed scheme finds that the average velocity indeed maintains the maximum within a certain phase margin. As can be expected, this robustness will relax the burden of sophisticated actuation tuning in practice.

Autonomy-oriented proximity mobile social network modeling in smart city for emergency rescue

Nearest neighbor mobile social network means that movers approaching in position communicate through their social sensors, which is called Proximity Mobile Social Network. Proximity Mobile Social Network can provide more social and business opportunities for users. To carry out disaster relief work in post-disaster environment, we need to collect incident information during the search process and report to the sink in time. Proximity Mobile Social Network provides flexible systems for emergency handling and disaster relief. Therefore, how to find a better data forwarding and routing strategy is the key problem of post-disaster rescue, and the research of user mobility model is the basis of the above problems. This article presents an Autonomy-Oriented Proximity Mobile Social Network modeling for emergency rescue in smart city, which simulates the network operating environment. First, we verify the performance of Autonomy-Oriented Proximity Mobile Social Network model in terms of self-organization, scale-free, aggregation, and community structure. Then, the rescue efficiency is discussed through the coverage of mobile sensors. Finally, performance of the routing strategy based on Autonomy-Oriented Proximity Mobile Social Network model is analyzed, and the effectiveness of the method is proved.

A scoping review of youth and young adults' roles in natural disaster mitigation and response: considerations for youth wellbeing during a global ecological crisis.

Youth and young adults, ages 15-29, have been identified as assets in mitigation and management for natural disasters around the world. This study reviews the literature on disaster mitigation, response, and recovery following natural disasters with a focus on the engagement of youth and young adults. The Arksey and O'Malley (2005) scoping review model was used to broadly summarize existing literature. A comprehensive electronic search was conducted using several databases. Keywords and index terms were searched using four concepts: (a) age (e.g., youth, young adult), (b) participation type (e.g., engagement, participation), (c) natural disaster type (e.g., hurricane, tsunami), and (d) disaster response type (e.g., planning, mitigation). The search yielded 214 articles published between 1990 and 2021. Of these articles, 19 met inclusion criteria. Identified literature focused on youth and young adults' mitigation and recovery efforts responding to natural disasters in several different countries. Themes of young people's participation or youth-led efforts focused on community mobilization and resilience (n = 5), youth empowerment and policy advocacy (n = 2), communication technology (n = 2), education-community partnerships (n = 9), and postdisaster rescue efforts (n = 1). With a changing climate and increased weather-related natural disasters, as well as in the context of a global health pandemic, community-based groups would benefit from learning from international efforts to engage young people in disaster mitigation and recovery efforts especially as it relates to promoting mental health and well-being.

The variation of environmental parameters after gas explosion in semi-closed pipeline

ABSTRACT The understanding of the laws of environmental parameters in the later stage of gas explosion in coal mine roadways is of great significance for the prevention and control of derivative disasters and post-disaster rescue. To further comprehend this, the article performed explosion experiments under different gas concentrations in a semi-closed pipeline, focusing on the continuously varied rules of environmental parameters (pressure, temperature, humidity) after a gas explosion. The results showed that the pressure at the open end of the pipeline exhibited a relatively remarkable upward tendency when it arrived in the valley. By comparing with the pressure monitored in the middle of the pipeline, it was concluded that there was a more apparent air reflux phenomenon at the open end. The changes in temperature and humidity were roughly similar, both had a relatively distinct increase after an explosion, with the temperature rising by 7.2% on average and the humidity increasing by 2.7% on average. When the methane concentration was 9.5%, its pressure peaks, temperature peak, and humidity peak were all the maximum. Moreover, the phenomenon of air reflux was also the earliest, with 3.1 seconds, which demonstrated that the closer to the gas equivalent concentration, the more sufficient and violent the explosion reaction, the greater the possibility of secondary accidents. The research can provide a theoretical basis for preventing derived hazards (coal dust explosions, secondary explosions) and reducing the effect of derived hazards.

Study on Numerical Simulation of Fire Danger Area Division in Mine Roadway

High-temperature poisonous smoke produced by coal mine roadway fire seriously affects miners' lives and safety. Studying the development law of high-temperature smoke in the process of mine roadway fire and then exploring the danger of roadway are of great significance to personnel safety and post-disaster rescue. In order to study this problem, the CFD numerical simulation method is used to establish a fire calculation model based on ANSYS Fluent software in the development stage of mine fire. The high-temperature flue gas flow in the roadway during the development stage of mine fire is simulated, and the variation law of temperature field and gas concentration field with time and space position under different levels of roadway in the development stage of fire is revealed. The variation rules of environmental parameters, such as temperature, CO, and CO2, are obtained by numerical calculation. Based on these, the danger zones of smoke spread in fire development stage are divided by the critical values of high-temperature smoke and toxicity evaluation index, and the mathematical fitting analysis of the evolution of the dangerous area with time is carried out. The research results have certain theoretical guiding significance for reducing underground environmental pollution and ensuring the personal safety of workers and rescuers.

A coarse-to-fine detection and localization method for multiple human subjects under through-wall condition using a new telescopic SIMO UWB radar

Radar-based life detecting technology has been researched more and more in recent years and applied widely in several areas. However, few researches on multi-subjects detecting and locating have been reported. Even these researches are mainly based on imaging technology with two shortcomings, namely the interference of ghost and difficult to focus the target’s position. A new coarse-to-fine approach for detecting and locating of human targets using single-input multiple-output (SIMO) radar under penetration conditions is proposed. The approach realized automatic recognition and localization of human subjects without any prior information, such as target count. Firstly, an improved censored mean level detector constant false alarm rate (CMLD-CFAR) by adding a feature to distinguish vital sign from background is proposed in each inner-channel to coarsely determine the targets’ time-of-arrival (TOA) distances. Secondly, the real targets count is finely determined by calculating the inter-channel Pearson correlation coefficient of signals from different channels. Then, a back projection (BP) is presented to calculate the targets’ 2-D locations. In the experiments of single and multi-target locating, all targets were identified correctly and localized near their actual positions with errors within 0.3 m. With the distinctive telescopic structure of the proposed radar, the azimuth resolution of locating is adjustable. Compare to current radar system for radar multi-target locating, like multiple-input multiple-output (MIMO) system, the proposed system can improve accuracy and automation of localization while decline the cost and complexity. It has potential to promote practical application of locating trapped human targets in post-disaster rescue and intelligent homeware fields.

Building damage detection based on multi-source adversarial domain adaptation

Building damage assessment plays an essential role during post-disaster rescue operations. Given that labeled samples are difficult to timely obtain after a disaster, transfer learning attracts increasing attention. However, different sensors employed cause considerable discrepancies not only between historical and current scenes but also among historical scenes, which could exert an effect on transfer performance. Therefore, a multi-source adversarial domain adaptation (MADA) method is proposed in this paper to fulfill the task of post-disaster building assessment. This method consists of two phases. First, imageries of several historical scenes are transformed into the same style of the current scene through the CycleGAN model with a classifier, ensuring class invariance, to be fused to make an adapted source domain. Second, feature alignment between adapted source and target domains is executed based on adversarial discriminative domain adaptation. The MADA method enhances the transformed image quality, fully utilizes relevant information in historical scenes, solves inter-scene interference problems among historical images, and improves the transfer efficiency from historical to the current disaster scene. Two experiments are conducted with Hurricane Sandy, Irma, and Maria datasets as multi-source and target domains to validate MADA’s effectiveness. Results show that the classification performance is better than other methods.