Rescue Environment Research Articles

The digital twins for mine site rescue environment: Application framework and key technologies

In the era of widespread adoption of the new generation of information technology, the crucial development directions for mine site emergency rescue include systematization, precision, intelligence, and diversification. Chinese mines have extensively invested in information technology construction in the field of safety. However, despite these efforts, they still face complex and changing situations following mine disasters. It is often difficult to comprehensively capture all information and devise appropriate rescue plans during the site rescue process. In this context, herein, the scientific connotation of the digital twin system for mine site rescue environment (DTS-MRE) is proposed. Further, its overall architecture, functional characteristics, and key technologies essential for system construction are introduced. The application of DTS-MRE is expected to aid the monitoring, simulation, emulation, coordination, prediction, and control of the entire process of mine emergency rescue governance; increase the success rate of mine emergency rescue; and provide scientific and technological support for mine safety emergency rescue.

Dual-antenna multidimensional positioning algorithm based on positioning of disaster relief personnel

When facing a major disaster, firefighters and other rescue workers may also encounter certain dangers, which means certain protective measures are needed to ensure the safety of disaster relief personnel. Due to the complexity of the rescue environment, such as being blocked by obstacles or due to the influence of magnetic field, satellite positioning may not be used, and the position of the personnel in need of rescue can not be accurately located. On account of the above issues, we used search and rescue equipment and handheld terminals, and the dual antenna multidimensional positioning algorithm were also used to determine the position of firefighters in real time. Matlab was used for simulation, and error sources and error sizes were estimated,which ensured the safety of firefighters and provided timely help and rescue in case of firefighters' distress. After simulation, it can be concluded that in the case of large signal-to-noise ratio, the positioning accuracy is high and the positioning effect is pretty well.

Allocation strategy of medical supplies during a public health emergency: a tripartite evolutionary game perspective

Ensuring the rational and orderly circulation of medical supplies during a public health emergency is crucial to quickly containing the further spread of the epidemic and restoring the order of rescue and treatment. However, due to the shortage of medical supplies, there are challenges to rationalizing the allocation of critical medical supplies among multiple parties with conflicting interests. In this paper, a tripartite evolutionary game model is constructed to study the allocation of medical supplies in the rescue environment of public health emergencies under conditions of incomplete information. The game’s players include Government-owned Nonprofit Organizations (GNPOs), hospitals, and the government. By analyzing the equilibrium of the tripartite evolutionary game, this paper makes an in-depth study on the optimal allocation strategy of medical supplies. The findings indicate that: (1) the hospital should reasonably increase its willingness to accept the allocation plan of medical supplies, which can help medical supplies allocate more scientifically. (2) The government should design a reasonable reward and punishment mechanism to ensure the rational and orderly circulation of medical supplies, which can reduce the interference of GNPOs and hospitals in the allocation process of medical supplies. (3) Higher authorities should strengthen the supervision of the government and the accountability for loose supervision. The findings of this research can guide the government in promoting better circulation of medical supplies during public health emergencies by formulating more reasonable allocation schemes of emergency medical supplies, as well as incentives and penalties. At the same time, for GNPOs with limited emergency medical supplies, the equal allocation of emergency supplies is not the optimal solution to improve the efficiency of emergency relief, and it is simpler to achieve the goal of maximizing social benefits by allocating limited emergency resources to the demand points that match the degree of urgency. For example, in Corona Virus Disease 2019, emergency medical supplies should be prioritized for allocation to government-designated fever hospitals that are have a greater need for medical supplies and greater treatment capacity.

Application of UAV in Fire Emergency Communication Support

Fire emergency communication is an important guarantee condition for the orderly and rapid development of fire emergency rescue work. However, the complexity of emergency rescue environment and the weakness of communication support force increase the difficulty of fire emergency communication support and affect the effect of communication support. Considering the importance and necessity of communication support in fire emergency rescue, as well as the gradual maturity of UAV technology, more and more fire emergency rescue work has introduced UAV technology, with the help of UAV to improve the support of emergency communication. This paper summarizes the practical application situation and advantages of UAV technology in fire emergency communication support, and elaborates the problems that need attention in the application of UAV in fire emergency communication support, so as to provide the corresponding reference for the application and development of UAV in fire emergency communication support.

Design a safe firefighting time (SFT) for major fire disaster emergency response

A major fire disaster is hazardous to both occupants trapped in the built environment and firefighters during the firefighting operation. Though various construction codes, technologies, and facilities have enhanced occupants’ evacuation in fire, insufficient effort is made to ensure a safe firefighting and rescue environment for firefighters, and their safety is not effectively guaranteed in the process of firefighting. To fill this gap, this work proposes a new concept of safe firefighting time (SFT) in fire safety design, combining the features of firefighting and evacuation behavior. By referring to the available and required safe egress time, ASFT (Available Safe Firefighting Time) and RSFT (Required Safe Firefighting Time) are defined with detailed calculation methods. As a demonstration, safe firefighting time including ASFT and RSFT is evaluated in a fire safety performance-based design of a tunnel. Apart from fire safety design, SFT could contributes to smart firefighting supported by emerging technologies. The framework for future fire safety design and the research needs in smart firefighting with SFT are discussed combining intelligent approaches such as IoT infrastructures and cloud services. In summary, this study introduces the safe firefighting time and application approaches in fire safety design that extends the current fire-safety design framework and lays a foundation for smart firefighting for engineers, firefighters and policymakers.

Implementation of RWP and Gauss Markov Mobility Model for Multi-UAV Networks in Search and Rescue Environment

Future generations of wireless networks are expected to heavily rely on unmanned aerial vehicles (UAVs). UAV networks have extraordinary features like high mobility, frequent topology change, tolerance to link failure, and extending the coverage area by adding external UAVs. UAV network provides several advantages for civilian, commercial, search and rescue applications. A realistic mobility model must be used to assess the dependability and effectiveness of UAV protocols and algorithms. In this research paper, the performance of the Gauss Markov (GM) and Random Waypoint (RWP) mobility models in multi-UAV networks for a search and rescue scenario is analyzed and evaluated. Additionally, the two mobility models GM and RWP are described in depth, together with the movement patterns they are related with. Furthermore, two-simulation scenarios conduct with help of an NS-3 simulator. The first scenario investigates the effect of UAV Speed by varying it from 10 to 50 m/s. the second scenario investigates the effect of the size of the transmitting packet by varying it from 64 to 1024 bytes. The performance of GM and RWP was compared based on packet delivery ratio (PDR), goodput, and latency metrics. Results indicate that the GM model provides the highest PDR and lowest latency in such high mobility environments.

Smart Black Box DVR System in IT-Based Vehicle Emergency Rescue Environment

In this paper, the driving habits and patterns are analyzed by automatically recognizing vehicle accidents and recording event data when dangerous situations occur, applying connected car service through IT technology. In addition, SBDS designs the highly scalable modeling that reproduces videos which are recorded before and after accidents. SBDS provides emergency rescue and traffic information services by receiving IoT sensor data connected to have an embedded system in the vehicle and notifying the accident location and video information to the control center, using wireless network service even when the vehicle is dormant. In addition, it is possible to implement a wireless e-Call service by interlocking ECU information and vehicle sensor data in case an emergency occurs.

The state of academic (un)freedom and scholar rescue programmes: a contemporary and critical overview

The attack on academic freedom has worsened in different parts of the world regardless of political context. Universities, academics and students have come under increasing attack and are subjected to censorship and violence, while academic programmes that have been categorised as ‘politically sensitive’ are cancelled or banished from the curriculum. Scholar rescue programmes remain the most important and enduring response to safeguarding and restoring the scholarly freedoms of academics whose intellectual rights have been threatened. However, few scholarly assessments of the state of the art in the scholar rescue environment are available. The present article is a critical review and meta-analysis of the current state of scholar rescue programmes, which have been established in response to the onslaught on academic freedom and freedom of academics. I describe current scholar rescue practice and raise critical issues that organisations in scholar rescue and mobility work must confront to meaningfully serve threatened academics around the world.

Obstacle Modeling and Structural Optimization of Four-Track Twin-Rocker Rescue Robot

In order to achieve the best obstacle surmounting performance of a mobile robot in the rescue environment, a four-track twin-rocker bionic rescue robot with an inner and outer concentric shaft was designed in this paper. From the viewpoint of dynamics, the motion process of the mass center of the robot when climbing steps forward and backward was studied. The maximum obstacle height of the robot was calculated. The relationship between the elevation angle of the car body, the swing angle of the rocker arm and the height of the steps was analyzed by simulation. The simulation results show that the maximum forward and reverse obstacle crossing heights were 92.99 mm and 155.82 mm, respectively. Obstacle climbing experiments of the designed robot prototype were carried out. It was found that the measured maximum height of the step was 95 mm, and the measured maximum height of the reverse obstacle was 165 mm. Finally, bionic particle swarm optimization was used to optimize the structural parameters of the rocker arm with an optimal length of 315.2 mm. The study of this paper can be referenced for the design and analysis of obstacle surmounting rescue robots with similar structures.

AvaLife-A New Multi-Disciplinary Approach Supported by Accident and Field Test Data to Optimize Survival Chances in Rescue and First Aid of Avalanche Patients.

Snow sports in the backcountry have seen a steep increase in popularity, and therefore preparedness for efficient companion and organized rescue is important. While technical rescue skills are widely taught, there is a lack of knowledge regarding first aid for avalanche patients. The stressful and time-critical situation for first responders requires a rule-based decision support tool. AvaLife has been designed from scratch, applying mathematical and statistical approaches including Monte Carlo simulations. New analysis of retrospective data and large prospective field test datasets were used to develop evidence-based algorithms exclusively for the avalanche rescue environment. AvaLife differs from other algorithms as it is not just a general-purpose CPR algorithm which has been slightly adapted for the avalanche patient. The sequence of actions, inclusion of the ≥150 cm burial depth triage criterion, advice to limit CPR duration for normothermic patients to 6 min in case of multiple burials and shortage of resources, criteria for using recovered subjects as a resource in the ongoing rescue, the adapted definition of “injuries incompatible with life”, reasoning behind the utmost importance of rescue breaths, as well as the updated BLS-iCPR algorithm make AvaLife useful in single and multiple burial rescue. AvaLife is available as a companion rescue basic life support (BLS) version for the recreational user and an advanced companion and organized rescue BLS version for guides, ski patrols and mountain rescuers. AvaLife allows seamless interoperability with advanced life support (ALS) qualified medical personnel arriving on site.

BIT-DMR: A Humanoid Dual-Arm Mobile Robot for Complex Rescue Operations

Using robots to assist or even replace rescuers for searching and rescuing has always been a research hotspot. Robots that can carry out dexterous operations at the scene are of great significance to reduce the life threat of rescue workers. Aiming at the characteristics of narrow space and frequent physical interaction in rescue scene, a dual-arm mobile robot BIT-DMR composed of humanoid upper body and tracked mobile platform is developed in this letter. The main work is as follows: a) A high-performance lightweight and heavy payload human-machine cooperative manipulator is developed, which has a slender shape and a large flexible workspace, improving the operation ability of the robot in complex rescue environment. b) A highly integrated tracked mobile platform is developed, which can change a variety of forms leading to a high trafficability in complex terrain. The flexibility of BIT-DMR to carry out rescue operation is verified by a series of experiments like payload testing, mobile platform performance, obstacle removing, door opening and casualty rescuing. This letter provides technical reserves for robots to assist or replace human beings to carry out rescue operations at the scene.

A Multi-Agent Control Architecture for a Rescue Robot

Cognitive architectures investigate the components and interactions neccessary for construction of an intelligent system. Despite much progress and theory, implementations of architectures are rare. This research presents a novel cognitive architecture grounded in the design of a control system for an autonomous rescue robot. Experiments are conducted in high-fidelity 3D simulation of a rescue environment based on NISTs RoboCup Rescue.

Visual victim detection and quadrotor-swarm coordination control in search and rescue environment

We propose a distributed victim-detection algorithm through visual information on quadrotors using convolutional neuronal networks (CNN) in a search and rescue environment. Describing the navigation algorithm, which allows quadrotors to avoid collisions. Secondly, when one quadrotor detects a possible victim, it causes its closest neighbors to disconnect from the main swarm and form a new sub-swarm around the victim, which validates the victim’s status. Thus, a formation control that permits to acquire information is performed based on the well-known rendezvous consensus algorithm. Finally, images are processed using CNN identifying potential victims in the area. Given the uncertainty of the victim detection measurement among quadrotors’ cameras in the image processing, estimation consensus (EC) and max-estimation consensus (M-EC) algorithms are proposed focusing on agreeing over the victim detection estimation. We illustrate that M-EC delivers better results than EC in scenarios with poor visibility and uncertainty produced by fire and smoke. The algorithm proves that distributed fashion can obtain a more accurate result in decision-making on whether or not there is a victim, showing robustness under uncertainties and wrong measurements in comparison when a single quadrotor performs the mission. The well-functioning of the algorithm is evaluated by carrying out a simulation using V-Rep.

Intelligent prediction of RBC demand in trauma patients using decision tree methods

BackgroundThe vital signs of trauma patients are complex and changeable, and the prediction of blood transfusion demand mainly depends on doctors’ experience and trauma scoring system; therefore, it cannot be accurately predicted. In this study, a machine learning decision tree algorithm [classification and regression tree (CRT) and eXtreme gradient boosting (XGBoost)] was proposed for the demand prediction of traumatic blood transfusion to provide technical support for doctors.MethodsA total of 1371 trauma patients who were diverted to the Emergency Department of the First Medical Center of Chinese PLA General Hospital from January 2014 to January 2018 were collected from an emergency trauma database. The vital signs, laboratory examination parameters and blood transfusion volume were used as variables, and the non-invasive parameters and all (non-invasive + invasive) parameters were used to construct an intelligent prediction model for red blood cell (RBC) demand by logistic regression (LR), CRT and XGBoost. The prediction accuracy of the model was compared with the area under the curve (AUC).ResultsFor non-invasive parameters, the LR method was the best, with an AUC of 0.72 [95% confidence interval (CI) 0.657–0.775], which was higher than the CRT (AUC 0.69, 95% CI 0.633–0.751) and the XGBoost (AUC 0.71, 95% CI 0.654–0.756, P < 0.05). The trauma location and shock index are important prediction parameters. For all the prediction parameters, XGBoost was the best, with an AUC of 0.94 (95% CI 0.893–0.981), which was higher than the LR (AUC 0.80, 95% CI 0.744–0.850) and the CRT (AUC 0.82, 95% CI 0.779–0.853, P < 0.05). Haematocrit (Hct) is an important prediction parameter.ConclusionsThe classification performance of the intelligent prediction model of red blood cell transfusion in trauma patients constructed by the decision tree algorithm is not inferior to that of the traditional LR method. It can be used as a technical support to assist doctors to make rapid and accurate blood transfusion decisions in emergency rescue environment, so as to improve the success rate of patient treatment.

Energy efficient emergency rescue scheme in wireless sensor networks

Internet of Things (IoT) plays an important role in various applications such as industrial control system, environmental monitoring, fire detection, smart home and much more. In today’s scenarios data transmission in emergency rescue is a challenging issue with respect of energy efficient. In this paper, an Energy Efficient Emergency Rescue Scheme (EEERS) is proposed and evaluated which transfers reliable data with high speed and minimum delay in the field of IoT. The simulation is done on MATLAB on different size of network 100–500 sensor nodes. Proposed routing scheme EEERS is compared with existing routing protocols SAR and SPEED on different parameters namely end-to-end delay, throughput, energy consumption, packet loss and packet delivery ratio. Simulation results show that EEERS minimizes end-to-end delay 30–35%, increases throughput 40–42%, reduces energy consumption 50–55%, minimizes packet loss 60–65% and enhances packet delivery ratio 36–40% in emergency rescue environment of IoT. EEERS works on large size of network and prolongs network lifetime.

Distributed Particle Swarm Optimization for Multi-Robot System in Search and Rescue Operations

Abstract In this paper, we tackle the problem of finding victims in a search and rescue environment, taking into account that the terrain in a disaster is complex and dangerous for rescuers to traverse. Furthermore, time is crucial when saving lives from a disaster considering all of these challenges, a solution is proposed by using a cooperative robotics team, which speeds up the process of searching for survivors and avoids risking additional lives. This article focuses on the navigation of a swarm of robots that can avoid collisions with obstacles that can be either static or dynamic, and locate victims. The method we employed to navigate in the environment is based on a DPSO Distributed Particle Swarm Optimization where each particle swarm represents a single robot. We show the interaction between swarms, and we make use of artificial potential functions for collision avoidance and for attraction to victims. We perform several simulation experiments to test the navigation algorithm, avoiding obstacles, and finding victims. These experiments are carried out in different environments, varying the number of victims and also the size and number of obstacles. The results show how the algorithm allows the group to avoid obstacles and find possible victims, all experiments are implemented using a combination of Python with V-Rep.

2D Lidar-Based SLAM and Path Planning for Indoor Rescue Using Mobile Robots

As the basic system of the rescue robot, the SLAM system largely determines whether the rescue robot can complete the rescue mission. Although the current 2D Lidar-based SLAM algorithm, including its application in indoor rescue environment, has achieved much success, the evaluation of SLAM algorithms combined with path planning for indoor rescue has rarely been studied. This paper studies mapping and path planning for mobile robots in an indoor rescue environment. Combined with path planning algorithm, this paper analyzes the applicability of three SLAM algorithms (GMapping algorithm, Hector-SLAM algorithm, and Cartographer algorithm) in indoor rescue environment. Real-time path planning is studied to test the mapping results. To balance path optimality and obstacle avoidance, A ∗ algorithm is used for global path planning, and DWA algorithm is adopted for local path planning. Experimental results validate the SLAM and path planning algorithms in simulated, emulated, and competition rescue environments, respectively. Finally, the results of this paper may facilitate researchers quickly and clearly selecting appropriate algorithms to build SLAM systems according to their own demands.

Directions for Sanitation-Based Environmental Structuring using AHP for the Prevention of Diarrhea in Pagar Alam City - Indonesia

Pagar Alam City is one of the cities in South Sumatera province which has a high number of people who are quite and fluctuating diarrhea caused by poor environmental sanitation. The research aims to produce a direction for the arrangement of a sanitary-based environment for diarrhea prevention in Pagar Alam City. This research is a qualitative study with an analysis of Analytical Hierarchy Process (AHP) which emphasizes comparative judgment based on data and literature study. From interviews and literature studies, there are three important criteria for structuring a sanitation-based environment, namely society, environment, and infrastructure. From these criteria, there are eight alternative policies related to the arrangement of sanitation based environment for diarrhea prevention, with priority as follows: Environment sanitation Program based on a case study, strengthening community empowerment facilitator, improving coordination and cooperation among related agencies, rescue environment through local wisdom, improvement of infrastructure access and sanitation facilities, forming sanitation clinics incorporated in Public health center, institutional strengthening and drafting strict rules, and Monitoring and evaluation of sanitation programs.

A Stackelberg Signaling Game for Human-UAV Collaboration in a Search-and-Rescue Context

Search-and-rescue (SAR) operations are challenging in the absence of a medium of communication between the rescuers and the rescuee. In this work, we model a particular rescue scenario as a modified asymmetric rendezvous game, where limited communication capabilities are present between the two players. This scenario can be modelled as a co-operative Stackelberg game, where the rescuer acts as a leader in signaling his intent to the rescuee. We present an efficient approach to obtain the optimal signaling policy, as well as its robust counterpart, when the topology of the rescue environment is unknown.

A distributed approach for road clearance with multi-robot in urban search and rescue environment

In urban search and rescue domains, robots explore the affected terrain to search and assist disaster victims. RoboCup Rescue simulation provides a platform for disaster management where heterogeneous field agents (fire-brigade agent, ambulance agent, and police force agent) collaborate to manage a mimicked calamity situation. The role of police force agents is crucial, as they clear the blocked roads to allow other agents to perform their tasks. In this paper we suggest a distributed multi-robot coordination approach for clearing a road blocked with heavy obstacles. The proposed framework is implemented and simulated in ARGoS, a multi-robot simulator. The experimental results show the validity and satisfactory performance of the proposed approach.