Trapped Victims Research Articles

A method to accelerate the rescue of fire-stricken victims

For individuals trapped in a fire, early detection can significantly increase their chances of survival. Presently, firefighters employ a systematic search method along the walls, ensuring a comprehensive and thorough exploration of the environment to prevent missing any trapped victims. However, this approach has its drawbacks, such as time wastage in areas or rooms without victims. The goal of this study is to propose a search method that can expedite the discovery of trapped victims. Our method relies primarily on prior knowledge, crowd information and the temperature within the fire scene, utilizing fuzzy logic to calculate the probability of the presence and survival of victims in each distinct space. The resulting search sequence not only accelerates victim discovery but also safeguards firefighters from unnecessary risks. We conducted various simulation experiments to validate our approach. In comparison to the sequential search method currently employed by firefighters, the experimental results indicate that our method reduces the time to locate trapped victims by 25 %. Compared to other path planning algorithms based on approximate optimization, our method offers a shorter computation time, making it suitable for integration into fire rescue systems to provide real-time assistance.

RUDE-AL: Roped UGV Deployment Algorithm of an MCDPR for Sinkhole Exploration.

The presence of sinkholes has been widely studied due to their potential risk to infrastructure and to the lives of inhabitants and rescuers in urban disaster areas, which is generally addressed in geotechnics and geophysics. In recent years, robotics has gained importance for the inspection and assessment of areas of potential risk for sinkhole formation, as well as for environmental exploration and post-disaster assistance. From the mobile robotics approach, this paper proposes RUDE-AL (Roped UGV DEployment ALgorithm), a methodology for deploying a Mobile Cable-Driven Parallel Robot (MCDPR) composed of four mobile robots and a cable-driven parallel robot (CDPR) for sinkhole exploration tasks and assistance to potential trapped victims. The deployment of the fleet is organized with node-edge formation during the mission's first stage, positioning itself around the area of interest and acting as anchors for the subsequent release of the cable robot. One of the relevant issues considered in this work is the selection of target points for mobile robots (anchors) considering the constraints of a roped fleet, avoiding the collision of the cables with positive obstacles through a fitting function that maximizes the area covered of the zone to explore and minimizes the cost of the route distance performed by the fleet using genetic algorithms, generating feasible target routes for each mobile robot with a configurable balance between the parameters of the fitness function. The main results show a robust method whose adjustment function is affected by the number of positive obstacles near the area of interest and the shape characteristics of the sinkhole.

Enhancing Safety and Efficiency in Firefighting Operations via Deep Learning and Temperature Forecasting Modeling in Autonomous Unit

Firefighters face numerous challenges when entering burning structures to rescue trapped victims, assess the conditions of a residential structure, and extinguish the fire as quickly as possible. These challenges include extreme temperatures, smoke, toxic gases, explosions, and falling objects, which can hinder their efficiency and pose risks to their safety. Accurate information and data about the burning site can help firefighters make informed decisions about their duties and determine when it is safe to enter and evacuate, reducing the likelihood of casualties. This research presents unsupervised deep learning (DL) to classify the danger levels at a burning site and an autoregressive integrated moving average (ARIMA) prediction model to forecast temperature changes using the extrapolation of a random forest regressor. The DL classifier algorithms provide the chief firefighter with an awareness of the danger levels in the burning compartment. The prediction models forecast the rise in temperature from a height ranging from 0.6 m to 2.6 m and the changes in temperature over time at an altitude of 2.6 m. Predicting the temperature at this altitude is critical as the temperature increases faster with height, and elevated temperatures can weaken the building’s structural material. We also investigated a new classification method using an unsupervised DL autoencoder artificial neural network (AE-ANN). The prediction data analytical approach included using the autoregressive integrated moving average (ARIMA) with random forest regression implementation. The proposed AE-ANN model, with an accuracy score of 0.869, did not perform as well compared to previous work, with an accuracy of 0.989, at achieving high accuracy scores for the classification task using the same dataset. However, the random forest regressor and our ARIMA models are analyzed and evaluated in this work, while other research has not utilized this dataset, even though it is open-sourced. However, the ARIMA model demonstrated remarkable predictions of the trends of temperature changes in a burning site. The proposed research aims to classify fire sites into dangerous levels and predict temperature progression using deep learning and predictive modeling techniques. This research’s main contribution is using a random forest regressor and autoregressive integrated moving average models to predict temperature trends in burning sites. This research demonstrates the potential of using deep learning and predictive modeling to enhance firefighter safety and decision-making processes.

Literasi Digital Untuk Melindungi Masyarakat Dari Kejahatan Siber

The digital transformation process uncovers evil. Migration from a manual pattern to an online-based system is only a condition that forces people to enter this service system. Without preparation and complete information, suddenly people are brought into a completely different atmosphere from the period they have experienced so far. Forced compulsion finally colored the journey to this new era coded 0 and 1. 
 Various communication events, especially with regard to digital crime cases, one of which occurred by taking advantage of public ignorance. If this new era is considered a necessity, total preparation is needed. Not on the issue of infrastructure, but also mental spiritual and knowledge of the community. Responding to this problem, this research was conducted with the aim of knowing cyber crime in an atmosphere of a digitally illiterate society. Using a qualitative descriptive method, observed data sources from online media are analyzed to find clear relationships that cause the emergence of cybercrime. 
 The results of the research show that people's lack of understanding of digital systems allows many victims to fall and fall into the traps set up by criminals. Therefore digital literacy activities must be carried out massively so that knowledge about digitalization does not trap victims. Digital literacy activities must be promoted as much as possible to touch all levels of society. This activity can be initiated by the government, private bodies, or community organizations.

DIGITAL CELLULAR TECHNOLOGIES AND GNSS WITH UAV IN SAR MISSIONS FOR PUBLIC PROTECTION AND DISASTER RELIEF SERVICES


 
 
 The objective of this paper is to analyze Digital Cellular Technologies (DCT) and European Global Navigation Satellite System (EGNSS)-Galileo with Unmanned Aerial Vehicles (UAV) in Search and Rescue (SAR) missions dedicated for Public Protection and Disaster Relief (PPDR) services. Using desk research methodology authors will evaluate current activities being done in SAR operations in PPDR services, such as police, firefighters, military based on the new technology solutions for SAR operations that support those forces to find trapped victims or fugitives quickly and effectively, thus, improving their time-to-reaction. In conclusion authors stated that the DCT mobile SAR system based on Galileo presents the most sophisticated technology and features that go beyond the state of the art taking into consideration operation safety, reliability and commercial costs in comparison to other systems.
 
 

Using Smartphones to Locate Trapped Victims in Disasters.

Large and unaccounted numbers of victims in disasters, events, or fires are often trapped in buildings or debris, and must be located and rescued as soon as possible. This study transforms smartphones into indoor locating tools without extra modification or complicated program installation, considering smartphones are likely to be carried when disasters strike. The study creates a system that converts smartphones into a lifesaving tool for trapped victims and rescuers. This study employs the Bluetooth beacon in smartphones to send signals using its low power consumption feature. The signal could continue transmitting for rescuers to locate trapped victims for longer. Rescuers could use the Bluetooth function on a regular notebook computer to search such signals without any hardware implementation or modification, allowing them to locate and determine the position of many trapped victims simultaneously. Implementing this system will decrease the search and rescue team’s need to enter unsafe areas and increase their rescue speed, a critical factor for the survival of trapped victims. Furthermore, when disasters strike, the smartphone calling function might not work, and the trapped victim might be too weak to call for help. Thus, autoreply messages from victims’ smartphones could help them be located within a 2-m error, even if covered by fallen debris such as wood piles or tiles. This effort will increase the chance of finding trapped victims within the golden rescue hours and reduce the exposure time of search and rescue teams in unsafe environments.

Integration of smart watch and geographic information system (GIS) to identify post-earthquake critical rescue area part. II. Analytical evaluation of the system

The efficient allocation of resources in the aftermath of an earthquake in an affected area largely depends on the identification of post-earthquake critical rescue area. This paper is the second part of the companion paper on the integration of smart watch and geographic information system (GIS) to identify post-earthquake critical rescue area. In the first paper, we proposed a new system through an application installed on a wearable device to dissipate the information of trapped victims called the Earthquake Emergency Micro Response System (EEMRS) Hossain et al. (2020) [27]. In the current paper an analytical model is developed to evaluate the effectiveness of it in the search and rescue (SAR) operations. The information dissemination formulation is postulated through observations and interactions with experts. The process of local first responders' immediate post-earthquake activities from dispatch to extricating the trapped victims at the affected area is carefully calibrated with the firefighter activities recorded in the aftermath of Kobe earthquake. Evaluation using the developed analytical method imply that the increase in use of smart watches in earthquake prone areas can significantly increase the extrication efficiency of firefighters. In addition, this proposed model can be used by emergency managers to know the robustness of their post-earthquake initial situation assessment techniques.

Integration of smart watch and Geographic Information System (GIS) to identify post-earthquake critical rescue area part. I. Development of the system

In this research, a new system is developed to aid the existing emergency response practices after a massive earthquake, hereafter called the Earthquake Emergency Micro Response System (EEMRS). This system can observe the post-earthquake situations by integrating smart watch data using exposed population with Geographic Information System (GIS). A smart watch is a potential tool to dissipate the information of the location and health condition of a potential victim. A methodology is developed to identify trapped victims and critical rescue area using the data dissipated by smart watches of potential victims and exposed elements. The developed method is capable to capture the victims and rescue the operations by identifying the critical rescue area in the shortest possible time by tracking victims' heart rate and movement. Medical team expert's opinions were used to evaluate the method and increase the effeciency of system, and to validate the model a hypothetical earthquake scenario is developed to emphasize and analyze the immediate situation. The aim of the developed system is to enhance efficiency, speed and proper location tracking to enable more victims to be rescued in an earthquake situation.

Love Scam di Selangor: Satu Penerokaan terhadap Modus Operandi Jenayah Siber ke atas Wanita Profesional

Love Scam is a cyber or commercial crime targeting women, especially professional women’s who have lost millions of ringgit in Malaysia. This study explores the factor of victim involvement and modus operandi used by the scammer. The interviews were conducted at the District Police Headquarters (IPPD) in Selangor. A total of five love scam victims were interviewed, with the assistance of police officers dealing with commercial crime cases. The findings show that prominent factors identified are the perpetrators sweet talk, socializing, easy internet access and self pressure among victims. The modus operandi often used by the perpetrators to trap victims is through fraud profile picture in social media, fake sweet promises, and packaged delivery and posing as representatives of tax agencies.

3D reconstruction of disaster scenes for urban search and rescue

Natural and man-made disasters that may take place due to a catastrophic incident (e.g., earthquake, explosion, terrorist attack) often result in trapped humans under rubble piles. In such emergency response situations, Urban Search and Rescue (USaR) teams have to make quick decisions under stress in order to determine the location of possible trapped victims. Fast 3D modelling of fully or partially collapsed buildings using images from Unmanned Aerial Vehicles (UAVs) can considerably help USaR efforts, thus improving disaster response and increasing survival rates. The a-priori establishment of a proper workflow for fast and reliable image-based 3D modelling and the a priori determination of the parameters that have to be set in each step of the photogrammetric pipeline are critical aspects that ensure the readiness in an emergency response situation. This paper evaluates powerful commercial and open-source software solutions for the 3D reconstruction of disaster scenes for rapid response situations. The software packages are tested using UAV datasets of a real earthquake scene. A thorough analysis on the parameters of the various modelling steps that may lead to desired results for USaR tasks is made and indicative processing chains are proposed, taking into account the restriction of time. Furthermore, some weaknesses of the data acquisition process that have been detected by performing the experiments are outlined and some improvements and additions are proposed, including an initial preprocessing of the images using a graph-based approach.

HANTU PEREMPUAN JAWA DALAM ALAMING LELEMBUT SEBAGAI REPRESENTASI FEMME FATALE

This research entitled “The Javanese Female Ghost in “Panjebar Semangat” as a Representation of Femme Fatale”aims to show the feminist value in Javanese horror stories with female ghost as a villain and men as most of their victims. This research uses feminism as a main approach and femme fatale theory as the specific approach theory. This research shows that there are three kinds of of female ghost, they are female ghosts who experienced a miserable life before her death, sensual women and women whose background is not known. For the three kinds of women it can be revealed the causes of the female spirits to become evil spirits, the modes of female ghosts to ensnare and trap victims, the female ghost‟s harmful effects to men, and the solutions as the anti-climac in the story

Hantu Perempuan Jawa dalam Alaming Lelembut Sebagai Representasi Femme Fatale

This study entitled “The Javanese Female Ghost in „Alaming Lelembut‟ as a Representation of Femme Fatale”aims to show the feminist value in Javanese horror stories with female ghost as a villain and men as most of their victims. This study uses feminism as a main approach and femme fatale theory as the specific approach theory. This study shows that there are three kinds of of female ghost, they are female ghosts who experienced a miserable life before her death, sensual women and women whose background is not known. For the three kinds of women it can be revealed the causes of the female spirits to become evil spirits, the modes of female ghosts to ensnare and trap victims, the female ghost‟s harmful effects to men, and the solutions as the anti-climac in the story.

CURBING THE MENACE OF HUMAN TRAFFICKING IN NIGERIAN COMMUNITIES

This paper examined the menace of human trafficking in the Nigerian Communities with emphasis on two local Government areas, one in Ekiti and one in Oyo State. Three research questions and three hypotheses were formulated to guide the study. The study was a descriptive survey research design and the population consisted of all the wards in the two chosen local government areas in Ekiti and Oyo States. Stratified random sampling technique was used to collect data rated on a four point Likert scale and on the items related to the study. The instrument was tested for reliability using Pearson’s Product Moment Correlation coefficient which yielded an index of 0.79 which was adjudged good enough for measuring the consistency of the items. Mean and Standard Deviation were used to answer the research questions while t-test was used to test the hypotheses at 0.05 level of significance. The study revealed that people both, young ,men and women are victims of human trafficking, it also revealed that poverty, greed and materialism are the main causes for falling victim of human trafficking. It was also found that traffickers use violence, threat, deception and debt bondage to trap victims. It was then recommended that community education should be embarked upon to make people aware of the menace of human trafficking, job opportunities should be created for the Nigerian youth and laws should be effectively enforced on human traffickers while rehabilitaive services should be adequately provided for the victims..

An UWB Radar Signal Processing Platform for Real- Time Human breathing Feature Extraction

Background/Objectives: To evacuate trapped victims in complex environment with the help of UWB to detect the victim whether injured or not even before evacuation. Methods/Statistical Analysis: UWB system was used for sensing the breathing activity. In this process, the primary issue is the definition of design constraints about the signal processing waveform to transmit, correctly for the concerned algorithms for retrieving the breathing frequency and waveform precisely even in worst environment noise. Findings: The observation made from this study showed that more bitwise linear characteristic produced by the captured radar breathing signals than sinusoidal characteristics. Applications/ Improvements: The proposed system helps to find the status of the victim whether dead or alive; healthy or injured

Looking ahead: What’s on the horizon for drones?

As researchers envisage new ways to use drones as flying laboratories, others are tinkering with their robotic insides, trying to make them smaller, faster, and safer. Many drone engineers are intent on designing flying robots to be more autonomous so that they can perform tasks without a pilot. Imagine, for example, drones capable of quickly mapping collapsed buildings to help search-and-rescue personnel find trapped victims or identify looming threats such as a fire or gas leak, says Vijay Kumar, who is developing this technology at the University of Pennsylvania. Others are working to improve communication between drones so that swarms of these flying machines can accomplish tasks that a single unmanned aerial vehicle could not achieve alone. Researchers could, for instance, deploy a flock of flying sensors to track the edges of a suspicious airborne plume spreading across the sky in real time, says Kam K. Leang, director of the

A new approach to road accident rescue

ABSTRACTObjective: This article develops and validates a new methodology and tool for rescue assistance in traffic accidents, with the aim of improving its efficiency and safety in the evacuation of people, reducing the number of victims in road accidents.Method: Different tests supported by professionals and experts have been designed under different circumstances and with different categories of damaged vehicles coming from real accidents and simulated trapped victims in order to calibrate and refine the proposed methodology and tool.Results: To validate this new approach, a tool called App_Rescue has been developed. This tool is based on the use of a computer system that allows an efficient access to the technical information of the vehicle and sanitary information of the common passengers. The time spent during rescue using the standard protocol and the proposed method was compared.Conclusion: This rescue assistance system allows us to make vital information accessible in posttrauma care services, improving the effectiveness of interventions by the emergency services, reducing the rescue time and therefore minimizing the consequences involved and the number of victims. This could often mean saving lives. In the different simulated rescue operations, the rescue time has been reduced an average of 14%.

An Adaptive-MSSA-Based Algorithm for Detection of Trapped Victims Using UWB Radar

Postdisaster search and rescue is an important application of ultrawideband (UWB) radar systems, which mainly detect trapped victims by their respiratory-motion response. The development of a respiratory-motion detection (RMD) algorithm that can eliminate nonstationary clutter and noise is a challenging task for the application. A new algorithm is proposed to deal with the task in this letter. It uses the multichannel singular spectrum analysis (MSSA) technique to reconstruct the respiratory-motion response detected by a UWB radar. During the reconstruction, the periodicity and range interrelation characteristics of the response are exploited to adaptively identify signal subspaces. The performance of the algorithm is verified both by simulated and real data. The results show its improved performance over the reference algorithms, e.g., a singular-value-decomposition-based algorithm. The adaptive-MSSA-based RMD algorithm has great promise not only in practical use but also for future research of UWB-radar-based human being remote sensing.

Designing an Infrastructure by RFID Based Hybrid Technology Smart Wristband (HTSW) to enhance the Quick Rescue Operation in Industrial Accident

Rescue operation plan playing a vital rule to saving maximum number of life in the time of natural or manmade accident in Industry. Because of high density of labour in industry, possible fatality is increasing day by day. Around 11,000 workers die each year in industrial accidents in Bangladesh. In the last few years, the fastest growing industry of Bangladesh, garments sector has witnessed many industrial accidents specially factory fires and building collapse where many people died and wounded. However, fire service and civil defence has no modern technology to face this kind of big disaster in industry. This paper, firstly discuss about recent industrial disaster in Bangladesh specially garments sector and try to find out the obstacles of quick rescue operation after a disaster occurs. It is important to know how many people are present in a damaged building or structure that needs to evacuate. Radio-frequency identification (RFID) technology is a wireless Automatic Identification and Data Capture (AIDC) technology and could be use in the immediate or aftermath of major disasters. This paper proposed, an infrastructure and a wristband model named “Hybrid Technology Smart Wristband (HTSW)” where RFID, RF-transceiver, Microcontroller and health sense technologies are integrated. In normal condition, HTSW will help the employee management system and in disaster situation, it will enhance the quick rescue operation by identifying the approximate location of dead and live injured person, making plan for transferring injured and trapped victims. In the time of regular and disaster situation, the operation procedures of proposed HTSW infrastructure have explained here.

Characterization and Identification of IR-UWB Respiratory-Motion Response of Trapped Victims

Impulse-radio ultrawideband (IR-UWB) radar is a popular research topic in the field of post-earthquake search and rescue. By lowering center frequency, it can penetrate through earthquake rubble to detect trapped victims mainly by identifying their respiratory-motion response. Thus, low-center-frequency IR-UWB respiratory-motion response is characterized for the first time in this paper. On this basis, a novel constant false alarm rate (CFAR) algorithm that automatically identifies the response is developed. The IR-UWB respiratory-motion response has range extension and interrelation characteristics. With these characteristics, the algorithm can effectively improve the estimation accuracy of clutter energy in CFAR detection. The characteristics and the algorithm performance are verified by experiment results, which show not only great promise in practice but also significance for future research of IR-UWB radar for detection of trapped victims.

Automatic Detection of Multiple Trapped Victims by Ultra-Wideband Radar

Via analyzing the characteristics of life sign, a novel method is proposed to detect multiple trapped victims by ultra-wideband radar in this letter. The signal-to-noise and clutter ratio (SNCR) is greatly improved. The non-static clutter can be removed effectively. The number, range position and respiratory frequency of life signs can be detected automatically and accurately in low SNCR environment. By using experiment and numerical simulation, the good performance of the new method is proved.