Development of Drone-Based Human Rescue Strategies Using Virtual Reality (original) (raw)

Challenges of Using Drones and Virtual/Augmented Reality for Disaster Risk Management

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Natural and man-made disasters can severely destroy environments and they make conditions difficult to access the affected areas and to provide assistance. The conditions on-site could be dangerous and unstable and there is an increasing need for life-saving decisions to be taken quickly to minimize evolving hazards and to start relief operations. The accurate and timely data gathering is important to produce a full information about the calamity. In recent disasters drones are deployed extensively to help find people quickly, provide imminent reliable imagery and data by flying closer to the ground. They are used to create disaster maps and assess damage after earthquakes, landslides, hurricanes, etc. The fast transition into the digital age makes new technologies become available to enhance and expand drone capabilities in disaster risk management, such as Virtual Reality (VR) and Augmented Reality (AR). The paper tries to analyze how VR can be used to plan operations in a controlled manner before deadly events strike by creating disaster simulations in digital environments, enabling the rescuers to practice as many times as necessary until they are able to achieve mastery of the life-saving techniques. The paper also analyzes how drones, equipped with cameras, devices and AR, can be used to create different types of maps that help rescuers locate critical spots. These can also facilitate the location of people in need, and can survey constructions to find critical damages.

VRescuer: A Virtual Reality Application for Disaster Response Training

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), 2019

With the advancement of modern technologies, Virtual Reality plays an essential role for training rescuers, particularly for disaster savers employing simulation training. By wholly immersed in the virtual environment, rescuers are capable of practicing the required skills without being threatened of their lives before experiencing the real world situation. This paper presented a work-in-progress Virtual Reality application called VRescuer to help trainees get used to various disaster circumstances. A scenario of a city was created with an ambulance rescuer and several rescuees in the scene. The intelligent ambulance rescuer was introduced as a rescuer/guider to automatically search and find the optimal paths for saving all rescuees. The trainee can interfere in the rescuing process by placing obstacles or adding more rescuees along the ways which cause the rescue agent to re-route the paths. The VRescuer was implemented in Unity3D with an Oculus Rift device, and it was assessed by ...

IRJET- Design and Development of smart UAV assistance for Firefighters

IRJET, 2021

There is an increasing need in the world today for supervision to ensure people's safety and security. The use of drones during structure fires, search and rescue operations in fire services shows great benefits. Artificial Intelligence (AI) is the technology to come in action here. AI is a futuristic technology that will be a powerful tool to save lives and help us with disruptive nature. It is a strong concept to save lives and help in disaster relief operations and humanitarian aid activities. This dissertation concentrates on the idea of building an Unmanned Aerial Vehicle (UAV) to help firemen estimate people stuck by fire using AI and image processing. This innovation can help the task force to plan relief efforts and to help the needy to be rescued. To achieve our desired aerial surveillance system, we shall incorporate these technologies.

REVOLUTIONIZING EMERGENCY RESPONSE: DRONE-BASED IMAGE RECOGNITION FOR REMOTE RESCUES

IAEME PUBLICATION, 2024

This article presents an innovative drone-based image recognition system to revolutionize search and rescue operations in remote and challenging environments. By integrating advanced unmanned aerial vehicles (UAVs) with cutting-edge artificial intelligence and computer vision technologies, the proposed system aims to significantly enhance the speed and efficiency of locating and assisting individuals in distress. The article outlines the system's core components, including a diverse drone fleet, sophisticated image recognition algorithms, and a centralized ground control station. It also details the operational workflow, from initial distress signal detection to the final deployment of human rescue teams. Additionally, the article addresses key technical challenges such as false positives, adverse weather conditions, and limited battery life, proposing innovative solutions to overcome these obstacles. This system represents a significant advancement in emergency response capabilities, potentially saving countless lives in critical situations where time is of the essence.

The Next Generation of Human-Drone Partnerships: Co-Designing an Emergency Response System

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 2020

The use of semi-autonomous Unmanned Aerial Vehicles (UAV) to support emergency response scenarios, such as fire surveillance and search and rescue, offers the potential for huge societal benefits. However, designing an effective solution in this complex domain represents a "wicked design" problem, requiring a careful balance between trade-offs associated with drone autonomy versus human control, mission functionality versus safety, and the diverse needs of different stakeholders. This paper focuses on designing for situational awareness (SA) using a scenario-driven, participatory design process. We developed SA cards describing six common design-problems, known as SA demons, and three new demons of importance to our domain. We then used these SA cards to equip domain experts with SA knowledge so that they could more fully engage in the design process. We designed a potentially reusable solution for achieving SA in multi-stakeholder, multi-UAV, emergency response applications.

A real-time field experiment on search and rescue operations assisted by unmanned aerial vehicles

Journal of Field Robotics, 2018

This paper reports on the performance of a novel system for supporting search and rescue activities, known as SARUAV (search and rescue unmanned aerial vehicle), in a field experiment during which a real-world search scenario was simulated. The experiment took place on March 2-3, 2017, at two sites located in southwestern Poland. Three groups acted in the experiment: (1) SARUAV and unmanned aerial vehicle (UAV) operators, (2) ground searchers, and (3) participants who simulated being lost. In the uncomplicated topography without snow cover, the system identified the lost persons, and ground searchers found them 31 min after the SARUAV report had been disseminated. In the mountainous area covered with snow, one person was found within 9 min after searchers received the SARUAV report; however, the other two persons were not identified by SARUAV. The field experiment served as a proof of concept of the SARUAV system, confirmed its potential in person identification studies, and helped to identify numerous scientific and technical problems that need to be solved to develop a mature version of the system. K E Y W O R D S lost person, nested k-means, ring model, target detection, unmanned aerial vehicle FlyTech UAV, Polish drone manufacturer, personal communication, March 13, 2017), which increases chances for an individual to survive.

DRONEVR: A virtual reality simulator for DroneOperator

2019

In recent years, Unmanned Aerial Vehicle (UAV) has been used extensively in various applications from entertainment, virtual tourism to construction, mining, agriculture. Navigation, path planning, and image acquisition are the main tasks in administering these aerial devices in accordance with real-time object tracking for affordable aerial vehicles. Aircraft crash is one of the most critical issues due to the uncontrolled environment and signal loss that cause the aerial vehicle to hit the buildings on its returning mode. Furthermore, real-time image processing, such as object tracking, has not yet been exploited for a low-cost aerial vehicle. This paper proposes a prototype embedded in a Web-based application called DroneVR to mitigate the aforementioned issues. The virtual reality environment was reconstructed based on the real-world fly data (OpenStreetMap) in which path planning and navigation were carried out. Gaussian Mixture Model was used to extract foreground and detect a moving object, Kalman Filter method was then applied to predict and keep track of object's motion. Perceived ease of use was investigated with a small sample size users to improve the simulator.

iVER: Intelligent Unmanned Aerial Vehicle to Assist Flood Search and Rescue

2017

Flood is a natural disaster that can disrupt large area for a long period of time. Many people are affected by it and it can cause major damage towards society and economy. The main cause of fatality during flood is drowning. This may be due to difficulties to find flood victims in short period of time. This research introduces intelligent Vehicle for Emergency Response (iVER), an unmanned aerial vehicle that can assist search and rescue during flood by providing live-feed of bird-eye-view videos of the surrounding area to the rescuers. iVER’s design, materials and features are all designed to be easy to handle by rescuers during emergency and under harsh weather. iVER’s features such easy take-off, auto-landing and fully autonomous flight optimisations are also discussed in this paper.

AI Enabled MED Drone for Healthcare Application

IJIRAE:: AM Publications,India, 2024

The project proposes the development of an AI-enabled MedDrone for medication delivery, introducing an innovative and efficient solution to enhance healthcare logistics. The MedDrone, equipped with artificial intelligence capabilities, aims to revolutionize the process of medication delivery by leveraging autonomous aerial technology. The system integrates advanced algorithms to optimize route planning, ensuring timely and accurate delivery of medications to designated locations. The AI component enables the drone to adapt to real-time variables such as weather conditions and traffic, enhancing the reliability and responsiveness of the delivery process. This project addresses the challenges of traditional medication distribution, offering a futuristic and intelligent approach to healthcare logistics through the deployment of AI-enabled autonomous drones for efficient and timely medication delivery. The proposed system integrates AI algorithms for real-time route optimization, obstacle avoidance, and decision-making, enabling the drone to autonomously navigate complex environments and deliver essential medical supplies such as first aid kits, defibrillators, and medications to the point of need. Through the utilization of machine learning techniques, the drone continuously learns from its interactions with the environment, enhancing its adaptability and performance over time. Additionally, the system incorporates advanced communication technologies to enable seamless coordination with emergency responders and healthcare professionals, ensuring timely delivery and proper utilization of resources. The efficacy of the proposed AI based medical drone system is demonstrated through simulations and real-world trials, highlighting its potential to revolutionize emergency response efforts and improve healthcare accessibility, particularly in challenging or resource constrained environments.