Rescuing system design

There are many different technologies and equipment to search for objects underground today including mine ore, water, mineral or oil, but almost none of those technologies and equipment are applied to searching for people. This research will help to define what kinds of detecting methods exist, and what kind of technologies could be possibly applied for detecting human beings underground. ... The primary goal is to develop a new system for rescuing people under special circumstances such as building collapses, earthquakes, and being trapped underground (e.g., mine shaft collapses). There are many different technologies that could be applied to these situations. However, many of these technologies and devices are not appropriate for these sensitive circumstances. The most important process through this thesis is to find the best and most accurate technologies for detecting and locating victims underground, and to define the most efficient system to save as many lives as possible. This thesis proposes and suggests the best way to rescue trapped people underground. It will solve the problems we have faced for a long time, and help rescuers to protect victims\u27 lives as well as their own

SpotMe Emergency Location Service

This document delves into our disaster relief application that allows people who are helpless due to a natural disaster to find a way out and get help. The purpose of this document is to explain how the application works, but more specifically the design of the application, use cases, and conceptual models. Starting with a brief introduction, this paper will dive into the necessary requirements needed to build an application at this scale while presenting several use cases. To help the reader understand the application at a finer detail, activity diagrams will be shown along with models. Lastly, the document will cover what technologies will need to be used as well as a test plan and risk analysis

Decentralised Coordination in RoboCup Rescue

Emergency responders are faced with a number of significant challenges when managing major disasters. First, the number of rescue tasks posed is usually larger than the number of responders (or agents) and the resources available to them. Second, each task is likely to require a different level of effort in order to be completed by its deadline. Third, new tasks may continually appear or disappear from the environment, thus requiring the responders to quickly recompute their allocation of resources. Fourth, forming teams or coalitions of multiple agents from different agencies is vital since no single agency will have all the resources needed to save victims, unblock roads, and extinguish the ?res which might erupt in the disaster space. Given this, coalitions have to be efficiently selected and scheduled to work across the disaster space so as to maximise the number of lives and the portion of the infrastructure saved. In particular, it is important that the selection of such coalitions should be performed in a decentralised fashion in order to avoid a single point of failure in the system. Moreover, it is critical that responders communicate only locally given they are likely to have limited battery power or minimal access to long range communication devices. Against this background, we provide a novel decentralised solution to the coalition formation process that pervades disaster management. More specifically, we model the emergency management scenario defined in the RoboCup Rescue disaster simulation platform as a Coalition Formation with Spatial and Temporal constraints (CFST) problem where agents form coalitions in order to complete tasks, each with different demands. In order to design a decentralised algorithm for CFST we formulate it as a Distributed Constraint Optimisation problem and show how to solve it using the state-of-the-art Max-Sum algorithm that provides a completely decentralised message-passing solution. We then provide a novel algorithm (F-Max-Sum) that avoids sending redundant messages and efficiently adapts to changes in the environment. In empirical evaluations, our algorithm is shown to generate better solutions than other decentralised algorithms used for this problem

SAFER: Search and Find Emergency Rover

When disaster strikes and causes a structure to collapse, it poses a unique challenge to search and rescue teams as they assess the situation and search for survivors. Currently there are very few tools that can be used by these teams to aid them in gathering important information about the situation that allow members to stay at a safe distance. SAFER, Search and Find Emergency Rover, is an unmanned, remotely operated vehicle that can provide early reconnaissance to search and rescue teams so they may have more information to prepare themselves for the dangers that lay inside the wreckage. Over the past year, this team has restored a bare, non-operational chassis inherited from Roverwerx 2012 into a rugged and operational rover with increased functionality and reliability. SAFER uses a 360-degree camera to deliver real time visual reconnaissance to the operator who can remain safely stationed on the outskirts of the disaster. With strong drive motors providing enough torque to traverse steep obstacles and enough power to travel at up to 3 ft/s, SAFER can cover ground quickly and effectively over its 1-3 hour battery life, maximizing reconnaissance for the team. Additionally, SAFER contains 3 flashing beacons that can be dropped by the operator in the event a victim is found so that when team members do enter the scene they may easily locate victims. In the future, other teams may wish to improve upon this iteration by adding thermal imaging, air quality sensors, and potentially a robotic arm with a camera that can see in spaces too small for the entire rover to enter

Effect and Compensation of Timing Jitter in Through-Wall Human Indication via Impulse Through-Wall Radar

Impulse through-wall radar (TWR) is considered as one of preferred choices for through-wall human indication due to its good penetration and high range resolution. Large bandwidth available for impulse TWR results in high range resolution, but also brings an atypical adversity issue not substantial in narrowband radars — high timing jitter effect, caused by the non-ideal sampling clock at the receiver. The fact that impulse TWR employs very narrow pulses makes little jitter inaccuracy large enough to destroy the signal correlation property and then degrade clutter suppression performance. In this paper, we focus on the timing jitter impact on clutter suppression in through-wall human indication via impulse TWR. We setup a simple timing jitter model and propose a criterion namely average range profile (ARP) contrast is to evaluate the jitter level. To combat timing jitter, we also develop an effective compensation method based on local ARP contrast maximization. The proposed method can be implemented pulse by pulse followed by exponential average background subtraction algorithm to mitigate clutters. Through-wall experiments demonstrate that the proposed method can dramatically improve through-wall human indication performance

User-Centered Design

The successful introduction and acceptance of novel technological tools are only possible if end users are completely integrated in the design process. However, obtaining such integration of end users is not obvious, as end‐user organizations often do not consider research toward new technological aids as their core business and are therefore reluctant to engage in these kinds of activities. This chapter explains how this problem was tackled in the ICARUS project, by carefully identifying and approaching the targeted user communities and by compiling user requirements. Resulting from these user requirements, system requirements and a system architecture for the ICARUS system were deduced. An important aspect of the user‐centered design approach is that it is an iterative methodology, based on multiple intermediate operational validations by end users of the developed tools, leading to a final validation according to user‐scripted validation scenarios

Crisis Analytics: Big Data Driven Crisis Response

Disasters have long been a scourge for humanity. With the advances in technology (in terms of computing, communications, and the ability to process and analyze big data), our ability to respond to disasters is at an inflection point. There is great optimism that big data tools can be leveraged to process the large amounts of crisis-related data (in the form of user generated data in addition to the traditional humanitarian data) to provide an insight into the fast-changing situation and help drive an effective disaster response. This article introduces the history and the future of big crisis data analytics, along with a discussion on its promise, challenges, and pitfalls