64,188 research outputs found
Smartphone sensing platform for emergency management
The increasingly sophisticated sensors supported by modern smartphones open
up novel research opportunities, such as mobile phone sensing. One of the most
challenging of these research areas is context-aware and activity recognition.
The SmartRescue project takes advantage of smartphone sensing, processing and
communication capabilities to monitor hazards and track people in a disaster.
The goal is to help crisis managers and members of the public in early hazard
detection, prediction, and in devising risk-minimizing evacuation plans when
disaster strikes. In this paper we suggest a novel smartphone-based
communication framework. It uses specific machine learning techniques that
intelligently process sensor readings into useful information for the crisis
responders. Core to the framework is a content-based publish-subscribe
mechanism that allows flexible sharing of sensor data and computation results.
We also evaluate a preliminary implementation of the platform, involving a
smartphone app that reads and shares mobile phone sensor data for activity
recognition.Comment: 11th International Conference on Information Systems for Crisis
Response and Management ISCRAM2014 (2014
Knowledge acquisition and dissemination for emergency situation
Emergency situation is highly uncertain, dynamic, time pressure in making decisions and involves multi organizations and multi jurisdiction level. This paper presents a conceptual architecture that can be used by emergency response task force in assisting the victims of the disaster. Flood disaster is used as a case study. The architecture describes the knowledge and communication for flood emergency response management
An embodied conversational agent for intelligent web interaction on pandemic crisis communication
In times of crisis, an effective communication mechanism is paramount in providing accurate and timely information to the community. In this paper we study the use of an intelligent embodied conversational agent (EGA) as the front end interface with the public for a Crisis Communication Network Portal (CCNet). The proposed system, CCNet, is an integration of the intelligent conversation agent, AINI, and an Automated Knowledge Extraction Agent (AKEA). AKEA retrieves first hand information from relevant sources such as government departments and news channels. In this paper, we compare the interaction of AINI against two popular search engines, two question answering systems and two conversational systems
Research Agenda in Intelligent Infrastructure to Enhance Disaster Management, Community Resilience and Public Safety
Modern societies can be understood as the intersection of four interdependent
systems: (1) the natural environment of geography, climate and weather; (2) the
built environment of cities, engineered systems, and physical infrastructure;
(3) the social environment of human populations, communities and socio-economic
activities; and (4) an information ecosystem that overlays the other three
domains and provides the means for understanding, interacting with, and
managing the relationships between the natural, built, and human environments.
As the nation and its communities become more connected, networked and
technologically sophisticated, new challenges and opportunities arise that
demand a rethinking of current approaches to public safety and emergency
management. Addressing the current and future challenges requires an equally
sophisticated program of research, technology development, and strategic
planning. The design and integration of intelligent infrastructure-including
embedded sensors, the Internet of Things (IoT), advanced wireless information
technologies, real-time data capture and analysis, and machine-learning-based
decision support-holds the potential to greatly enhance public safety,
emergency management, disaster recovery, and overall community resilience,
while addressing new and emerging threats to public safety and security.
Ultimately, the objective of this program of research and development is to
save lives, reduce risk and disaster impacts, permit efficient use of material
and social resources, and protect quality of life and economic stability across
entire regions.Comment: A Computing Community Consortium (CCC) white paper, 4 page
Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)
This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio
Cross-comparative analysis of evacuation behavior after earthquakes using mobile phone data
Despite the importance of predicting evacuation mobility dynamics after large
scale disasters for effective first response and disaster relief, our general
understanding of evacuation behavior remains limited because of the lack of
empirical evidence on the evacuation movement of individuals across multiple
disaster instances. Here we investigate the GPS trajectories of a total of more
than 1 million anonymized mobile phone users whose positions are tracked for a
period of 2 months before and after four of the major earthquakes that occurred
in Japan. Through a cross comparative analysis between the four disaster
instances, we find that in contrast with the assumed complexity of evacuation
decision making mechanisms in crisis situations, the individuals' evacuation
probability is strongly dependent on the seismic intensity that they
experience. In fact, we show that the evacuation probabilities in all
earthquakes collapse into a similar pattern, with a critical threshold at
around seismic intensity 5.5. This indicates that despite the diversity in the
earthquakes profiles and urban characteristics, evacuation behavior is
similarly dependent on seismic intensity. Moreover, we found that probability
density functions of the distances that individuals evacuate are not dependent
on seismic intensities that individuals experience. These insights from
empirical analysis on evacuation from multiple earthquake instances using large
scale mobility data contributes to a deeper understanding of how people react
to earthquakes, and can potentially assist decision makers to simulate and
predict the number of evacuees in urban areas with little computational time
and cost, by using population density information and seismic intensity which
can be observed instantaneously after the shock
Virtual Reality Games for Motor Rehabilitation
This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion
OpenKnowledge at work: exploring centralized and decentralized information gathering in emergency contexts
Real-world experience teaches us that to manage emergencies, efficient crisis response coordination is crucial; ICT infrastructures are effective in supporting the people involved in such contexts, by supporting effective ways of interaction. They also should provide innovative means of communication and information management. At present, centralized architectures are mostly used for this purpose; however, alternative infrastructures based on the use of distributed information sources, are currently being explored, studied and analyzed. This paper aims at investigating the capability of a novel approach (developed within the European project OpenKnowledge1) to support centralized as well as decentralized architectures for information gathering. For this purpose we developed an agent-based e-Response simulation environment fully integrated with the OpenKnowledge infrastructure and through which existing emergency plans are modelled and simulated. Preliminary results show the OpenKnowledge capability of supporting the two afore-mentioned architectures and, under ideal assumptions, a comparable performance in both cases
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