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

Enabling Information Gathering Patterns for Emergency Response with the OpenKnowledge System

Today's information systems must operate effectively within open and dynamic environments. This challenge becomes a necessity for crisis management systems. In emergency contexts, in fact, a large number of actors need to collaborate and coordinate in the disaster scenes by exchanging and reporting information with each other and with the people in the control room. In such open settings, coordination technologies play a crucial role in supporting mobile agents located in areas prone to sudden changes with adaptive and flexible interaction patterns. Research efforts in different areas are converging to devise suitable mechanisms for process coordination: specifically, current results on service-oriented computing and multi-agent systems are being integrated to enable dynamic interaction among autonomous components in large, open systems. This work focuses on the exploitation and evaluation of the OpenKnowledge framework to support different information-gathering patterns in emergency contexts. The OpenKnowledge (OK) system has been adopted to model and simulate possible emergency plans. The Lightweight Coordination Calculus (LCC) is used to specify interaction models, which are published, discovered and executed by the OK distributed infrastructure in order to simulate peer interactions. A simulation environment fully integrated with the OK system has been developed to: (1) evaluate whether such infrastructure is able to support different models of information-sharing, e.g., centralized and decentralized patterns of interaction; (2) investigate under which conditions the OK paradigm, exploited in its decentralized nature, can improve the performance of more conventional centralized approaches. Preliminary results show the capability of the OK system in supporting the two afore-mentioned patterns and, under ideal assumptions, a comparable performance in both cases

EmergenSIG: an integrated location-based system for emergency management

Several solutions have been proposed for emergencies scenarios. These solutions include real-time data communication, location-aware, coordination, and decision-making support systems. In this context, this dissertation presents a location-awareness system fully oriented to emergency scenarios, called EmergenSIG. This approach provides and gathers important field information from an occurrence (emergency situation) and shares it to all the different agents. They include police, firefighters, medical emergency teams, among others, mobilized to the same operations theater (OT). Therefore, allowing a faster and integrated response to all the involved agents, enhancing the emergency management of the occurrence. The core of this proposal is based on a low cost solution oriented to the agents on the field (EmergenSIG mobile application), which interacts with the EmergenSIG Web application, oriented to the civil protection entities, through REST Web services. EmergenSIG focuses on medical emergencies and wildfires. It was evaluated and demonstrated in different mobile devices considering different screen sizes following a usercentered design. The system was also been evaluated and validated by real entities and civil protection agents on simulated emergency scenarios.Várias soluções têm sido propostas para cenários de emergências médicas . Estas soluções incluem comunicações de dados em tempo real ,sensíveis á localização , coordenação e sistemas de apoio à tomada de decisão. Neste contexto, esta dissertação apresenta um sistema sensível à localização totalmente orientada para cenários de emergência, chamada EmergenSIG. Esta abordagem proporciona e reúne importantes informações de uma ocorrência (situação de emergência) compartilhando-a para todos os diferentes agentes. Nos quais se incluem a polícia, bombeiros, equipas de emergência médica, entre outros, que se mobilizaram para o mesmo teatro de operações (TO). Portanto, permite uma resposta mais rápida e integrada para todos os agentes envolvidos, aumentando a eficácia da gestão da emergência de uma ocorrência. O cerne desta proposta é baseada numa solução de baixo custo direcionada para os agentes no terreno (aplicação móvel EmergenSIG), que interage com o aplicativo Web EmergenSIG, orientada para as entidades da proteção civil, através de serviços Web REST. O EmergenSIG centra-se em emergências médicas e incêndios florestais. Foi avaliada e demonstrada em diferentes dispositivos móveis, considerando diferentes tamanhos de ecrã e seguindo um design centrado no utilizador. O sistema também foi avaliado e validado por entidades reais e agentes da proteção civil em cenários de emergência simulados

SmartPM: automatic adaptation of dynamic processes at run-time

The research activity outlined in this thesis is devoted to define a general approach, a concrete architecture and a prototype Process Management System (PMS) for the automated adaptation of dynamic processes at run-time, on the basis of a declarative specification of process tasks and relying on well-established reasoning about actions and planning techniques. The purpose is to demonstrate that the combination of procedural and imperative models with declarative elements, along with the exploitation of techniques from the field of artificial intelligence (AI), such as Situation Calculus, IndiGolog and automated planning, can increase the ability of existing PMSs of supporting dynamic processes. To this end, a prototype PMS named SmartPM, which is specifically tailored for supporting collaborative work of process participants during pervasive scenarios, has been developed. The adaptation mechanism deployed on SmartPM is based on execution monitoring for detecting failures at run-time, which does not require the definition of the adaptation strategy in the process itself (as most of the current approaches do), and on automatic planning techniques for the synthesis of the recovery procedure

The applicability of the 3C model for understanding the use of technology in emergency management scenarios

The nature of emergency is intensive, imposing challenges related to the way coagencies collaborate. The 3C model consists of the combination of three elements, namely communication, coordination, and cooperation, connecting in a cycle, illustrating the nature of collaborative work for accomplishing certain tasks. Very few studies considered the use of the 3C model for improving collaboration in domains other than emergency management. This paper presents a scoping review of the literature in the domain of emergency management, focusing on how the 3C model can help us understand the use of technology for improving collaboration. The paper identifies the commonalities between the elements of the 3C model for improving our understanding of collaboration in emergency management scenarios, and indicating the inter-relationships among the elements of the 3C model that are applicable for understanding the topology of technology use in emergency management

Mobiilse värkvõrgu protsessihaldus

Värkvõrk, ehk Asjade Internet (Internet of Things, lüh IoT) edendab lahendusi nagu nn tark linn, kus meid igapäevaselt ümbritsevad objektid on ühendatud infosüsteemidega ja ka üksteisega. Selliseks näiteks võib olla teekatete seisukorra monitoorimissüsteem. Võrku ühendatud sõidukitelt (nt bussidelt) kogutakse videomaterjali, mida seejärel töödeldakse, et tuvastada löökauke või lume kogunemist. Tavaliselt hõlmab selline lahendus keeruka tsentraalse süsteemi ehitamist. Otsuste langetamiseks (nt milliseid sõidukeid parasjagu protsessi kaasata) vajab keskne süsteem pidevat ühendust kõigi IoT seadmetega. Seadmete hulga kasvades võib keskne lahendus aga muutuda pudelikaelaks. Selliste protsesside disaini, haldust, automatiseerimist ja seiret hõlbustavad märkimisväärselt äriprotsesside halduse (Business Process Management, lüh BPM) valdkonna standardid ja tööriistad. Paraku ei ole BPM tehnoloogiad koheselt kasutatavad uute paradigmadega nagu Udu- ja Servaarvutus, mis tuleviku värkvõrgu jaoks vajalikud on. Nende puhul liigub suur osa otsustustest ja arvutustest üksikutest andmekeskustest servavõrgu seadmetele, mis asuvad lõppkasutajatele ja IoT seadmetele lähemal. Videotöötlust võiks teostada mini-andmekeskustes, mis on paigaldatud üle linna, näiteks bussipeatustesse. Arvestades IoT seadmete üha suurenevat hulka, vähendab selline koormuse jaotamine vähendab riski, et tsentraalne andmekeskust ülekoormamist. Doktoritöö uurib, kuidas mobiilsusega seonduvaid IoT protsesse taoliselt ümber korraldada, kohanedes pidevalt muutlikule, liikuvate seadmetega täidetud servavõrgule. Nimelt on ühendused katkendlikud, mistõttu otsuste langetus ja planeerimine peavad arvestama muuhulgas mobiilseadmete liikumistrajektoore. Töö raames valminud prototüüpe testiti Android seadmetel ja simulatsioonides. Lisaks valmis tööriistakomplekt STEP-ONE, mis võimaldab teadlastel hõlpsalt simuleerida ja analüüsida taolisi probleeme erinevais realistlikes stsenaariumites nagu seda on tark linn.The Internet of Things (IoT) promotes solutions such as a smart city, where everyday objects connect with info systems and each other. One example is a road condition monitoring system, where connected vehicles, such as buses, capture video, which is then processed to detect potholes and snow build-up. Building such a solution typically involves establishing a complex centralised system. The centralised approach may become a bottleneck as the number of IoT devices keeps growing. It relies on constant connectivity to all involved devices to make decisions, such as which vehicles to involve in the process. Designing, automating, managing, and monitoring such processes can greatly be supported using the standards and software systems provided by the field of Business Process Management (BPM). However, BPM techniques are not directly applicable to new computing paradigms, such as Fog Computing and Edge Computing, on which the future of IoT relies. Here, a lot of decision-making and processing is moved from central data-centers to devices in the network edge, near the end-users and IoT sensors. For example, video could be processed in mini-datacenters deployed throughout the city, e.g., at bus stops. This load distribution reduces the risk of the ever-growing number of IoT devices overloading the data center. This thesis studies how to reorganise the process execution in this decentralised fashion, where processes must dynamically adapt to the volatile edge environment filled with moving devices. Namely, connectivity is intermittent, so decision-making and planning need to involve factors such as the movement trajectories of mobile devices. We examined this issue in simulations and with a prototype for Android smartphones. We also showcase the STEP-ONE toolset, allowing researchers to conveniently simulate and analyse these issues in different realistic scenarios, such as those in a smart city.  https://www.ester.ee/record=b552551

Model-Driven Data Integration for Emergency Response : Doctoral Dissertation for the Degree Philosophiae Doctor (PhD) at the Faculty of Engineering and Science, Specialization in Information and Communication Technology

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