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How information systems can help in alarm/alert detection /
Alarm or alert detection remains an issue in various areas from nature, i.e. flooding, animals or earthquake, to software systems. Liveness, dynamicity, reactivity of alarm systems: how to ensure the warning information reach the right destination at the right moment and in the right location, still...
| Clasificación: | Libro Electrónico |
|---|---|
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London, UK : Kidlington, Oxford, UK :
ISTE Press Ltd ; Elsevier Ltd,
2018.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 245 | 0 | 0 | |a How information systems can help in alarm/alert detection / |c edited by Florence S�edes. |
| 264 | 1 | |a London, UK : |b ISTE Press Ltd ; |a Kidlington, Oxford, UK : |b Elsevier Ltd, |c 2018. | |
| 264 | 4 | |c �2018 | |
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| 520 | |a Alarm or alert detection remains an issue in various areas from nature, i.e. flooding, animals or earthquake, to software systems. Liveness, dynamicity, reactivity of alarm systems: how to ensure the warning information reach the right destination at the right moment and in the right location, still being relevant for the recipient, in spite of the various and successive filters of confidentiality, privacy, firewall policies, etc.? Also relevant in this context are to technical contingency issues: material failure, defect of connection, break of channels, independence of information routes and sources? Alarms with crowd media, (mis)information vs. rumours: how to make the distinction? The prediction of natural disasters (floods, avalanches, etc.), health surveillance (affectionate fevers of cattle, pollution by pesticides, etc.), air, sea and land transport, or space surveillance to prevent Risks of collisions between orbital objects involve more and more actors within Information Systems, one of whose purposes is the dissemination of alerts. By expanding the capabilities and functionality of such national or international systems, social networks are playing a growing role in dissemination and sharing, eg. with the support of systems like the Google Alert (https://www.google.fr/alerts) which concerns the publication of contents online. Recently, the Twitter microblogging platform announced a broadcast service, designed to help government organizations with alerts to the public. The proper functioning of such systems depends on fundamental properties such as resilience, liveliness and responsiveness: any alert must absolutely reach the right recipient at the right time and in the right place, while remaining relevant to him, despite the various constraints. on the one hand to external events, such as hardware failures, connection faults, breaks in communication channels, on the other hand to confidentiality, such as the collection and use of personal data (with or without the consent of the user), or the disparity of access policies (generation according to industrial, technological, security constraints, management of internal / external policies, etc.) between actors. This book opens the discussion on the "procrastination", the dynamics and the reactivity of the alert systems, but also the problems of confidentiality, filtering of information, and the means of distinguishing information and rumor. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Front Cover; How Information Systems Can Help in Alarm/Alert Detection; Copyright Page; Contents; Introduction; Predicting Alarms through Big Data Analytics: Feedback from Industry Pilots; Mobility and Prediction: an Asset for Crisis Management; Smartphone Applications: a Means to Promote Emergency Management in France?; Mobiquitous Systems Applied to Earthquake Monitoring: the SISMAPP project; Information Systems for Supporting Strategic Decisions and Alerts in Pharmacovigilance; An Ontologically-based Trajectory Modeling Approach for an Early Warning System | |
| 505 | 8 | |a Toward a Modeling of Population Behaviors in Crisis SituationsOnline Social Network Phenomena: Rumor, Buzz and Spam; How Can Computer Tools Improve Early Warnings for Wildlife Diseases?; 1. Predicting Alarms through Big Data Analytics: Feedback from Industry Pilots; 1.1. Introduction; 1.2. Background: alarm terminology, system analysis and data analytics; 1.3. Overview of the case studies and methodology; 1.4. Case Study 1: improving IT availability using predictive maintenance; 1.5. Case study 2: better care quality through clinical pathways; 1.6. Discussion and related work | |
| 505 | 8 | |a 1.7. Conclusion and perspectives1.8. Acknowledgments; 1.9. References; 2. Mobility and Prediction: an Asset for Crisis Management; 2.1. Introduction; 2.2. Related works on MCSC; 2.3. Our proposed framework; 2.4. Urban mobility and prediction with Ur-MoVe; 2.5. Conclusion and future works; 2.6. References; 3. Smartphone Applications: a Means to Promote Emergency Management in France?; 3.1. Introduction; 3.2. Investing in smartphones: a contextual opportunity; 3.3. Considerable benefits expected; 3.4. Potential that should not be overestimated | |
| 505 | 8 | |a 3.5. How can we encourage recourse to smartphone applications?3.6. Conclusions; 3.7. References; 4. Mobiquitous Systems Applied to Earthquake Monitoring: the SISMAPP Project; 4.1. Introduction; 4.2. Motivations; 4.3. State of the art; 4.4. Overview of our work; 4.5. Measurement collector from the mobile accelerometer sensor; 4.6. Conclusion and continuation of the project; 4.7. Acknowledgments; 4.8. References; 5. Information Systems for Supporting Strategic Decisions and Alerts in Pharmacovigilance; 5.1. Introduction; 5.2. Pharmacovigilance | |
| 505 | 8 | |a 5.3. System and clinical trial project organization analysis5.4. The state of the art; 5.5. Issues; 5.6. Proposal: considered solution; 5.7. Conclusion; 5.8. References; 6. An Ontologically-based Trajectory Modeling Approach for an Early Warning System; 6.1. Introduction; 6.2. Related work; 6.3. Modeling approach; 6.4. Domain trajectory ontology; 6.5. Time ontology; 6.6. Mapping trajectory and time ontologies; 6.7. Trajectory ontology inference framework; 6.8. Trajectory ontology inference framework implementation; 6.9. Experiments; 6.10. Application domain inference refinement | |
| 588 | 0 | |a Online resource; title from digital title page (viewed on January 02, 2019). | |
| 650 | 0 | |a Electric alarms. | |
| 650 | 6 | |a Alarmes �electriques. |0 (CaQQLa)201-0001034 | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING |x Mechanical. |2 bisacsh | |
| 650 | 7 | |a Electric alarms. |2 fast |0 (OCoLC)fst00904399 | |
| 776 | 0 | 8 | |i Print version: |t HOW INFORMATION SYSTEMS CAN HELP IN ALARM/ALERT DETECTION. |d [Place of publication not identified] : ISTE PRESS LTD - ELSEVIER, 2018 |z 1785483021 |w (OCoLC)1045458312 |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9781785483028 |z Texto completo |