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.
- Presents alarm or alert detection in all its aspects
- Finds a solution so that the alert information reaches the right destination
- Find relevance to various technical issues
Specialists in plic safety, prevention of natural hazards (earthquakes, floods and fires), ecology and environments, network, big data and public alert
1. Predicting Alarms through Big Data Analytics: Feedback from Industry Pilots
Christophe PONSARD, Annick MAJCHROWSKI, Mathieu GOEMINNE
2. Mobility and Prediction: An Asset for Crisis Management
Nicolas GUTOWSKI, Tassadit AMGHAR, Olivier CAMP, Slimane HAMMOUDI
3. Smartphone Applications: A Means to Promote Emergency Management in France?
4. Mobiquitous Systems Applied to Earthquake Monitoring: The SISMAPP Project
5. Information Systems for Supporting Strategic Decisions and Alerts in Pharmacovigilance
Yannick BARDIE, Thérèse LIBOUREL
6. An Ontologically-based Trajectory Modeling Approach for an Early Warning System
Jamal MALKI, Alain BOUJU
7. Toward a Modeling of Population Behaviors in Crisis Situations
Elsa NEGRE, Maude ARRU, Camille ROSENTHAL-SABROUX
8. Online Social Network Phenomena:Buzz, Rumor and Spam
Manel MEZGHANI, Mahdi WASHHA, Florence SÈDES
9. How Can Computer Tools Improve Early Warnings for Wildlife Diseases?
Pierpaolo BRENA, Dominique GAUTHIER, Antoine HUMEAU, Florence BAURIER, Frédéric DEJ, Karin LEMBERGER, Jean-Yves CHOLLET, Anouk DECORS
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- © ISTE Press - Elsevier 2019
- 8th November 2018
- ISTE Press - Elsevier
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Florence Sèdes is a Professor of Computer Science at Paul Sabatier University, Toulouse, France. Her research focuses on data science, and she has published many books and articles and advised more than 30 PhDs. She leads various international, European and national projects on personal (meta)data privacy and management with applications to deep/machine learning for alert, spam and rumor detection, social emotion and interaction
Professor, Paul Sabatier University, Toulouse, France