Social Emergency Alert Service - A Location-Based Privacy-Aware Personal Safety Service

Ovelgönne, Michael; Sonnenbichler, Andreas C.; Geyer-Schulz, Andreas

doi:10.1109/ngmast.2010.27

Cited by 10 publications

(4 citation statements)

References 6 publications

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“…One such solution is an application called Emergency Alert System (EAS), which sends emergency calls to the social contacts of the requester [6]. These above mentioned mobile systems, while requesting for blood donation; considers only static contact location of the blood donors.…”

Section: Related Workmentioning

confidence: 99%

A Geo-Location based Mobile Service that Dynamically Locates and Notifies the nearest Blood Donors for Blood Donation during Medical Emergencies

Parikh¹,

Kathiria²,

Vaghela³

et al. 2014

IJCA

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Section: Related Workmentioning

confidence: 99%

A Geo-Location based Mobile Service that Dynamically Locates and Notifies the nearest Blood Donors for Blood Donation during Medical Emergencies

Parikh¹,

Kathiria²,

Vaghela³

et al. 2014

IJCA

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“…This information is geolocated, either from image metadata or through a textual or visual analysis, and displayed on a map. An emergency alert service [12] informs social contacts and public authorities about the emergency situation. Events and user interactions are represented by means of the WeKnowIt core ontology, CURIO 2 , which defines resources for user generated content.…”

Section: Related Workmentioning

confidence: 99%

Semantic reasoning for intelligent emergency response applications

Hristoskova

Ongenae

Turck

2013

2013 11th IEEE International Conference on Industrial Informatics (INDIN)

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Abstract-Emergency response applications require the processing of large amounts of data, generated by a diverse set of sensors and devices, in order to provide for an accurate and concise view of the situation at hand. The adoption of semantic technologies allows for the definition of a formal domain model and intelligent data processing and reasoning on this model based on generated device and sensor measurements. This paper presents a novel approach to emergency response applications, such as fire fighting, integrating a formal semantic domain model into an event-based decision support system, which supports reasoning on this model. The developed model consists of several generic ontologies describing concepts and properties which can be applied to diverse context-aware applications. These are extended with emergency response specific ontologies. Additionally, inference on the model performed by a reasoning engine is dynamically synchronized with the rest of the architectural components. This allows to automatically trigger events based on predefined conditions. The proposed ontology and developed reasoning methodology is validated on two scenarios, i.e. (i) the construction of an emergency response incident and corresponding scenario and (ii) monitoring of the state of a fire fighter during an emergency response.

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“…[6] Visual Sentiment analysis on twitter data streams has also been done , indicating positive and negative tweets from all around the world using natural language processing. [7] A social emergency alert service [8] that makes use of the wide availability of smart phones and activates nearby social contacts in cases of emergency has also been researched. Also, a Dangerous Location Aware System for Assisting Kids Safety Care [9] provides insight as to how the system alerts a kid on the move of the possible dangers whenever he/she is near accident prone areas.…”

Section: Literature Review and Related Workmentioning

confidence: 99%

Using Social Networking Data as a Location based Warning System

Alkutkar¹,

Sam²,

Tambe³

et al. 2012

IJCA

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Twitter and Facebook are huge social networks that contain a lot of data that can be used for sentiment analysis. We often find out that a particular area we travel to is dangerous, after asking around. However what if we could use social networking data like 'tweets' to find out if a place is actually dangerous? This paper introduces how to use social networking data, analyze it and use it for alerting someone in a disaster prone or high crime rate prone area with the help of smartphones using natural language processing and sentiment analysis.

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Social Emergency Alert Service - A Location-Based Privacy-Aware Personal Safety Service

Cited by 10 publications

References 6 publications

A Geo-Location based Mobile Service that Dynamically Locates and Notifies the nearest Blood Donors for Blood Donation during Medical Emergencies

A Geo-Location based Mobile Service that Dynamically Locates and Notifies the nearest Blood Donors for Blood Donation during Medical Emergencies

Semantic reasoning for intelligent emergency response applications

Using Social Networking Data as a Location based Warning System

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