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A semantic autonomous video surveillance system for dense camera networks in Smart Cities.

Calavia L, Baladrón C, Aguiar JM, Carro B, Sánchez-Esguevillas A - Sensors (Basel) (2012)

Bottom Line: This paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement.Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies.This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network.

View Article: PubMed Central - PubMed

Affiliation: Universidad de Valladolid, Dpto. TSyCeIT, ETSIT, Paseo de Belén 15, Valladolid 47011, Spain. lcaldom@ribera.tel.uva.es

ABSTRACT
This paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network.

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Related in: MedlinePlus

OWL and SWRL code.
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f3-sensors-12-10407: OWL and SWRL code.

Mentions: The prototype implemented uses Semantic Web standards for the specification of these two elements, using the JENA framework as a provider of all the required semantic operations within Java. Specifically, the ontology is defined using OWL (Web Ontology Language); SWRL (Semantic Web Rule Language) is used for the specification of the semantic rules (Figure 3). The ontology governs how the moving objects, routes, sinks and sources are understood. For instance, in a traffic management ontology used for a camera watching a segment of a highway, moving objects will be cars and trucks; routes will be highway lanes; sinks and sources will most probably be the edges of the highway segment. But in a vandalism control ontology used for a camera watching a public garden, moving objects will be people, and routes will be common pathways.


A semantic autonomous video surveillance system for dense camera networks in Smart Cities.

Calavia L, Baladrón C, Aguiar JM, Carro B, Sánchez-Esguevillas A - Sensors (Basel) (2012)

OWL and SWRL code.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472835&req=5

f3-sensors-12-10407: OWL and SWRL code.
Mentions: The prototype implemented uses Semantic Web standards for the specification of these two elements, using the JENA framework as a provider of all the required semantic operations within Java. Specifically, the ontology is defined using OWL (Web Ontology Language); SWRL (Semantic Web Rule Language) is used for the specification of the semantic rules (Figure 3). The ontology governs how the moving objects, routes, sinks and sources are understood. For instance, in a traffic management ontology used for a camera watching a segment of a highway, moving objects will be cars and trucks; routes will be highway lanes; sinks and sources will most probably be the edges of the highway segment. But in a vandalism control ontology used for a camera watching a public garden, moving objects will be people, and routes will be common pathways.

Bottom Line: This paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement.Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies.This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network.

View Article: PubMed Central - PubMed

Affiliation: Universidad de Valladolid, Dpto. TSyCeIT, ETSIT, Paseo de Belén 15, Valladolid 47011, Spain. lcaldom@ribera.tel.uva.es

ABSTRACT
This paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network.

Show MeSH
Related in: MedlinePlus