# Semantic Traffic Sensor Data:
## 2 Related Work
### Analysis of Traffic-Related Ontologies  
Different types of existing ontologies related to the traffic of vehicles can be considered. We can highlight the following ones:  
* The Vocabulary to Represent Data About Traffic Ontology [23], developed by [PERSON] (a member of the Ontology Engineering Group at the Polytechnic University of Madrid) has been proposed for the representation of the situation of traffic in a city. It extends the Sensor Network Ontology (SSN) [24; 25; 26] to represent the intensity of traffic on the different road segments of a city. It represents road segments (concept _escjr:TramoVia_), traffic observations (concept _estrf:TrafficObservation_, which for the moment is specialized only in the subconcept _estrf:TrafficIntensityObservation_, but other subconcepts could be added in the future to represent other types of traffic observations), the sensor or sensing system used to obtain a given measurement (concept _estrf:TrafficIntensitySensor_, which is considered optional), the result of an observation (concept _TrafficIntensitySensorOutput_, which has a value-concept_estrf:TrafficIntensityObservationValue_, linked to TrafficIntensitySensorOutput through the property _ssn:hasValue_ and is produced by a specific sensor or sensing system identified by a specific URI and linked to TrafficIntensitySensorOutput through the property _ssn:isProducedBy_), and finally an instance _estrf:TrafficIntensity_ that represents the type of property being measured (in this case, the intensity of the traffic). This vocabulary is still work in progress, developed in the context of the working group on transport of AENOR [27]. The authors recommend using this vocabulary in conjunction with the vocabulary proposed to represent city road maps (particularly, road segments) [28]. This proposal does not currently contemplate the modeling of traffic properties other than traffic intensities (_estrf:TrafficIntensityObservation_), but they can be easily added by extending _estrf:TrafficObservation_. * The work presented in [29] presents an ontology-driven architecture that enables performing several automatic tasks to increase traffic safety and improve the comfort of the drivers. The ontology layer is described as composed of three groups of interrelated concepts: concepts related to vehicles, concepts related to roads, and concepts related to sensors. The concepts related to vehicles describe a taxonomy of vehicles of different types, including commercial vehicles, public vehicles (buses and taxis), private vehicles (cars, bicycles, and motorbikes) and priority vehicles (ambulances, police cars, and fire trucks), and also allow representing information about their routes and locations. The concepts related to the infrastructure include a taxonomy of different types of roads (local roads, prefectural roads, national highways, and national expressways), as well as the representation of other parts of the infrastructure, such as the road segments, traffic lights and traffic signs, lanes, road markings (e.g., painted arrows), and other infrastructure elements (tunnels, parkings, roundabouts, bridges, gas stations, and toll stations). Finally, the concepts related to sensors are based on the use of the SSN ontology. Besides, a mapping schema is proposed to map the sensor data to semantic data, as in [30], in such a way that the sensor data can be automatically represented as instances of the SSN ontology; the property observed is _Car_flow_ property. This is a relevant work that proposes an ontological layer covering different aspects of traffic. Still, it mainly focuses on the development of an architecture that exploits such a layer to perform various actions through an agent layer. Some use case scenarios are presented: regulating the air conditioning of a car, traffic light adjustment based on the traffic flow and the weather conditions, and traffic congestion control for GPS navigators.