Title
MSSN-Onto: An ontology-based approach for flexible event processing in Multimedia Sensor Networks
Date Issued
01 July 2020
Access level
metadata only access
Resource Type
journal article
Author(s)
Angsuchotmetee C.
Chbeir R.
Publisher(s)
Elsevier B.V.
Abstract
Multimedia Sensor Networks (MSNs) have gained much attention in recent years from the emerging trends of Internet of Things (IoT). They can be found in different scenarios in our everyday life (e.g., smart homes, smart buildings). Sensors in MSNs can have different capacities, produce multiple kinds of outputs, and have different output encoding formats. Thus, detecting complex events, which requires the aggregation of several sensor readings, can be difficult due to the lack of a generic model that can describe: (i) sensor networks infrastructure, (ii) individual sensor specificities, as well as (iii) multimedia data, while allowing the alignment with the application domain knowledge. In this study, we propose Multimedia Semantic Sensor Network Ontology (MSSN-Onto) to ensure MSNs modeling and provide both syntactic and semantic data interoperability for defining and detecting events in various domains. To show the readiness of MSSN-Onto, we used it as the core ontology of a dedicated framework (briefly defined here). We also adopted MSSN-Onto in HIT2GAP European Project. A prototype has been implemented to conduct a set of tests. Experimental results show that MSSN-Onto can be used to: (i) effectively model MSNs and multimedia data; (ii) define complex events; and (iii) allow to build an efficient event querying engine for MSNs.
Start page
1140
End page
1158
Volume
108
Language
English
OCDE Knowledge area
Ingeniería de sistemas y comunicaciones Ciencias de la computación
Scopus EID
2-s2.0-85042565227
Source
Future Generation Computer Systems
ISSN of the container
0167739X
Sponsor(s)
We would like to acknowledge Campus France, French Embassy of Thailand, and Prince of Songkla University for providing funding support (Franco-Thailand Scholarship 2013/2014). Also, many thanks to the Computer Science Laboratory of the University Pau & Pays Adour (LIUPPA) for providing all necessary infrastructure and tools needed for this work. We also would like to thank Dr. Gilbert Tekli for his support and advice.
Sources of information: Directorio de Producción Científica Scopus