Estimating Fire Weather Indices Via Semantic Reasoning Over Wireless Sensor Network Data Streams

Gao, Lianli; Bruenig, Michael; Hunter, Jane

doi:10.5121/ijwest.2014.5401

Cited by 6 publications

(3 citation statements)

References 34 publications

(44 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Over the last decade, Semantic Web technologies have been integrated into wireless sensor networks (WSN) for various purposes [27], such as activity detection and data management [24], raw sensor data processing [3], analysis of sensor networks and their data [21], optimization of energy consumption of sensor networks [6], or estimation of fire wheather indices [14].…”

Section: Related Workmentioning

confidence: 99%

Fuzzy Semantic Web Architecture for Activity Detection in Wireless Multimedia Sensor Network Applications

Ozdin¹,

Yazıcı

Koyuncu

2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

View full text Add to dashboard Cite

This study aims to increase the reliability of activity detection in Wireless Multimedia Sensor Networks (WMSNs) by using Semantic Web technologies extended with fuzzy logic. The proposed approach consists of three layers: the sensor layer, the data layer, and the Semantic Web layer. The sensor layer comprises a WMSN comprising sensor nodes with multimedia and scalar sensors. The data layer retrieves and stores data from the sink of WMSN. At the top of the architecture, there is a semantic web layer that includes a semantic web application server, a fuzzy reasoning engine, and a semantic knowledge base. When a new entity is detected at the sensor layer, the associated data produced by the sensors and the sink are collected in the data layer and transmitted to the semantic web application server where the data is converted into subjects, predicates, and objects, according to the ontology conceived and recorded in RDF format. Then, the fuzzy reasoning engine is automatically activated and fuzzy rules are executed to determine if there is an activity in the monitored area. Our implementation confirms that extended semantic Web technologies with fuzzy logic can have a significant impact on the detection of activities in WMSNs.

show abstract

Section: Related Workmentioning

confidence: 99%

Fuzzy Semantic Web Architecture for Activity Detection in Wireless Multimedia Sensor Network Applications

Ozdin¹,

Yazıcı

Koyuncu

2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

View full text Add to dashboard Cite

show abstract

“…MF definition should cope with the semantics of sensor data and phenomenon (Ross 2010). For illustration, let's consider a sensor network recording temperature in an area under bushfire, considering the ontology of sensor data for fire monitoring (Gao et al 2014), MF for such case can be of S shape as illustrated in Figure 1. [ ]…”

Section: Stage-1: Local Detection Of Phenomenon Using Three-valued Logicmentioning

confidence: 99%

Modelling Vague Shape Dynamic Phenomena from Sensor Network data using a Decentralized Fuzzy Rule-Based Approach

Cesarie¹,

Njila²,

Mostafavi³

et al. 2016

GIScience

View full text Add to dashboard Cite

Modelling dynamic phenomena of vague shape from sensor data is still a challenging problem for many applications. In this paper, we propose a decentralized fuzzy rule-based approach based on fuzzy object model to build a more realistic spatiotemporal representation for such phenomena. This approach has been successfully implemented in a simulation case of bushfire monitoring, showing advantages for spatial decision making in a disaster management context.

show abstract

“…In Eid et al [ 19 ] and Huang et al [ 20 ], ontologies are defined in order to describe concepts and relationships of WSNs from the network data and to improve the accuracy of queries. In [ 21 ], data from a WSN are used for fire hazard rating applying Semantic Web technologies for the processing of data streams, which allow domain experts to specify and adjust the rules to calculate fire rates. As for [ 22 ], the Semantic Web is used in WSNs for precision farming applications.…”

Section: Related Workmentioning

confidence: 99%

SITRUS: Semantic Infrastructure for Wireless Sensor Networks

Bispo

Rosa

Cunha

2015

Sensors

View full text Add to dashboard Cite

Wireless sensor networks (WSNs) are made up of nodes with limited resources, such as processing, bandwidth, memory and, most importantly, energy. For this reason, it is essential that WSNs always work to reduce the power consumption as much as possible in order to maximize its lifetime. In this context, this paper presents SITRUS (semantic infrastructure for wireless sensor networks), which aims to reduce the power consumption of WSN nodes using ontologies. SITRUS consists of two major parts: a message-oriented middleware responsible for both an oriented message communication service and a reconfiguration service; and a semantic information processing module whose purpose is to generate a semantic database that provides the basis to decide whether a WSN node needs to be reconfigurated or not. In order to evaluate the proposed solution, we carried out an experimental evaluation to assess the power consumption and memory usage of WSN applications built atop SITRUS.

show abstract

Estimating Fire Weather Indices Via Semantic Reasoning Over Wireless Sensor Network Data Streams

Abstract: ABSTRACT

Cited by 6 publications

References 34 publications

Fuzzy Semantic Web Architecture for Activity Detection in Wireless Multimedia Sensor Network Applications

Fuzzy Semantic Web Architecture for Activity Detection in Wireless Multimedia Sensor Network Applications

Modelling Vague Shape Dynamic Phenomena from Sensor Network data using a Decentralized Fuzzy Rule-Based Approach

SITRUS: Semantic Infrastructure for Wireless Sensor Networks

Contact Info

Product

Resources

About