Group decision making with a fuzzy linguistic majority
Fuzzy Sets and Systems
Linguistic decision analysis: steps for solving decision problems under linguistic information
Fuzzy Sets and Systems - Special issue on soft decision analysis
The nesC language: A holistic approach to networked embedded systems
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Energy-efficient surveillance system using wireless sensor networks
Proceedings of the 2nd international conference on Mobile systems, applications, and services
Monitoring Civil Structures with a Wireless Sensor Network
IEEE Internet Computing
Agent-Based Petroleum Offshore Monitoring Using Sensor Networks
DEXA '06 Proceedings of the 17th International Conference on Database and Expert Systems Applications
Health monitoring of civil infrastructures using wireless sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Information fusion for wireless sensor networks: Methods, models, and classifications
ACM Computing Surveys (CSUR)
A survey on clustering algorithms for wireless sensor networks
Computer Communications
PEACH: Power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks
Computer Communications
A Holistic Approach to Decentralized Structural Damage Localization Using Wireless Sensor Networks
RTSS '08 Proceedings of the 2008 Real-Time Systems Symposium
Fuzzy Self-Clustering for Wireless Sensor Networks
EUC '08 Proceedings of the 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing - Volume 01
A semantic middleware for autonomic wireless sensor networks
WMUPS '09 Proceedings of the 2009 Workshop on Middleware for Ubiquitous and Pervasive Systems
D-FLER: a distributed fuzzy logic engine for rule-based wireless sensor networks
UCS'07 Proceedings of the 4th international conference on Ubiquitous computing systems
Tandem: a context-aware method for spontaneous clustering of dynamic wireless sensor nodes
IOT'08 Proceedings of the 1st international conference on The internet of things
An application-specific protocol architecture for wireless microsensor networks
IEEE Transactions on Wireless Communications
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We propose a semantic clustering model based on a fuzzy inference system to find out the semantic neighborhood relationships in wireless sensor networks in order to both reduce energy consumption and improve the data accuracy. As a case study we describe a structural health monitoring application which was used to illustrate and assess the proposed model. We conduct experiments in order to evaluate the proposal in two different scenarios of damage with different data aggregation methods. We also compared our proposal, using the same data set, with a deterministic clustering method and with the LEACH algorithm. The results indicate that our approach is an energy-efficient clustering method for WSNs, outperforming both the deterministic clustering and LEACH algorithms in about 70% and 47% of energy savings respectively. The energy saving comes from the fact that we have a more efficient in-network data aggregation process since by exploiting the semantic relation between sensor nodes we can potentially aggregate more similar data and consequently, decrease the data redundancy (thus minimizing transmissions). Nodes that are semantically unrelated can operate in low-duty cycle, further reducing the energy consumption. Moreover, our proposal has the potential to improve the data accuracy provided for the application where accuracy is a QoS requirement in typical WSN applications.