Fuzzy logic-based hardware architecture for event detection in Wireless Sensor Networks

In this paper, we present and evaluate a hardware multi-sensor architecture for objects / events detection, especially designed to enable low power and higher precision in Wireless Sensor Networks. The proposed architecture is based on fuzzy logic approach in order to improve mapping between QoS requirements for a communication processes and available hardware resources in WSN nodes. It improves the accuracy in taking decision about a system that has imprecise information. Each node introduces two types of sensors, scalar and visual. Scalar sensors perform detection and localization of objects, while the other visual is responsible to monitoring objects. A set of fuzzy rules to analyze signals collected by different sensors is used to activate rest of the sensing circuits (i.e., data processing and communication) only when the event of interest in the environment is available. We discuss in depth the internal hardware architecture of the proposed solution which is planned to reach high performance running in FPGAs circuit. Synthesis results and relevant performance comparisons with related works are presented.

[1]  Kay Römer,et al.  The design space of wireless sensor networks , 2004, IEEE Wireless Communications.

[2]  Vijay Ramaraju,et al.  Energy Efficient Image Transmission In Wireless Multimedia Sensor Networks , 2014 .

[3]  Jean-Marie Moureaux,et al.  Design and performance analysis of a zonal DCT-based image encoder for Wireless Camera Sensor Networks , 2012, Microelectron. J..

[4]  Ganesh K. Venayagamoorthy,et al.  Computational Intelligence in Wireless Sensor Networks: A Survey , 2011, IEEE Communications Surveys & Tutorials.

[5]  Marília Curado,et al.  QoE-aware FEC mechanism for intrusion detection in multi-tier Wireless Multimedia Sensor Networks , 2012, 2012 IEEE 8th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).

[6]  Sener Uysal,et al.  Forest Fire Detection in Wireless Sensor Network Using Fuzzy Logic , 2013, 2013 Fifth International Conference on Computational Intelligence, Communication Systems and Networks.

[7]  Dr. Kasim M. Al-Aubidy.  FPGA Implementation of Fuzzy Inference System for Embedded Applications , 2007 .

[8]  Ran Wolff,et al.  Noname manuscript No. (will be inserted by the editor) In-Network Outlier Detection in Wireless Sensor Networks , 2022 .

[9]  Federico Viani,et al.  Wireless Architectures for Heterogeneous Sensing in Smart Home Applications: Concepts and Real Implementation , 2013, Proceedings of the IEEE.

[10]  Marko Hännikäinen,et al.  A Survey of Wireless Sensor Network Abstraction for Application Development , 2012, Int. J. Distributed Sens. Networks.

[11]  Syed Mahfuzul Aziz,et al.  Energy Efficient Image Transmission in Wireless Multimedia Sensor Networks , 2013, IEEE Communications Letters.

[12]  Jean-Marie Moureaux,et al.  Low power hardware-based image compression solution for wireless camera sensor networks , 2012, Comput. Stand. Interfaces.

[13]  Rajdeep Singh,et al.  Multi-Sensor Based Forest Fire Detection System , 2013 .

[14]  Vilém Novák,et al.  Fuzzy Set , 2009, Encyclopedia of Database Systems.

[15]  R. Yager.  On a general class of fuzzy connectives , 1980 .

[16]  A. Srividya,et al.  Multi-Sensor Data Fusion in Cluster based Wireless Sensor Networks Using Fuzzy Logic Method , 2008, 2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems.

[17]  Amrit,et al.  Comparison of Mamdani-Type and Sugeno-Type Fuzzy Inference Systems for Air Conditioning System , 2012 .

[18]  Kieu-Xuan Thuc,et al.  A collaborative event detection scheme using fuzzy logic in clustered wireless sensor networks , 2011 .