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Performing acoustic localization in a network of embedded smart sensors

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Situation awareness is an important aspect of ubiquitous computer systems, as these systems of systems are highly integrated with the physical world and for successful operation they must maintain high awareness of the environment. Acoustic information is one of the most popular modalities, by which the environment states are estimated. Multi-sensor approaches also provide the possibility for acoustic source localization. This paper considers an acoustic localization system of dual channel smart sensors interconnected through a Wireless Sensor Network (WSN). The low computational power of smart sensor devices requires distribution of localization tasks among WSN nodes. The Initial Search Region Reduction (ISRR) method is used in the WSN to meet this requirement. ISRR, as opposed to conventional localization methods, performs significantly less complex computations and does not require exchange of raw signal between nodes. The system is implemented on smart dust motes utilizing Atmel ATmega128RFA1 processors with integrated 2.4GHz IEEE 802.15.4 compliant radio transceivers. The paper discusses complications introduced by low power hardware and ad-hoc networking, and also reviews conditions of real-time operation.
Rocznik
Strony
86--95
Opis fizyczny
Bibliogr. 21 poz., 1 fot. kolor., rys., wykr.
Twórcy
autor
  • Research Laboratory for Proactive Technologies, Department of Computer Control, Tallinn University of Technology, Ehitajate tee 5, 19086, Tallinn, Estonia
autor
  • Research Laboratory for Proactive Technologies, Department of Computer Control, Tallinn University of Technology, Ehitajate tee 5, 19086, Tallinn, Estonia
autor
  • Research Laboratory for Proactive Technologies, Department of Computer Control, Tallinn University of Technology, Ehitajate tee 5, 19086, Tallinn, Estonia
Bibliografia
  • [1] S. Astapov and A. Riid, “A multistage procedure of mobile vehicle acoustic identification for single-sensor embedded device,” International Journal of Electronics and Telecommunications (JET), vol. 59, no. 2, pp. 151–160, 2013.
  • [2] S. Astapov, J.-S. Preden, J. Ehala, and A. Riid, “Object detection for military surveillance using distributed multimodal smart sensors,” in Proc. 19th Int. Conf. on Digital Signal Processing (DSP 2014), 20–23 Aug. 2014, pp. 366–371.
  • [3] H. Lohrasbipeydeh, A. Zielinski, and T. Gulliver, “A new acoustic method for passive sperm whale depth tracking,” in Proc. IEEE Region 10 Conference TENCON 2012, Nov 2012, pp. 1–5.
  • [4] J.-C. Wang, C.-H. Lin, E. Siahaan, B.-W. Chen, and H.-L. Chuang, “Mixed sound event verification on wireless sensor network for home automation,” IEEE Transactions on Industrial Informatics, vol. 10, no. 1, pp. 803–812, Feb 2014.
  • [5] Y. Lee, K. Kim, D. Han, and H. Ko, “Acoustic and visual signal based violence detection system for indoor security application,” in Proc. 2012 IEEE Int. Conf. on Consumer Electronics (ICCE), 2012, pp. 737–738.
  • [6] S. Astapov, J. S. Preden, T. Aruvali, and B. Gordon, “Production machinery utilization monitoring based on acoustic and vibration signal analysis,” in Proc. 8th Int. Conf. DAAAM Baltic Industrial Engineering, 2012, pp. 268–273.
  • [7] A. Dhawan, R. Balasubramanian, and V. Vokkarane, “A framework for real-time monitoring of acoustic events using a wireless sensor network,” in Proc. IEEE Int. Conf. Technologies for Homeland Security (HST), 2011, pp. 254–261.
  • [8] T. Liu, Y. Liu, X. Cui, G. Xu, and D. Qian, “MOLTS: Mobile object localization and tracking system based on wireless sensor networks,” in Proc. IEEE 7th Int. Conf Networking, Architecture and Storage (NAS), 2012, pp. 245–251.
  • [9] Z. Merhi, M. Elgamel, and M. Bayoumi, “A lightweight collaborative fault tolerant target localization system for wireless sensor networks,” IEEE Transactions on Mobile Computing, vol. 8, no. 12, pp. 1690–1704, 2009.
  • [10] G. Vakulya and G. Simon, “Fast adaptive acoustic localization for sensor networks,” IEEE Transactions on Instrumentation and Measurement, vol. 60, no. 5, pp. 1820–1829, 2011.
  • [11] S. Astapov, J.-S. Preden, and J. Berdnikova, “Simplified acoustic localization by linear arrays for wireless sensor networks,” in Proc. 18th Int. Conf. on Digital Signal Processing (DSP), 2013, pp. 1–6.
  • [12] S. Astapov, J. Berdnikova, and J. S. Preden, “Optimized acoustic localization with SRP-PHAT for monitoring in distributed sensor networks,” International Journal of Electronics and Telecommunications, vol. 59, no. 4, pp. 383–390, 2013.
  • [13] Q. Wang, R. Zheng, A. Tirumala, X. Liu, and L. Sha, “Lightning: A hard real-time, fast, and lightweight low-end wireless sensor election protocol for acoustic event localization,” IEEE Transactions on Mobile Computing, vol. 7, no. 5, pp. 570–584, 2008.
  • [14] E. Mangas and A. Bilas, “FLASH: Fine-grained localization in wireless sensor networks using acoustic sound transmissions and high precision clock synchronization,” in Proc. 29th IEEE Int. Conf. Distributed Computing Systems ICDCS, 2009, pp. 289–298.
  • [15] H. Do, H. F. Silverman, and Y. Yu, “A real-time SRP-PHAT source location implementation using stochastic region contraction (SRC) on a large-aperture microphone array,” in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing ICASSP, vol. 1, 2007, pp. 121–124.
  • [16] C. T. Ishi, O. Chatot, H. Ishiguro, and N. Hagita, “Evaluation of a MUSIC-based real-time sound localization of multiple sound sources in real noisy environments,” in Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems IROS 2009, 2009, pp. 2027–2032.
  • [17] Y. Liu and Z. Yang, Location, Localization, and Localizability: Locationawareness Technology for Wireless Networks. Springer, 2010.
  • [18] D. Blatt and A. O. Hero, “Apocs: a rapidly convergent source localization algorithm for sensor networks,” in Proc. IEEE/SP 13th Workshop Statistical Signal Processing, 2005, pp. 1214–1219.
  • [19] Z. Merhi, M. Elgamel, and M. Bayoumi, “Acoustic target localization in sensor networks with FUZZYART,” in Proc. 50th Midwest Symp. Circuits and Systems MWSCAS 2007, 2007, pp. 1536–1539.
  • [20] J. S. Preden, J. Llinas, G. Rogova, R. Pahtma, and L. Motus, “On-line data validation in distributed data fusion,” in SPIE Defense, Security and Sensing, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV, vol. 8742, 2013, pp. 1–12.
  • [21] J. S. Preden, L. Motus, R. Pahtma, and M. Meriste, “Data exchange for shared situation awareness,” in 2012 IEEE Int. Multi-Disciplinary Conf. on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), March 2012, pp. 198–201.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b335e5e0-62c1-439c-b531-09f4d3bf713c
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