Skip to main content

Abstract

The continuous technological upgradations in the RF (radio frequency), processors, nanotechnology, and microelectromechanical systems (MEMS) domains have fostered the growth of wireless sensor networks (WSN), which in turn allowed to develop a wide range applications based on it, for instance, the technological breakthrough in the semiconductor industry stimulated to produce low-power, low-cost, and small-sized processors with high computational capacities. Speaking in more clear words, the miniaturization of sensing and computing devices enabled the development of tiny, low-cost, and low-power sensors, controllers, and actuators. Basically WSNs consist of a large number of tiny and low-cost sensor nodes that are networked via low-power wireless communication links. These networks allow to closely observe ambient environment of interest at an economical cost much lower than other possible technological solutions. Each sensor node in WSN has sensing, communication, and computation capabilities. By exploiting appropriate advanced mesh networking protocols, these nodes form a sea of connectivity that covers the physical environmental area under observation. In WSN the transmitting node opt out possible communication paths by hopping sensed data of interest from node to node toward its destination. Although the capability of single sensor node is minimal, the composition of hundreds or thousands of such nodes offers very high new technological possibilities for wide variety of applications. The power of WSN lies in the possibility of heavy deployment of large numbers of tiny nodes, which can assemble and configure on their own. Stating in simple words, these nodes have networking capability, which facilitates coordination, cooperation, and collaboration among them to meet the requirements of the underlying application. The WSN can also provide a robust service in hostile or inaccessible environments, wherein human intervention may be too dangerous or almost not possible. This new technology is exciting with unlimited potential for numerous application areas, including environmental, medical, military, transportation, entertainment, crisis management, disaster relief operations, homeland defense, and smart spaces. It is envisioned that in the near future the WSN will be an integral as well as essential aspect of our lives.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Y. Zhang, L. Sun, H. Song, X. Cao, Ubiquitous WSN for healthcare: Recent advances and future prospects. IEEE Internet Things J. (2014). https://doi.org/10.1109/JIOT.2014.2329462

  2. S. Gezici et al., Localization via ultra-wideband radios: A look at positioning aspects of future sensor networks. IEEE Signal Process. Mag. (2005). https://doi.org/10.1109/MSP.2005.1458289

  3. I. F. Akyildiz, T. Melodia, K. R. Chowdhury, A survey on wireless multimedia sensor networks. Comput. Netw. 51(4) (2007). https://doi.org/10.1016/j.comnet.2006.10.002

  4. I. Khemapech, I. Duncan, A Miller, A survey of wireless sensor networks technology, in 6th Annual Postgraduate Symposium on the Convergence of Telecommunications, Networking and Broadcasting, vol. 6 (2005)

    Google Scholar 

  5. W. Dargie, C. Poellabauer, Fundamentals of Wireless Sensor Networks: Theory and Practice (Wiley, New York, 2011)

    Google Scholar 

  6. G. Xu, W. Shen, X. Wang, Applications of wireless sensor networks in marine environment monitoring: a survey. Sensors (Switzerland) 14(9) (2014). https://doi.org/10.3390/s140916932

  7. P. Kumar, H. J. Lee, Security issues in healthcare applications using wireless medical sensor networks: a survey. Sensors 12(1) (2012). https://doi.org/10.3390/s120100055

  8. B. Rashid, M. H. Rehmani, Applications of wireless sensor networks for urban areas: a survey. J. Netw. Comput. Appl. 60 (2016). https://doi.org/10.1016/j.jnca.2015.09.008

  9. S. R. Jondhale, R. S. Deshpande, GRNN and KF framework based real time target tracking using PSOC BLE and smartphone. Ad Hoc Netw. (2019). https://doi.org/10.1016/j.adhoc.2018.09.017

  10. S. R. Jondhale, R. S. Deshpande, Kalman filtering framework-based real time target tracking in wireless sensor networks using generalized regression neural networks. IEEE Sensors J. (2019). https://doi.org/10.1109/JSEN.2018.2873357

  11. S. Jondhale, R. Deshpande, Self recurrent neural network based target tracking in wireless sensor network using state observer. Int. J. Sensors Wirel. Commun. Control (2018). https://doi.org/10.2174/2210327908666181029103202

  12. S. R. Jondhale, R. S. Deshpande, Modified Kalman filtering framework based real time target tracking against environmental dynamicity in wireless sensor networks. Ad Hoc Sens. Wirel. Netw. 40(1–2), 119–143 (2018)

    Google Scholar 

  13. M. Zhou, Q. Zhang, Z. Tian, F. Qiu, Q. Wu, Integrated location fingerprinting and physical neighborhood for WLAN probabilistic localization, in Fifth International Conference on Computing, Communications and Networking Technologies (ICCCNT) (2014). https://doi.org/10.1109/ICCCNT.2014.6963028

  14. R. S. Campos, L. Lovisolo, M. L. R. De Campos, Wi-Fi multi-floor indoor positioning considering architectural aspects and controlled computational complexity. Expert Syst. Appl. (2014). https://doi.org/10.1016/j.eswa.2014.04.011

  15. A. Payal, C. S. Rai, B. V. R. Reddy, Artificial neural networks for developing localization framework in wireless sensor networks, in 2014 International Conference on Data Mining and Intelligent Computing (ICDMIC) (2014). https://doi.org/10.1109/ICDMIC.2014.6954228

  16. M. Anand, T. Sasikala, Efficient energy optimization in mobile ad hoc network (MANET) using better-quality AODV protocol. Cluster Comput. 22 (2019). https://doi.org/10.1007/s10586-018-1721-2

  17. C. Feng, W. S. A. Au, S. Valaee, Z. Tan, Received-signal-strength-based indoor positioning using compressive sensing. IEEE Trans. Mob. Comput. (2012). https://doi.org/10.1109/TMC.2011.216

  18. S. R. Jondhale, R. S. Deshpande, S. M. Walke, A. S. Jondhale, Issues and challenges in RSSI based target localization and tracking in wireless sensor networks, in 2016 International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT) (2017). https://doi.org/10.1109/ICACDOT.2016.7877655

  19. S. R. Jondhale, R. S. Deshpande, Tracking target with constant acceleration motion using Kalman Filtering, in 2018 International Conference On Advances in Communication and Computing Technology (ICACCT) (2018). https://doi.org/10.1109/ICACCT.2018.8529628

  20. N. Patwari, J. N. Ash, S. Kyperountas, A. O. Hero, R. L. Moses, N. S. Correal, Locating the nodes: Cooperative localization in wireless sensor networks. IEEE Signal Process. Mag. (2005). https://doi.org/10.1109/MSP.2005.1458287

  21. S. Kumar and S. Lee, Localization with RSSI values for wireless sensor networks: an artificial neural network approach. Int. J. Comput. Netw. Commun. (2014). https://doi.org/10.3390/ecsa-1-d007

  22. Z. Chen, Q. Zhu, and Y. C. Soh, Smartphone inertial sensor-based indoor localization and tracking with iBeacon corrections. IEEE Trans. Ind. Inf. (2016). https://doi.org/10.1109/TII.2016.2579265

  23. L. Mihaylova, D. Angelova, D. R. Bull, N. Canagarajah, Localization of mobile nodes in wireless networks with correlated in time measurement noise. IEEE Trans. Mob. Comput. (2011). https://doi.org/10.1109/TMC.2010.132

  24. A. El-Rabbany, Introduction to GPS: the global position system (Artech House, London, 2006)

    Google Scholar 

  25. P. A. Zandbergen, S. J. Barbeau, Positional accuracy of assisted GPS data from high-sensitivity GPS-enabled mobile phones. J. Navig. (2011). https://doi.org/10.1017/S0373463311000051

  26. M. B. Higgins, Heighting with GPS: possibilities and limitations, in Comm. 5 Int. Fed. Surv. (1999)

    Google Scholar 

  27. Z. Bin Tariq, D. M. Cheema, M. Z. Kamran, I. H. Naqvi, Non-GPS positioning systems. ACM Comput. Surv. (2017). https://doi.org/10.1145/3098207

  28. F. Viani, M. Bertolli, M. Salucci, A. Polo, Low-cost wireless monitoring and decision support for water saving in agriculture. IEEE Sensors J (2017). https://doi.org/10.1109/JSEN.2017.2705043

  29. R. Faragher, R. Harle, Location fingerprinting with bluetooth low energy beacons. IEEE J. Sel. Areas Commun. (2015). https://doi.org/10.1109/JSAC.2015.2430281

  30. M. H. Anisi, G. Abdul-Salaam, A. H. Abdullah, A survey of wireless sensor network approaches and their energy consumption for monitoring farm fields in precision agriculture. Precis. Agric. (2015). https://doi.org/10.1007/s11119-014-9371-8

  31. P. Abouzar, D. G. Michelson, M. Hamdi, RSSI-based distributed self-localization for wireless sensor networks used in precision agriculture. IEEE Trans. Wirel. Commun. (2016), https://doi.org/10.1109/TWC.2016.2586844

  32. J. Yick, B. Mukherjee, D. Ghosal, Wireless sensor network survey. Comput. Netw. (2008). https://doi.org/10.1016/j.comnet.2008.04.002

  33. R. Silva, J. Sa Silva, F. Boavida, Mobility in wireless sensor networks - survey and proposal. Comput. Commun. (2014). https://doi.org/10.1016/j.comcom.2014.05.008

  34. V. C. Paterna, A. C. Augé, J. P. Aspas, M. A. P. Bullones, A bluetooth low energy indoor positioning system with channel diversity, weighted trilateration and kalman filtering. Sensors (Switzerland) (2017). https://doi.org/10.3390/s17122927

  35. Y.W. Prakash, V. Biradar, S. Vincent, M. Martin, A. Jadhav, Smart bluetooth low energy security system (2018). https://doi.org/10.1109/WiSPNET.2017.8300139

    Book  Google Scholar 

  36. M. S. Pan, Y. C. Tseng, ZigBee wireless sensor networks and their applications. Sens. Netw. Config. Fundam. Stand. Platforms Appl. (2007). https://doi.org/10.1007/3-540-37366-7_16

  37. M. R. Mohd Kassim, I. Mat, A. N. Harun, Wireless sensor network in precision agriculture application, in 2014 International Conference on Computer, Information and Telecommunication Systems (CITS) (2014). https://doi.org/10.1109/CITS.2014.6878963

  38. A. Minaie, Application of wireless sensor networks in health care system application of wireless sensor networks in health care system, in ASEE Annual Conference and Exposition (2013)

    Google Scholar 

  39. R. J. F. Rossetti, Internet of Things (IoT) and smart cities, in IEEE Readings Smart Cities (2015)

    Google Scholar 

  40. A. Zanella, Best practice in RSS measurements and ranging. IEEE Commun. Surv. Tutorials (2016). https://doi.org/10.1109/COMST.2016.2553452

  41. B. Latré, B. Braem, I. Moerman, C. Blondia, P. Demeester, A survey on wireless body area networks. Wirel. Netw. (2011). https://doi.org/10.1007/s11276-010-0252-4

  42. F. Viani, P. Rocca, G. Oliveri, D. Trinchero, A. Massa, Localization, tracking, and imaging of targets in wireless sensor networks: an invited review. Radio Sci. (2011). https://doi.org/10.1029/2010RS004561

  43. D. M. Han, J. H. Lim, Smart home energy management system using IEEE 802.15.4 and zigbee. IEEE Trans. Consum. Electron. (2010). https://doi.org/10.1109/TCE.2010.5606276

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Jondhale, S.R., Maheswar, R., Lloret, J. (2022). Fundamentals of Wireless Sensor Networks. In: Received Signal Strength Based Target Localization and Tracking Using Wireless Sensor Networks. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-74061-0_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-74061-0_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-74060-3

  • Online ISBN: 978-3-030-74061-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics