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RSSI Based Localization and Tracking in a Spatial Network System using Wireless Sensor Networks

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Abstract

Localization has been a major research area in Wireless Sensor Networks \(\left( {WSN} \right)\) and has a rich literature of using many methods to estimate location accuracy. In \(WSN\), localization systems use data from sensors which receive signals from beacons. The information received from a sensor node provides data about the location in the sequence. So it must be accurately estimated in a networked transportation system since the movement of data in the system involves both time and space coordinates. To estimate the location of the unknown nodes, wused the Received Signal Strength Indicator (RSSI), available on all wireless sensor nodes. The algorithm has been deloped to reduce the effect of non-deterministic delays using site-specific empirical models to achieve good location accuracy. As a measure of the propagation time of packets to reduce synchronization error, all nodes are synchronized using Round Trip Time and provide an accurate estimation of the node in time scale. Also, this paper describes the signal intensity based Extended Kalman filter for tracking a dynamically moving object from the optimized value of \(RSSI\). Our method is compared with the existing methods and proved to be better under various circumstances of localization and tracking.

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The data that supports the findings of this study are available on request from the corresponding author. The data is not publicly available due to containing information that could compromise the privacy of research participants.

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The code that supports the findings of this study are available on request from the corresponding author. The code is not publicly available due to containing information that could compromise the privacy of research participants.

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Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. School of Computing, SRM University, Chennai, India

    Amutha Balakrishnan & Karthick Nanmaran

  2. Department of Artificial Intelligence and Data Science, Annamacharya Institute of Technology and Sciences, Rajampet, Andhra Pradesh, India

    Kadiyala Ramana

  3. School of Computing, SASTRA Deemed University, Thanjavur, India

    Manikandan Ramachandran

  4. Department of Electrical and Computer Engineering, San Francisco State University, San Francisco, CA, 94132, USA

    Vidhyacharan Bhaskar

  5. Department of Computer Science and Engineering, Sree Vidyanikethan Engineering College, Tirupati, AP-517102, India

    Suresh Kallam

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  1. Amutha Balakrishnan
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  2. Kadiyala Ramana
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  4. Manikandan Ramachandran
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  5. Vidhyacharan Bhaskar
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Contributions

AB: Conceptualization, Methodology, Software, Visualization KR: Data curation, Writing—original draft, Data Analysis, Investigation. KN: Software, Validation, Editing. MR: Software, Validation, Editing. VCB: Supervision, Writing—review and editing. SK: Software, Validation, Editing.

Corresponding author

Correspondence to Vidhyacharan Bhaskar.

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Balakrishnan, A., Ramana, K., Nanmaran, K. et al. RSSI Based Localization and Tracking in a Spatial Network System using Wireless Sensor Networks. Wireless Pers Commun 123, 879–915 (2022). https://doi.org/10.1007/s11277-021-09161-0

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