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Optimization of sensor node location utilizing artificial intelligence for mobile wireless sensor network

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Abstract

Physical activity can be monitored via small low-power sensor nodes (SNs) that are widely dispersed over the earth. For WSN sensor nodes, GPS is one of the most commonly utilised localization algorithms. Military, industrial, and more recently, consumer and civil uses of GPS are all examples of its vast range of applications. Wi-Fi enabled smart sensors are the product of a combination of WSNs and embedded intelligent sensor structures. Building smart sensor systems relies heavily on AI methods. An innovative Hybrid DA-FA and several meta-heuristics are compared in this research paper as initial contribution. A single anchor node meta-heuristic algorithm is suggested to determine the location of a node using a range-based approach. In contrast to the randomly moving target nodes, the anchor node is fixed in the middle of the region. Line-of-Sight difficulties can now be alleviated to a greater extent thanks to the introduction of virtual anchor nodes. They have shown a significant improvement in localization accuracy and rapid convergence in mobility-based scenarios with a reduced number of anchor nodes. A comparison of the accuracy, localization error, and other metrics of both methods is included in the new approach. We have evaluated the DA-FA techniques performance for maximum error which is reduced to 21.53% in comparison of existing approach. However, the minimum error is reduced to 3.91%.

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Funding

The authors are thankful to the Deanship of Scientific Research at Najran University for funding this work under the Research Priorities and Najran Research funding program grant code NU/NRP/SERC/12/38.

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Authors and Affiliations

  1. Information Systems Department, College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia

    Mesfer Alrizq

  2. Department of Information Technology, Indian Institute of Information Technology (IIIT), Bhopal, 462003, Madhya Pradesh, India

    Shalini Stalin

  3. Computer Science Department, College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia

    Sultan Alyami

  4. Department of Electronics & Communication Engineering, Gyan Ganga Institute of Technology and Sciences, Jabalpur, Madhya Pradesh, India

    Vandana Roy

  5. IES College of Technology, Kolar Road, Bhopal, Madhya Pradesh, India

    Anuprita Mishra

  6. Department of Computer Science and Information Technology, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, Chhattisgarh, India

    Amit Kumar Chandanan

  7. Department of Computer and Information Systems, Sadat Academy for Management Sciences, Cairo, 11742, Egypt

    Nancy Awadallah Awad

  8. Department of Electrical and Electronics, NITTE Meenakshi Institute of Technology, Bangalore, Karnataka, India

    Prashanth Venkatesh

Authors
  1. Mesfer Alrizq
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  2. Shalini Stalin
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  3. Sultan Alyami
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  4. Vandana Roy
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  5. Anuprita Mishra
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  6. Amit Kumar Chandanan
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  7. Nancy Awadallah Awad
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  8. Prashanth Venkatesh
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Contributions

All author is contributed to the design and methodology of this study, the assessment of the outcomes and the writing of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Shalini Stalin.

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Alrizq, M., Stalin, S., Alyami, S. et al. Optimization of sensor node location utilizing artificial intelligence for mobile wireless sensor network. Wireless Netw 30, 6619–6631 (2024). https://doi.org/10.1007/s11276-023-03469-4

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