volume | PIER Journals

2023-11-03

Measurement and Prediction of Signal Strength of Wireless Sensor Network

Li Yang Foong,

Mr. Li Yang Foong

University of Nottingham Malaysia

Malaysia

Homepage

Soo Yong Lim,

Dr. Soo Yong Lim

Department of Electrical and Electronic Engineering

University of Nottingham Malaysia

Malaysia

Homepage

Kheong Sann Chan

Dr. Kheong Sann Chan

University of Nottingham Malaysia

Malaysia

Homepage

Progress In Electromagnetics Research M, Vol. 120, 145-154, 2023

doi:10.2528/PIERM23070301

Abstract

This paper utilizes an efficient prediction model using the concept of ray-tracing based on the Theory of Geometrical Optics (GO) to predict the signal strength between two wireless sensor nodes within an indoor environment, which can provide aid to designers in the implementation of Wireless Sensor Networks (WSNs). WSN is a technology that is widely used for functions such as collecting and processing data, then transmit it wirelessly within the network. WSNs are typically autonomous and self-organizing networks of nodes that communicate wirelessly with each other and collaborate to perform tasks such as data processing, sensing, aggregation, and forwarding. With the increasing prevalence of WSNs in indoor environments, installations of numerous sensor nodes are necessary to collect and transmit data in certain areas, which builds up to a single network. Thus, to ensure the functionality of the WSNs, it is of utmost importance to ensure a reliable connection between the nodes, which is directly affected by its location and placement. The prediction model developed in this work is built using MATLAB software, which is then implemented into a Graphical User Interface (GUI) using MATLAB App Designer, which allows modifications to be made to the prediction model as to fit the user’s environment. The results of our prediction model are compared against experimental ones obtained through physical measurements using wireless communications technologies such as ZigBee and Bluetooth Low Energy (BLE).

Citation

Copy Export

Li Yang Foong, Soo Yong Lim, and Kheong Sann Chan, "Measurement and Prediction of Signal Strength of Wireless Sensor Network," Progress In Electromagnetics Research M, Vol. 120, 145-154, 2023.
doi:10.2528/PIERM23070301

References

1. Kocakulak, M. and I. Butun, "An overview of Wireless Sensor Networks towards internet of things," 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), 1-6, Las Vegas, NV, USA, 2017.

2. El-Maghrabi, H. M., "A standard ray tracing technique for predicting signal strength of wireless sensor network in smart building," Progress In Electromagnetics Research Letters, Vol. 105, 79-84, 2022.
doi:10.2528/PIERL22052504

3. Ashok Somani, N., "Zigbee: A low power wireless technology for industrial applications," Int. J. Control Theory Comput. Model., Vol. 2, No. 3, 27-33, May 2012.

4. Mahmood, M. A., W. K. G. Seah, and I. Welch, "Reliability in wireless sensor networks: A survey and challenges ahead," Comput. Networks, Vol. 79, 166-187, Mar. 2015.
doi:10.1016/j.comnet.2014.12.016

5. Kurt, S. and B. Tavli, "Path-loss modeling for wireless sensor networks: A review of models and comparative evaluations," IEEE Antennas and Propagation Magazine, Vol. 59, No. 1, 18-37, Feb. 2017.
doi:10.1109/MAP.2016.2630035

6. Laaraiedh, M., et al., "Ray tracing-based radio propagation modeling for indoor localization purposes," 2012 IEEE 17th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2012, 276-280, 2012.

7. Ramya, C. M., M. Shanmugaraj, and R. Prabakaran, "Study on ZigBee technology," ICECT 2011 — 2011 3rd International Conference on Electronics Computer Technology, Vol. 6, 297-301, 2011.

8. Vishnubhotla, R., et al., "ZigBee based multi-level parking vacancy monitoring system," 2010 IEEE International Conference on Electro/Information Technology, 1-4, Normal, IL, USA, 2010.

9. Sakphrom, S., K. Suwannarat, R. Haiges, and K. Funsian, "A simplified and high accuracy algorithm of RSSI-based localization zoning for children tracking in-out the school buses using bluetooth low energy beacon," Informatics, Vol. 8, No. 4, Dec. 2021.
doi:10.3390/informatics8040065

10. Nair, K., J. Kulkarni, M. Warde, et al. "Optimizing power consumption in IOT based wireless sensor networks using Bluetooth Low Energy," Proceedings of the 2015 International Conference on Green Computing and Internet of Things, ICGCIoT 2015, 589-593, Jan. 2016.

11. Darroudi, S. M. and C. Gomez, "Bluetooth low energy mesh networks: A survey," Sensors (Switzerland), Vol. 17, No. 7, MDPI AG, Jul. 01, 2017.

12. Lim, S. Y., Z. Yun, and M. F. Iskander, "Radio propagation modeling: A unified view of the raytracing image method across emerging indoor and outdoor environments," The World of Applied Electromagnetics, 301-328, Springer International Publishing, Cham, 2018.

13. Yun, Z. and M. F. Iskander, "Ray tracing for radio propagation modeling: Principles and applications," IEEE Access, Vol. 3, 1089-1100, Institute of Electrical and Electronics Engineers Inc., 2015.

14. Iskander, M. F., "Oblique incidence plane wave reflection and transmission," Electromagnetic Fields and Waves. Prospect Heights, 436-479, Waveland Pr Inc., Illinois, 2000.

15. Zhang, Y. and S. Y. Lim, "An investigation into the diffraction effects of building FAC¸ADE for propagation modelling," Progress In Electromagnetics Research M, Vol. 97, 25-34, 2020.

16. "IEEE standard for low-rate wireless networks," IEEE Std 802.15.4-2020 (Revision of IEEE Std 802.15.4-2015), 1-800, 2020.