A Hybrid Localization Algorithm for Enhanced Accuracy and Robustness in Healthcare Systems
Keywords:
Hybrid localization, RSSI, Time of Arrival (ToA), Machine Learning, Healthcare, LocalizationAbstract
This paper presents a novel hybrid localization algorithm designed for healthcare systems, integrating Received Signal Strength Indicator (RSSI) and Time of Arrival (ToA) measurements with machine learning techniques. The algorithm aims to enhance the accuracy, robustness, and computational efficiency of sensor localization in dynamic healthcare environments. Experimental results demonstrate that the hybrid algorithm achieves a significantly lower localization error, averaging 0.5 meters, compared to traditional RSSI-only and ToA-only methods. The algorithm's rapid convergence and low computational time make it suitable for real-time applications. Additionally, its robustness to measurement noise, a common challenge in healthcare settings, underscores its reliability. This research underscores the potential of advanced localization technologies to improve patient monitoring, safety, and overall healthcare delivery, with future work poised to further enhance performance and adaptability.
References
T. Ahmad, "3D Localization Techniques for Wireless Sensor Networks," Ph.D. dissertation, Auckland Univ. of Technol., Auckland, New Zealand, 2019. Available from: https://hdl.handle.net/10292/12965
M. Riaz et al., "Secure and Fast Image Encryption Algorithm Based on Modified Logistic Map," Information, vol. 15, no. 3, p. 172, 2024. Available from: https://doi.org/10.3390/info15030172
T. Ahmad, X. J. Li, and B. C. Seet, "Parametric loop division for 3D localization in wireless sensor networks," Sensors, vol. 17, no. 7, p. 1697, 2017. Available from: https://doi.org/10.3390/s17071697
V. Rajendran, K. Obraczka, and J. J. Garcia-Luna-Aceves, "Energy-Efficient, Collision-Free Medium Access Control for Wireless Sensor Networks," in Proc. ACM SenSys '03, Los Angeles, CA, USA, Nov. 2003, pp. 181–192. Available from: https://doi.org/10.1145/958491.958513
L. Bao and J. J. Garcia-Luna-Aceves, "A New Approach to Channel Access Scheduling for Ad Hoc Networks," in Proc. 7th Ann. Int’l. Conf. Mobile Comp. and Net., 2001, pp. 210–221. Available from: https://doi.org/10.1145/381677.381698
T. Ahmad, X. J. Li, and B. C. Seet, "A self-calibrated centroid localization algorithm for indoor ZigBee WSNs," in Proc. 2016 8th IEEE Int. Conf. Commun. Softw. and Netw. (ICCSN), 2016, pp. 455-461. Available from: https://doi.org/10.1109/ICCSN.2016.7587200
P. Klosen, "Thirty-seven years of MT1 and MT2 melatonin receptor localization in the brain: Past and future challenges," J. Pineal Res., vol. 76, no. 3, p. e12955, 2024. Available from: https://doi.org/10.1111/jpi.12955
T. Ahmad, X. J. Li, and B. C. Seet, "3D localization based on parametric loop division and subdivision surfaces for wireless sensor networks," in Proc. 2016 25th Wireless and Optical Commun. Conf. (WOCC), 2016, pp. 1-6. Available from: https://doi.org/10.1109/WOCC.2016.7506540
Y. C. Tay, K. Jamieson, and H. Balakrishnan, "Collision Minimizing CSMA and Its Applications to Wireless Sensor Networks," IEEE J. Sel. Areas Commun., vol. 22, no. 6, pp. 1048–1057, Aug. 2004. Available from: https://doi.org/10.1109/JSAC.2004.830898
T. Ahmad, X. J. Li, and B. C. Seet, "3D localization using social network analysis for wireless sensor networks," in Proc. 2018 IEEE 3rd Int. Conf. Commun. and Inf. Syst. (ICCIS), 2018, pp. 88-92. Available from: https://doi.org/10.1109/ICOMIS.2018.8644742
J. H. Betzing, "Beacon-based customer tracking across the high street: perspectives for location-based smart services in retail," Ph.D. dissertation, 2018. Available from: https://aisel.aisnet.org/amcis2018/OrgTrasfm/Presentations/4/
T. Ahmad et al., "A Novel Self-Calibrated UWB Based Indoor Localization Systems for Context-Aware Applications," IEEE Trans. Consum. Electron., 2024. Available from: https://doi.org/10.1109/TCE.2024.3369193
H. Lu, "Ultrasonic Signal Design for Beacon-based Indoor Localization," Ph.D. dissertation, 2021. Available from: https://www.ideals.illinois.edu/items/118141
T. Ahmad, X. J. Li, B. C. Seet, and J. C. Cano, "Social Network Analysis Based Localization Technique with Clustered Closeness Centrality for 3D Wireless Sensor Networks," Electronics, vol. 9, no. 5, p. 738, 2020. Available from: https://doi.org/10.3390/electronics9050738
M. A. Khan, K. Muhammad, M. Sharif, T. Akram, and S. Kadry, "Intelligent fusion-assisted skin lesion localization and classification for smart healthcare," Neural Comput. Appl., vol. 36, no. 1, pp. 37-52, 2024. Available from: https://link.springer.com/article/10.1007/s00521-021-06490-w
J. Biswas, S. M. Mustaquim, S. S. Hossain, and I. M. Siddique, "Instantaneous Classification and Localization of Eye Diseases via Artificial Intelligence," Eur. J. Adv. Eng. Technol., vol. 11, no. 3, pp. 45-53, 2024. Available from: https://doi.org/10.5281/zenodo.10813807
J. Hightower and G. Borriello, "Location sensing techniques," IEEE Comput., vol. 34, no. 8, pp. 57-66, 2001. Available from: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=3a7cb58dec6c39d31db6c36aec6091e3149baaf6
M. A. Saleem et al., "Deep learning-based dynamic stable cluster head selection in VANET," J. Adv. Transp., vol. 2021, 2021. Available from: https://doi.org/10.1155/2021/9936299
K. Naheem and M. S. Kim, "A Robust Indoor Pedestrian Localization Approach Against Human Body Shadowing for UWB-Enabled Smartphones," IEEE Trans. Instrum. Meas., 2024. Available from: https://doi.org/10.1109/TIM.2024.3368497
M. R. Yuce, "Implementation of wireless body area networks for healthcare systems," Sens. Actuators A: Phys., vol. 162, no. 1, pp. 116-129, 2010. Available from: https://doi.org/10.1016/j.sna.2010.06.004
T. Ahmad et al., "A Novel Self-Calibrated UWB Based Indoor Localization Systems for Context-Aware Applications," IEEE Trans. Consum. Electron., 2024. Available from: https://doi.org/10.1109/TCE.2024.3369193
J. Lee, W. Chung, and E. Kim, "Robust DV-Hop algorithm for localization in wireless sensor network," in Proc. Int. Conf. Control, Autom. and Syst., Gyeonggi-do, South Korea, 2010, pp. 2506–2509. Available from: https://doi.org/10.1109/ICCAS.2010.5670294
Y. Liu, Z. Yang, X. Wang, and L. Jian, "Location, localization, and localizability," J. Comput. Sci. Technol., vol. 25, pp. 274-297, 2010. Available from: https://link.springer.com/article/10.1007/s11390-010-9324-2
S. He and S. H. G. Chan, "Wi-Fi fingerprint-based indoor positioning: Recent advances and comparisons," IEEE Commun. Surv. Tutor., vol. 18, no. 1, pp. 466-490, 2015. Available from: https://doi.org/10.1109/COMST.2015.2464084
T. Ahmad, X. J. Li, and B. C. Seet, "Noise Reduction Scheme for Parametric Loop Division 3D Wireless Localization Algorithm Based on Extended Kalman Filtering," J. Sens. Actuator Netw., vol. 8, no. 2, p. 24, 2019. Available from: https://doi.org/10.3390/jsan8020024
M. Murtaza, M. Sharif, M. AbdullahYasmin, and T. Ahmad, "Facial expression detection using six facial expressions hexagon (sfeh) model," in Proc. 2019 IEEE 9th Annu. Comput. and Commun. Workshop and Conf. (CCWC), 2019, pp. 0190-0195. Available from: https://doi.org/10.1109/CCWC.2019.8666602
T. Ahmad, X. J. Li, and B. C. Seet, "Fuzzy-Logic Based Localization for Mobile Sensor Networks," in Proc. 2019 2nd Int. Conf. Commun., Comput. and Digital Syst. (CCODE), 2019, pp. 43-47. Available from: https://doi.org/10.1109/C-CODE.2019.8681024
T. Ahmad, X. J. Li, A. K. Cherukuri, and K. I. Kim, "Hierarchical localization algorithm for sustainable ocean health in large-scale underwater wireless sensor networks," Sustain. Comput.: Informatics and Syst., vol. 39, p. 100902, 2023. Available from: https://doi.org/10.1016/j.suscom.2023.100902
M. I. U. Haq et al., "Robust graph-based localization for industrial Internet of things in the presence of flipping ambiguities," CAAI Trans. Intell. Technol., 2023. Available from: https://doi.org/10.1049/cit2.12203
T. Ahmad, X. J. Li, W. Jiang, and A. Ghaffar, "Frugal Sensing: A Novel approach of Mobile Sensor Network Localization based on Fuzzy-Logic," in Proc. ACM MobiArch 2020 The 15th Workshop on Mobility in the Evolving Internet Architecture, 2020, pp. 8-15. Available from: https://doi.org/10.1145/3411043.3412509
T. Ahmad et al., "Spark Spectrum Allocation for D2D Communication in Cellular Networks," CMC-Comput. Mater. Continua, vol. 70, no. 3, pp. 6381-6394, 2022. Available from: http://dx.doi.org/10.32604/cmc.2022.019787
Z. Wang, Ji, and H. Jin, "Improvement on APIT localization algorithms for wireless sensor networks," in Proc. 2009 Int. Conf. Netw. Security, Wireless Commun. and Trusted Comput., vol. 1, pp. 719-723. Available from: https://doi.org/10.1109/NSWCTC.2009.370
Z. Shah et al., "A New Generalized Logarithmic–X Family of Distributions with Biomedical Data Analysis," Appl. Sci., vol. 13, no. 6, p. 3668, 2023. Available from: https://doi.org/10.3390/app13063668
T. Ahmad, "An improved accelerated frame slotted ALOHA (AFSA) algorithm for tag collision in RFID," arXiv preprint arXiv:1405.6217, 2014. Available from: https://doi.org/10.48550/arXiv.1405.6217
Y. Wang, X. Wang, D. Wang, and D. P. Agrawal, "Range-free localization using expected hop progress in wireless sensor networks," IEEE Trans. Parallel Distrib. Syst., vol. 20, no. 10, pp. 1540–1552, 2009. Available from: https://doi.org/10.1109/TPDS.2008.239
Z. Shah et al., "A New Generalized Logarithmic–X Family of Distributions with Biomedical Data Analysis," Appl. Sci., vol. 13, no. 6, p. 3668, 2023. Available from: https://doi.org/10.3390/app13063668
