Authors : Jerome Jayanathan Needhipathi; Akhil Duvvuru

Volume/Issue : Volume 10 - 2025, Issue 4 - April

Google Scholar : https://tinyurl.com/2ndjct5u

Scribd : https://tinyurl.com/4dd973tc

DOI : https://doi.org/10.38124/ijisrt/25apr1325

Google Scholar

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Note : Google Scholar may take 15 to 20 days to display the article.

Abstract : Embedded sensors and wireless networks have experienced substantial advancements in their design use throughout recent years. Advanced sensors with wireless connectivity foster new application systems that improve individuals' daily functions and independence and enhance their life quality. A detailed study about Wi-Fi-based monitoring systems for smart conference management appears in this article to improve visitor experience while enhancing event operation efficiency and providing exhibitors and organizers with data possibilities. The solution uses current Wi-Fi infrastructure to enable immediate monitoring of visitors as they move through the event space without asking them for any active involvement. The information collection enables strategic trade show sectioning as well as resource distribution decisions while enabling stands and crowd control measures and exhibitor-specific feedback that leads to better market engagement and operational performance. The research investigates essential privacy and ethical aspects by concentrating on anonymous data handling and clear visibility and adherence to privacy rules. Events monitoring through Wi-Fi systems proves to be an advantageous solution for modern event management which delivers benefits to exhibitors together with attendees and organizers.

Keywords : Wi-Fi-Based Monitoring, Smart Conference Management, Visitor Experience, Privacy and Ethics, Event Operation Efficiency.

References :

1. N. Hernández, M. Ocaña, J. Alonso, and E. Kim, “WiFi-based indoor localization and tracking of a moving device,” in 2014 Ubiquitous Positioning Indoor Navigation and Location Based Service, UPINLBS 2014 - Conference Proceedings, 2014. doi: 10.1109/UPINLBS.2014.7033738.
2. M. Vega-Barbas, M. Álvarez-Campana, D. Rivera, M. Sanz, and J. Berrocal, “Aforos: A low-cost wi-fi-based monitoring system for estimating occupancy of public spaces,” Sensors, 2021, doi: 10.3390/s21113863.
3. M. Ribeiro, N. Nunes, V. Nisi, and J. Schöning, “Passive Wi-Fi monitoring in the wild: a long-term study across multiple location typologies,” Pers. Ubiquitous Comput., 2022, doi: 10.1007/s00779-020-01441-z.
4. Y. Lin, Q. Li, D. Lyu, and X. Wang, “A Review of Wi-Fi-Based Traffic Detection Technology in the Field of Intelligent Transportation Systems,” 2022. doi: 10.3390/buildings12040428.
5. A. Abedi and D. Vasisht, “Non-cooperative wi-fi localization and its privacy implications,” Proc. Annu. Int. Conf. Mob. Comput. Networking, MOBICOM, pp. 570–582, 2022, doi: 10.1145/3495243.3560530.
6. I. V. Korogodir, V. V. Dneprov, and O. K. Mikhaylova, “Triangulation Positioning by Means of Wi-Fi Signals in Indoor Conditions,” in Progress in Electromagnetics Research Symposium, 2019. doi: 10.1109/PIERS-Spring46901.2019.9017863.
7. F. Liu et al., “Survey on WiFi-based indoor positioning techniques,” 2020. doi: 10.1049/iet-com.2019.1059.
8. H. Liu, H. Darabi, P. Banerjee, and J. Liu, “Survey of wireless indoor positioning techniques and systems,” 2007. doi: 10.1109/TSMCC.2007.905750.
9. V. Honkavirta, T. Perälä, S. Ali-Löytty, and R. Piché, “A comparative survey of WLAN location fingerprinting methods,” in Proceedings - 6th Workshop on Positioning, Navigation and Communication, WPNC 2009, 2009. doi: 10.1109/WPNC.2009.4907834.
10. A. Mingkhwan, “WI-FI tracker: An organization WI-FI tracking system,” Can. Conf. Electr. Comput. Eng., no. May, pp. 231–234, 2006, doi: 10.1109/CCECE.2006.277387.
11. P. Roy and C. Chowdhury, “A survey on ubiquitous WiFi-based indoor localization system for smartphone users from implementation perspectives,” CCF Trans. Pervasive Comput. Interact., 2022, doi: 10.1007/s42486-022-00089-3.
12. M. F. Mosleh, M. J. Zaiter, and A. H. Hashim, “Enhanced Distance Utilized ToA/RSS to Estimate Position using Trilateration in Outdoor,” IOP Conf. Ser. Mater. Sci. Eng., 2021, doi: 10.1088/1757-899x/1105/1/012023.
13. V. Prajapati, “Integrating Blockchain for Vendor Coordination and Agile Scrum in Efficient Project Execution,” Int. J. Innov. Sci. Res. Technol., vol. 10, no. 3, 2025.
14. A. Goyal, “Integrating Blockchain for Vendor Coordination and Agile Scrum in Efficient Project Execution,” Int. J. Innov. Sci. Res. Technol., vol. 9, no. 12, 2024.
15. V. S. Thokala, “Improving Data Security and Privacy in Web Applications : A Study of Serverless Architecture,” Int. Res. J., vol. 11, no. 12, pp. 74–82, 2024.
16. Suhag Pandya, “Innovative blockchain solutions for enhanced security and verifiability of academic credentials,” Int. J. Sci. Res. Arch., vol. 6, no. 1, pp. 347–357, Jun. 2022, doi: 10.30574/ijsra.2022.6.1.0225.
17. H. Hussien, Y. Shiferaw, and N. Teshale, “Survey on Indoor Positioning Techniques and Systems,” 2018, pp. 46–55. doi: 10.1007/978-3-319-95153-9_5.
18. V. Panchal, “Energy-Efficient Core Design for Mobile Processors : Balancing Power and Performance,” pp. 191–201, 2024.
19. J. Dai, M. Wang, B. Wu, J. Shen, and X. Wang, “A Survey of Latest Wi-Fi Assisted Indoor Positioning on Different Principles,” 2023. doi: 10.3390/s23187961.
20. S. Arora and S. R. Thota, “Ethical Considerations and Privacy in AI-Driven Big Data Analytics,” Int. Res. J. Eng. Technol., vol. 11, no. 05, 2024.
21. S. Singh, “Enhancing Observability and Reliability in Wireless Networks with Service Mesh Technologies,” Int. J. Adv. Res. Sci. Commun. Technol., vol. 5, no. 1, 2025, doi: 10.48175/568.
22. P. Piyush, A. A. Waoo, M. P. Singh, P. K. Pareek, S. Kamal, and S. V. Pandit, “Strategizing IoT Network Layer Security Through Advanced Intrusion Detection Systems and AI-Driven Threat Analysis,” J. Intell. Syst. Internet Things, vol. 24, no. 2, pp. 195–207, 2024, doi: 10.54216/JISIoT.120215.
23. T. Bravenec, M. Gould, T. Fryza, and J. Torres-Sospedra, “Influence of Measured Radio Map Interpolation on Indoor Positioning Algorithms,” IEEE Sens. J., 2023, doi: 10.1109/JSEN.2023.3296752.
24. T. Simelane, T. N. D. Mathaba, and T. O. Otunniyi, “A Review Paper: Indoor Positioning Systems Using Radio Frequency Technology,” in International Conference on Electrical, Computer and Energy Technologies, ICECET 2023, 2023. doi: 10.1109/ICECET58911.2023.10389298.
25. Y. Narita, S. Lu, and H. Kamabe, “Accuracy Evaluation of Indoor Positioning by Received Signal Strength using Deep Learning,” in International Conference on Advanced Communication Technology, ICACT, 2022. doi: 10.23919/ICACT53585.2022.9728858.
26. I. Strelkovskaya, I. Solovskaya, and J. Strelkovska, “The use of Linear Complex Planar Splines to Improve the Accuracy of Determining the location of the User in Wi-Fi/Indoor Networks,” in 2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology, PIC S and T 2021 - Proceedings, 2021. doi: 10.1109/PICST54195.2021.9772175.
27. H. Didden, Y. Sikka, and M. Kakkar, “Android based wireless positioning system,” in Proceedings of the Confluence 2020 - 10th International Conference on Cloud Computing, Data Science and Engineering, 2020. doi: 10.1109/Confluence47617.2020.9058144.
28. S. Jahagirdar, A. Ghatak, and A. A. Kumar, “WiFi based Indoor Positioning System using Machine Learning and Multi-Node Triangulation Algorithms,” in 2020 11th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2020, 2020. doi: 10.1109/ICCCNT49239.2020.9225350.