| Title |
An Empirical Analysis Of Fingerprinting Based Device-Free Localization Using Iot |
| ID_Doc |
7944 |
| Authors |
Karthikeyan K.; Radhika M.; Sivaprakash K.; Sarayu E. |
| Year |
2022 |
| Published |
8th International Conference on Advanced Computing and Communication Systems, ICACCS 2022 |
| DOI |
http://dx.doi.org/10.1109/ICACCS54159.2022.9785230 |
| Abstract |
Device-free localization (DFL) is not an evolving technology for assessing a person or object's position that is not fitted with any electronic chip, nor is it directly involved in the process of place. Motivated by the recent developments in the Internet of Things (IoT), the device-free calibration method in IoT environments automatically creates a device-free fingerprint. Accurate localization has been a key concern for numerous location-based services. Growing attention has recently been drawn to research on IoT localization systems for smart cities. Localization using the current wireless communication system is seen as a high-potential, efficient process. IoT-based approaches to fingerprinting have recently gained prominence. Finally, a comprehensive and detailed site survey process is required to construct the fingerprint using device-free localization. To address this problem, an effort was made to review the theory behind device-free localization and various machine learning frameworks developed. © 2022 IEEE. |
| Author Keywords |
Device-free localization; Fingerprint; IoT; Logistic Regression; Naive Bayes; SVM |
