@techreport{oai:ipsj.ixsq.nii.ac.jp:00210948,
 author = {Yuanzhi, Huo and Pradini, Puspitaningayu and Kazushi, Hamazaki and Nobuo, Funabiki and Minoru, Kuribayashi and Kazuyuki, Kojima and Yuanzhi, Huo and Pradini, Puspitaningayu and Kazushi, Hamazaki and Nobuo, Funabiki and Minoru, Kuribayashi and Kazuyuki, Kojima},
 issue = {4},
 month = {May},
 note = {To achieve the high accuracy while wearing an inexpensive, tiny, and long-life transmitter, we have developed a fingerprint-based indoor localization system. It adopts IEEE802.15.4 devices and restricts the detection granularity to one room in an indoor environment. Unfortunately, wireless signals of the devices often fluctuate due to human movements and other uncontrollable factors. It has been observed that it can be solved by assigning plural fingerprints to one room. However, their values need to be properly selected. In this paper, we study the parameter optimization method for this indoor localization system. An existing parameter optimization tool is employed where the score function is newly defined to estimate the optimality of the current parameters. For evaluations, we apply the method to the measured data using the system in #2 Engineering Building of Okayama University. The results show that the detection accuracy becomes higher than 90% for any room by increasing the number of fingerprints and optimizing the parameter values by the proposal., To achieve the high accuracy while wearing an inexpensive, tiny, and long-life transmitter, we have developed a fingerprint-based indoor localization system. It adopts IEEE802.15.4 devices and restricts the detection granularity to one room in an indoor environment. Unfortunately, wireless signals of the devices often fluctuate due to human movements and other uncontrollable factors. It has been observed that it can be solved by assigning plural fingerprints to one room. However, their values need to be properly selected. In this paper, we study the parameter optimization method for this indoor localization system. An existing parameter optimization tool is employed where the score function is newly defined to estimate the optimality of the current parameters. For evaluations, we apply the method to the measured data using the system in #2 Engineering Building of Okayama University. The results show that the detection accuracy becomes higher than 90% for any room by increasing the number of fingerprints and optimizing the parameter values by the proposal.},
 title = {A Study of Parameter Optimization Method for Fingerprint-based Indoor Localization System Using IEEE 802.15.4 Devices},
 year = {2021}
}