Optimal Wi-Fi access point placement for RSSI-based indoor localization using genetic algorithm

2017 ◽  
Author(s):  
Abdulsalam Alsmady ◽  
Fahed Awad
Keyword(s):  
Genetic Algorithm ◽  
Indoor Localization ◽  
Access Point ◽  
Point Placement

scholarly journals A Generative Method for Indoor Localization Using Wi-Fi Fingerprinting

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2392
Author(s):  
Óscar Belmonte-Fernández ◽  
Emilio Sansano-Sansano ◽  
Antonio Caballer-Miedes ◽  
Raúl Montoliu ◽  
Rubén García-Vidal ◽  
...  
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Indoor Localization ◽  
Hidden Markov ◽  
Signal Strength ◽  
Access Point ◽  
Received Signal Strength ◽  
Machine Learning Algorithms ◽  
Forward Algorithm ◽  
Generative Method

Indoor localization is an enabling technology for pervasive and mobile computing applications. Although different technologies have been proposed for indoor localization, Wi-Fi fingerprinting is one of the most used techniques due to the pervasiveness of Wi-Fi technology. Most Wi-Fi fingerprinting localization methods presented in the literature are discriminative methods. We present a generative method for indoor localization based on Wi-Fi fingerprinting. The Received Signal Strength Indicator received from a Wireless Access Point is modeled by a hidden Markov model. Unlike other algorithms, the use of a hidden Markov model allows ours to take advantage of the temporal autocorrelation present in the Wi-Fi signal. The algorithm estimates the user’s location based on the hidden Markov model, which models the signal and the forward algorithm to determine the likelihood of a given time series of Received Signal Strength Indicators. The proposed method was compared with four other well-known Machine Learning algorithms through extensive experimentation with data collected in real scenarios. The proposed method obtained competitive results in most scenarios tested and was the best method in 17 of 60 experiments performed.

scholarly journals One Slope Model: Efforts to Optimize Wifi Networks in the Office of communication and informatics in Palembang

2020 ◽  
Vol 2 (1) ◽  
pp. 23-32
Author(s):  
Winda Wulandari ◽  
Ari Muzakir
Keyword(s):  
Network Performance ◽  
Access Point ◽  
Wifi Networks ◽  
Coverage Area ◽  
Propagation Models ◽  
Existing Problems ◽  
The One ◽  
The City ◽  
Point Placement

Information technology in the field of transmission that is currently developing, one of which is Wi-Fi. Wi-Fi devices provide user convenience in carrying out their activities. The quality of Wi-Fi network performance can be known by the reception of the signal received by the user. If the placement of an access point (AP) is done correctly, the network will be optimized. There are several propagation models in the room that can be used as a guideline in determining the placement of the AP, one slope model is a way to measure the average level of a building and only depends on the distance of the transmitter and receiver. This research was conducted in order to overcome the problem of Wi-Fi network area coverage at the Office of Communication and Information of the City of Palembang. This study conducted an experiment to change the layout of AP's placement, measure and calculate data in priority with the one slope model. The results of measurements and calculations carried out analysis and comparison in order to determine the results of the experiments conducted. The results of this study indicate that an attempt to change the AP layout with one slope model can overcome existing problems and get better Wi-Fi coverage area performance. In the calculation with the one slope model of the 2-trial access point placement results in a decrease and an increase in signal. The signal reduction occurred in experiment 1, whereas in experiment 2 (design 2) the signal increased by 1.46dBm.

scholarly journals Access Point Placement Recommendation Using Cost-231 Multiwall Propagation

2020 ◽  
Vol 10 (2) ◽  
pp. 103
Author(s):  
Fransiska Sisilia Mukti
Keyword(s):  
Wave Propagation ◽  
Distribution Pattern ◽  
Radio Wave ◽  
Signal Strength ◽  
Access Point ◽  
Propagation Model ◽  
Radio Wave Propagation ◽  
Signal Distribution ◽  
Point Placement

<p class="JGI-AbstractIsi">This study provides an overview of signal distribution pattern using Cost-231 Multi-Wall (MWM) propagation model. The signal distribution pattern is used as a reference in projecting indoor Access Points (AP) placement in Malang Institute of Asia. The MWM approach estimates the actual radio wave propagation value for measurements are made by considering obstacles between APs and user devices. The study recommends 10 optimal points of AP placement for the 1st, 3rd and 4th-floors, and 7 optimal points for the 2nd-floor. Determination of these placement points was based on the estimated signal strength obtained by users, at -50dBM up to - 10dBm, which is the range for good and excellent signal category.</p>

scholarly journals An Efficient Indoor Wi-Fi Positioning Method Using Virtual Location of AP

2020 ◽  
Vol 9 (4) ◽  
pp. 261
Author(s):  
Fan Xu ◽  
Xuke Hu ◽  
Shuaiwei Luo ◽  
Jianga Shang
Keyword(s):  
Indoor Localization ◽  
Attenuation Factor ◽  
Access Point ◽  
Location Estimation ◽  
Signal Attenuation ◽  
Distance Ratio ◽  
Localization Accuracy ◽  
Access Points ◽  
Attenuation Parameter ◽  
The Impact

Wi-Fi fingerprinting has been widely used for indoor localization because of its good cost-effectiveness. However, it suffers from relatively low localization accuracy and robustness owing to the signal fluctuations. Virtual Access Points (VAP) can effectively reduce the impact of signal fluctuation problem in Wi-Fi fingerprinting. Current techniques normally use the Log-Normal Shadowing Model to estimate the virtual location of the access point. This would lead to inaccurate location estimation due to the signal attenuation factor in the model, which is difficult to be determined. To overcome this challenge, in this study, we propose a novel approach to calculating the virtual location of the access points by using the Apollonius Circle theory, specifically the distance ratio, which can eliminate the attenuation parameter term in the original model. This is based on the assumption that neighboring locations share the same attenuation parameter corresponding to the signal attenuation caused by obstacles. We evaluated the proposed method in a laboratory building with three different kinds of scenes and 1194 test points in total. The experimental results show that the proposed approach can improve the accuracy and robustness of the Wi-Fi fingerprinting techniques and achieve state-of-art performance.

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