Automatic signal strength map construction in indoor positioning system based on round trip time of flight measurements and inertial navigation

Author(s):  
Aleksandr Galov ◽  
Alex Moschevikin
2021 ◽  
pp. 101416
Author(s):  
Omar Hashem ◽  
Khaled A. Harras ◽  
Moustafa Youssef

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Herryawan Pujiharsono ◽  
Duwi Utami ◽  
Rafina Destiarti Ainul

Wireless network technology that is used today is developing rapidly because of the increasing need for location information of an object with high accuracy. Global Positioning System (GPS) is a technology to estimate the current location. Unfortunately, GPS has a disadvantage of low accuracy of 10 meters when used indoors. Therefore, it began to be developed with the concept of an indoor positioning system. This is a technology used to estimate the location of objects in a building by utilizing WSN (Wireless Sensor Network). The purpose of this study is to estimate the location of the unknown nodes in the lecturer room as an object and obtain the accuracy of the system being tested. The positioning process is based on the received signal strength (RSSI) on the unknown node using the ZigBee module. The trilateration method is used to estimate unknown node located at the observation area based on the signal strength received at the time of testing. The result shows that the path loss coefficient value at the observation area is 0.9836 and the Mean Square Error of the test is 1.251 meters, which indicates that the system can be a solution to the indoor GPS problem.


Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7261
Author(s):  
Hajime Ando ◽  
Shingo Sekoguchi ◽  
Kazunori Ikegami ◽  
Hidetaka Yoshitake ◽  
Hiroka Baba ◽  
...  

Monitoring of personal exposure to hazardous substances has garnered increasing attention over the past few years. However, no straightforward and exact indoor positioning technique has been available until the recent discovery of Wi-Fi round trip time (Wi-Fi RTT). In this study, we investigated the possibility of using a combination of Wi-Fi RTT for indoor positioning and a wearable particle monitor (WPM) to observe dust concentration during walking in a simulated factory. Ultrasonic humidifiers were used to spray sodium chloride solution inside the factory. The measurements were recorded three times on different routes (Experiments A, B, and C). The error percentages, i.e., measurements that were outside the expected measurement area, were 7% (49 s/700 s) in Experiment A, 2.3% (15 s/660 s) in Experiment B, and 7.8% (50 s/645 s) in Experiment C. The dust measurements were also recorded without any obstruction. A heat map was created based on the results from both measured values. Wi-Fi RTT proved useful for computing the indoor position with high accuracy, suggesting the applicability of the proposed methodology for occupational health monitoring.


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