scholarly journals INVESTIGATION OF BLUETOOTH LOW ENERGY (BLE) AND WIRELESS LOCAL AREA NETWORK (WLAN)-DERIVED DISTANCE MEASUREMENTS USING MOBILE PHONES FOR INDOOR POSITIONING

Author(s):  
K. M. K. Daray ◽  
P. A. G. Todoc ◽  
C. J. S. Sarmiento

Abstract. The indoor positioning problem is not the unavailability of indoor positioning technology, but the difficulty of arriving at an acceptable compromise of technical constraints like cost, performance, ease of use, and availability of technologies. In a developing country such as the Philippines, these constraints have more weight and can restrict the advancement of indoor positioning.This study investigates the use of Bluetooth Low Energy (BLE) and Wireless Local Area Network (WLAN) in Euclidean distance computation, which implies prospect use for indoor positioning through trilateration. It is a proof-of-concept study that BLE and WLAN, using readily-available services such as Nearby Application Programming Interface (API) and beacon simulators, can be used for indoor positioning. This method offers a better trade-off between cost, power, and accuracy.Nearby API and a regular beacon simulator application were used as beacons. The received signal strength interface (RSSI) was measured and used to calculate the Euclidean distance. From each beacon were calculated four different distances, Nearby yielding a maximum error of 26% and a minimum of 4%. The beacon simulator was less accurate and had a maximum error of 60.5% and a minimum of 4%. This shows that it is possible to calculate Euclidean distance using WLAN and BLE, and that Nearby API, which uses both, was more accurate than the beacon simulator, which used only BLE.

2011 ◽  
Vol 204-210 ◽  
pp. 1599-1602 ◽  
Author(s):  
Zhi An Deng ◽  
Yu Bin Xu ◽  
Di Wu

Indoor positioning system in wireless local area network (WLAN) has been a subject of intensive research due to its cost effectiveness and reasonable positioning accuracy. A new WLAN indoor positioning algorithm based on support vector regression (SVR) and space partitioning is proposed. The whole positioning environment is partitioned into several subspaces by combining k-means clustering method and binary support vector classifiers (SVC). Then the mapping function between received signal strength (RSS) and the physical space is established by SVR machine for each subspace. Subspace with much smaller physical range means more compact input feature space and leads to the enhancement of generalization capability for each SVR machine. The proposed algorithm and other well-known positioning algorithms are carried and compared in a real WLAN environment. Experimental results show that the proposed algorithm achieves 14.6 percent (0.31m) improvement than the single SVR algorithm in the sense of mean positioning error.


Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2433 ◽  
Author(s):  
Litao Han ◽  
Li Jiang ◽  
Qiaoli Kong ◽  
Ji Wang ◽  
Aiguo Zhang ◽  
...  

For existing wireless network devices and smart phones to achieve available positioning accuracy easily, fingerprint localization is widely used in indoor positioning, which depends on the differences of the Received Signal Strength Indicator (RSSI) from the Wireless Local Area Network (WLAN) in different places. Currently, most researchers pay more attention to the improvement of online positioning algorithms using RSSI values, while few focus on the MAC (media access control) addresses received from the WLAN. Accordingly, we attempt to integrate MAC addresses and RSSI values simultaneously in order to realize indoor localization within multi-story buildings. A novel approach to indoor positioning within multi-story buildings is presented in this article, which includes two steps: firstly, to identify the floor using the difference of received MAC addresses in different floors; secondly, to implement further localization on the same floor. Meanwhile, clustering operation using MAC addresses as the clustering index is introduced in the online positioning phase to improve the efficiency and accuracy of indoor positioning. Experimental results show that the proposed approach can achieve not only the precise location with the horizontal accuracy of 1.8 meters, but also the floor where the receiver is located within multi-story buildings.


2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
Pedro Daniel Urbina Coronado ◽  
Horacio Ahuett-Garza ◽  
Vishnu-Baba Sundaresan ◽  
Ruben Morales-Menendez

Developments of technologies that facilitate vehicle connectivity represent a market demand. In particular,mobile device(MD) technology provides advanced user interface, customization, and upgradability characteristics that can facilitate connectivity and possibly aid in the goal of autonomous driving. This work explores the use of a MD in the control system of a conceptualelectric vehicle(EV). While the use of MD for real-time control and monitoring has been reported, proper consideration has not been given to delays in data flow and their effects on system performance. The motor of a novel propulsion system for an EV was conditioned to be controlled in a wireless local area network by an ecosystem that includes a MD and an electronic board. An intended accelerator signal is predefined and sent to the motor and rotational speed values produced in the motor are sent back to the MD. Sample periods in which the communication really occurs are registered. Delays in the sample periods and produced errors in the accelerator and rotational speed signals are presented and analyzed. Maximum delays found in communications were of 0.2 s, while the maximum error produced in the accelerator signal was of 3.54%. Delays are also simulated, with a response that is similar to the behavior observed in the experiments.


Sign in / Sign up

Export Citation Format

Share Document