A Signal Strength Based Location Estimation Algorithm within a Wireless Network

Shum, Kevin Chin Yiu; Cheng, Quan Jia; Ng, Joseph Kee Yin; Ng, Donna

doi:10.1109/aina.2011.80

Cited by 12 publications

(7 citation statements)

References 8 publications

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“…Besides, radio characteristics in an open environment are never static, and there is no universally fine methodology to tune the data to accommodate environmental change, although, one acknowledges a growing interest in post-deployment adaptation in recent years from telecom industry [25]. Even the commercial products like that provided by Ekahau fall victim to environmental change post-deployment adaptation problems [26]. Consequently, the issue of handling uncertainty pervading the signal strength measurements as well as environmental layout is of paramount importance.…”

Section: Related Workmentioning

confidence: 97%

Multivariable fuzzy inference system for fingerprinting indoor localization

Oussalah

Alakhras

Hussein

2015

Fuzzy Sets and Systems

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The emergence of wireless sensor network has raised the need for cheap wireless indoor localization technique. This paper considers the problem of fingerprinting indoor localization based on signal strength measurements RSS. A new approach based on Fuzzy logic has been put forward. The proposal makes use of k-nearest neighbor classification in signal space. The localization of target node is then determined as a weighted combination of nearest fingerprints. The weights are determined using Takagi-Sugeno fuzzy controller with two inputs. A new enhancement to the kNN is proposed to enhance the accuracy of location estimation; this enhancement allows the kNN to outlier some miss elected neighbors based on triangular area measurements. The performance of the developed estimation algorithm has been evaluated using both Monte Carlo simulations and real testbed scenarios while compared to other alternative approaches. Crown

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Section: Related Workmentioning

confidence: 97%

Multivariable fuzzy inference system for fingerprinting indoor localization

Oussalah

Alakhras

Hussein

2015

Fuzzy Sets and Systems

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“…Least sum of square (SS) [26,28]: INSAR calculates the difference between the signal that is read on the fly and the signal that is stored in the database for 3. Least average of square AS: INSAR calculates the difference between the signal that is read on the fly and the signal that is stored in the database for the same MAC address and calculates the square of difference for each Access point.…”

Section: Positioning Systemmentioning

confidence: 99%

Insar

Alnabhan

Tomaszewski

2014

Proceedings of the Sixth ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness - ISA '14

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Indoor navigation applications for mobile devices are being more common and needed for people who want to find inside building destinations. Many indoor navigation applications utilize different technologies, such as Wi-Fi fingerprinting, have been suggested. Most of these applications use a fixed background map and pre-calculated paths to lead the user to their destinations. Users of these systems need general map reading skills and understanding how specifically indoor maps work. In addition, these system types need to implement complex and accurate calculations to determine routing paths before navigation starts -which could be affected by unstable Wi-Fi signals. In this paper, we suggest INSAR or Indoor Navigation System Using Augmented Reality, which utilizes Wi-Fi fingerprinting, augmented reality (AR), and digital compass technologies in an integrated Android-based app. Specifically, we used a Wi-Fi fingerprinting method to determine user position, augmented reality to display real-time navigation information, and a compass to determine destination direction. Additionally, digital compass use to read the destination direction of each reference point (RP) helps direct the users "on the fly" thus reducing potential Wi-Fi signal instability effects.

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“…Some popular techniques based on RSSI are the fingerprinting, aggregated signal layout, and center of gravity (CG) [4]. To further enhance the performance in using RSSI, the signal aggregated method was proposed in [21]. In [5], an efficient approach was proposed to reduce the manual calibration and to optimize the accuracy in indoor positioning using RSSI.…”

Section: Localization Using Wireless Communicationmentioning

confidence: 99%

“…However, the disadvantage is the difficulties in setup and heavy maintenance cost of the fingerprint database. Fortunately, this cost can be reduced by the aggregated signal layout technique where the accuracy is roughly maintained [21]. Figure 7 shows an example floor plan of a store.…”

Section: Localization Using Wlanmentioning

confidence: 99%

“…Since we adopt using the aggregated signal layout approach [21] for location estimation, we have to find out the signal-distance relationship for the target operation environment. For this real-time calibration, access points act as sensors to capture the communication signals between the access points and the WiFi-enabled smartphone as well as among all the access points themselves.…”

Section: Localization Using Wlanmentioning

confidence: 99%

See 1 more Smart Citation

A Pervasive Promotion Model for Personalized Promotion Systems on Using WLAN Localization and NFC Techniques

Lam

Wang

et al. 2015

Mobile Information Systems

Self Cite

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In this paper, we propose a novelpervasive business modelfor sales promotion in retail chain stores utilizing WLAN localization andnear field communication (NFC)technologies. The objectives of the model are to increase the customers’flowof the stores and theirincentivesin purchasing. In the proposed model, the NFC technology is used as the first mean to motivate customers to come to the stores. Then, with the use of WLAN, the movements of the customers, who are carrying smartphones, within the stores are captured and maintained in themovement database. By interpreting the movements of customers as indicators of their interests to the displayed items,personalizedpromotion strategies can be formulated to increase their incentives for purchasing future items. Various issues in the application of the adopted localization scheme for locating customers in a store are discussed. To facilitate the item management and space utilization in displaying the items, we propose anenhanced R-treefor indexing the data items maintained in the movement database. Experimental results have demonstrated the effectiveness of the adopted localization scheme in supporting the proposed model.

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A Signal Strength Based Location Estimation Algorithm within a Wireless Network

Cited by 12 publications

References 8 publications

Multivariable fuzzy inference system for fingerprinting indoor localization

Multivariable fuzzy inference system for fingerprinting indoor localization

Insar

A Pervasive Promotion Model for Personalized Promotion Systems on Using WLAN Localization and NFC Techniques

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