Quality Of Location-based Services Research Articles

An Adaptive User Tracking Algorithm Using Irregular Data Frames for Passive Fingerprint Positioning.

Wi-Fi fingerprinting is the most popular indoor positioning method today, representing received signal strength (RSS) values as vector-type fingerprints. Passive fingerprinting, unlike the active fingerprinting method, has the advantage of being able to track location without user participation by utilizing the signals that are naturally emitted from the user’s smartphone. However, since signals are generated depending on the user’s network usage patterns, there is a problem in that data are irregularly collected according to the patterns. Therefore, this paper proposes an adaptive algorithm that shows stable tracking performances for fingerprints generated at irregular time intervals. The accuracy and stability of the proposed tracking method were verified by experiments conducted in three scenarios. Through the proposed method, it is expected that the stability of indoor positioning and the quality of location-based services will improve.

Trip destination prediction based on a deep integration network by fusing multiple features from taxi trajectories

Trip destination prediction plays an important role in exploring urban travel patterns. Accurate prediction can improve the efficiency of traffic management and the quality of location-based services. Here, a deep learning structure that contains three components: travel information extraction, classification learning mechanism, and output module is proposed. Three types of information (the partial trajectory of on-going trips, historical trajectories, and related external information) are extracted in the first component. Then, the classification learning mechanism chooses different methods (i.e. Long Short-Term Memory network and Embedding technology) according to the characteristic of variables. Finally, an output layer that integrates the prior information about destinations is constructed. Two open-source trajectory datasets are used to validate the effectiveness of the proposed model. Results show that the proposed model outperforms benchmark models using only part of the information or using all of the information but ignore the classification learning mechanism. The performance of the proposed model under different call types and travel durations is further explored. The result of this study will help understand travel behaviour in urban cities.

Complete Bipartite Anonymity for Location Privacy

Users are vulnerable to privacy risks when providing their location information to location-based services (LBS). Existing work sacrifices the quality of LBS by degrading spatial and temporal accuracy for ensuring user privacy. In this paper, we propose a novel approach, Complete Bipartite Anonymity (CBA), aiming to achieve both user privacy and quality of service. The theoretical basis of CBA is that: if the bipartite graph of k nearby users’ paths can be transformed into a complete bipartite graph, then these users achieve k-anonymity since the set of “end points connecting to a specific start point in a graph” is an equivalence class. To achieve CBA, we design a Collaborative Path Confusion (CPC) protocol which enables nearby users to discover and authenticate each other without knowing their real identities or accurate locations, predict the encounter location using users’ moving pattern information, and generate fake traces obfuscating the real ones. We evaluate CBA using a real-world dataset, and compare its privacy performance with existing path confusion approach. The results show that CBA enhances location privacy by increasing the chance for a user confusing his/her path with others by 4 to 16 times in low user density areas. We also demonstrate that CBA is secure under the trace identification attack.

GPS signal accuracy and coverage analysis platform: Application to Trimble Juno SB receiver

Nowadays, information and mobile information technologies are being considered by the scientific community as primordial support for many other emerging technologies. The present paper exposes the results of a study and the analysis of accuracy, coverage and continuity of Global Positioning System (GPS) signal, using the Trimble Juno SB receiver. This is frequently used today for data collection and integration within Geographic Information Systems (GISs). Location-based services quality is highly depending on the accuracy of the position of the user. Generally, for each GPS enabled receiver the user need to evaluate the radius of the confidence region which describes the accuracy of the GPS device. In order to describe the accuracy of GPS receivers; a statistical method using a mobile software acquisition tool developed within our research group has been used. Intensive field measurements (i.e., 1data/1min x 3days) were carried out in Tetuan city (Morocco) during days of 29-30-31 May 2012 using local storage database feature. Homogeneous observation conditions and settings were respected for GPS signal acquisition. Finally, after calibrating the equipment, the results indicate that the Trimble Juno SB GPS receiver is well suited for services where meter accuracy is required.

A study on the accuracy of AGA positioning algorithm in multipath environment

The quality of location-based services (LBS) services depends on the available accuracy of the used positioning method. There are generally several ones for wireless networks. The more accurate methods are way more expensive to implement. On the contrary, there are methods with lower accuracy and much lower costs as well. Received signal strength (RSS) method, which is described below, belongs to the latter case. The purpose of this paper is to describe a performance of adaptive geometric algorithm (AGA)for estimation of mobile station position in multipath environment. The algorithm is an improved version of basic geometric algorithm and it is compared to it as well as to Standard Least Squares method. The properties of the proposed algorithm are evaluated in a simulation and experimental scenario. Both scenarios are implemented in typical multipath conditions, which are crucial in wireless communication. Key words: Adaptive geometric algorithm, mobile positioning, received signal strength method, wireless networks.

A Cooperative Position Fix Scheme Based on a Group Management on the Vehicular Network

This paper proposes and evaluates the performance of a cooperative position fix scheme built on top of a group management mechanism carried out by processes distributed across the vehicular network. The main goal is to enhance the accuracy of map matching and thus the quality of diverse location-based services without extra equipment. Designed on the telematics network consisting of many vehicles simultaneously moving on the road network, the proposed scheme enables the in-vehicle telematics device to play a role of collecting GPS readings from its neighbors through an appropriate wireless network interface when necessary. With at least 3 affirmative points having just a single segment to match, the GPS deviation for each time instant can be estimated by solving an equation system which has more variables than equations, and the estimated term improves the accuracy of positioning data. The performance measurement result shows that the proposed scheme can reduce the ratio of ambiguous points from 32.0% to 20.6%, while increasing that of affirmative points from 61.0% to 71.2%, sharpening the gap between the best two matches.

Satellite Positioning for LBS: A Zagreb Field Positioning Performance Study

Recent studies confirm the importance of satellite positioning in location-based services (LBS) development. A field study was conducted in suburban and rural areas near Zagreb, Croatia in order to examine the real-time data compliance with recently established positioning performance requirements for LBS quality of service (QoS). Data analysis was based on comparison between actual positioning performance and pre-specified positioning parameter values using defined comparative procedures. The results presented here confirm a good correlation between the actual and required positioning performance, even without implementation of any of augmentation or assistance positioning methods.