Energy-efficient WiFi scanning for localization

@article{Choi2017EnergyefficientWS,
  title={Energy-efficient WiFi scanning for localization},
  author={Taehwa Choi and Yohan Chon and Hojung Cha},
  journal={Pervasive Mob. Comput.},
  year={2017},
  volume={37},
  pages={124-138}
}
Abstract WiFi radio signals are commonly used for the localization of mobile devices. [...] Key Method We predict the number of scanned access points (APs) according to locations and optimize the dwell time of beacon-listening to obtain the minimum number of scanned APs. The evaluation shows that the proposed system saves the energy consumption of WiFi scans by 33.6% and 45.7%, according to the number of scanned APs, while not decreasing the accuracy of localization in indoor and outdoor scenarios.Expand
Locate the Mobile Device by Enhancing the WiFi-Based Indoor Localization Model
TLDR
A WiFi-based localization model is proposed by modifying the large localization errors and enhancing the Gaussian process regression (MEGPR) by introducing the AP discrimination criterion (APDC) and the results show that compared with other existing localization models, the average localization error of the proposed MEGPR model is minimum, which further verifies the effectiveness of the proposal. Expand
Energy Modeling of IoT Mobile Terminals on WiFi Environmental Impacts †
TLDR
The impacts of some important factors of WiFi environments on the energy consumption of mobile phones, which are typical IoT end devices, are explored and a time-based signal strength-aware energy model and packet type/amount-awareEnergy models are constructed. Expand
A software architecture for energy consumption optimization in location-based mobile applications
TLDR
This paper proposes an adaptive middleware architecture for mobile applications using location-based services, developed after analyzing popular positioning techniques, such as GPS, Wi-Fi, and Cell Towers. Expand
Multivariate Polynomial Interpolation Based Indoor Fingerprinting Localization Using Bluetooth
TLDR
Extensive simulation results verify that the proposed multivariate polynomial function interpolation based fingerprinting localization method can improve localization accuracy effectively. Expand
Capturing Privacy-Preserving User Contexts with IndoorHash
TLDR
This paper addresses the challenge of producing a new location hash that captures the indoor location of a user, without disclosing the physical coordinates, thus preserving their privacy and enabling a new generation of privacy-preserving crowdsourcing mobile applications that protect from third parties re-identification attacks. Expand
Towards privacy-sensitive mobile crowdsourcing
TLDR
It is shown that FOUGERE defeats the state-of-the-art location-based privacy attacks with little impact on the quality of the collected data, and is proposed to convey data samples from user devices using peer-to-peer (P2P) communications to third-party servers, thus introducing an a priori data anonymization process that is resilient to location- based attacks. Expand
Organising the knowledge from stack overflow about location-sensing of Android applications
TLDR
The authors used the non-negative matrix factorisation (NMF) method to identify the topics discussed by the developers on stack overflow and found the following ten topics: fundamental, background service, global positioning system (GPS) provider, application error, location updates, programming aspects, GPS alternatives, location settings, NULL location, and location testing. Expand
The Behavioral Response to Location Based Services: An Examination of the Influence of Social and Environmental Benefits, and Privacy
Given the importance tourism has in many economies, this research was designed to study how the social and environmental benefits of Location Based Services (LBS) in the tourism sector influence userExpand
Distributed Applications and Interoperable Systems: 20th IFIP WG 6.1 International Conference, DAIS 2020, Held as Part of the 15th International Federated Conference on Distributed Computing Techniques, DisCoTec 2020, Valletta, Malta, June 15–19, 2020, Proceedings
TLDR
SafeSpark is a secure data analytics framework that enables the combination of different cryptographic processing techniques with hardware-based protected environments for privacy-preserving data storage and processing and is modular and extensible therefore adapting to data analytics applications with different performance, security and functionality requirements. Expand
Channel Load Aware AP / Extender Selection in Home WiFi Networks Using IEEE 802.11k/v
TLDR
This article introduces a centralized, easily implementable channel load aware selection mechanism for WiFi networks that takes full advantage of IEEE 802.11k/v capabilities to collect data from STAs, and distribute association decisions accordingly, resulting in an overall improvement of the main analyzed metrics (throughput and delay). Expand

References

SHOWING 1-10 OF 14 REFERENCES
Incremental Wi-Fi scanning for energy-efficient localization
TLDR
This work proposes a novel, incremental approach that reduces the energy consumption of Wi-Fi localization by scanning just a few selected channels, and shows that, compared to full scans, incremental scanning can reduce theEnergy consumption between 20.64% and 57.79%. Expand
Improving energy efficiency of Wi-Fi sensing on smartphones
TLDR
WiFisense is presented, a system that employs user mobility information retrieved from low-power sensors in smartphones, and further includes adaptive Wi-Fi sensing algorithms, to conserve battery power while improvingWi-Fi usage. Expand
Removing useless APs and fingerprints from WiFi indoor positioning radio maps
TLDR
The results show that there is possibility to simplify the radio maps of the positioning engines without significant degradation on the positioning precision and accuracy, and therefore to reduce the processing time for estimating the position of a tracked WiFi tag. Expand
SwiftScan: Efficient Wi-Fi scanning for background location-based services
  • R. Faragher, A. Rice
  • Engineering, Computer Science
  • 2015 International Conference on Indoor Positioning and Indoor Navigation (IPIN)
  • 2015
TLDR
SwiftScan is described and validated, an intelligent, self-training Wi-Fi fingerprinting scheme that reduces the energy consumption of periodic backgroundWi-Fi scanning for localisation purposes and shows that energy savings of over 90% are possible. Expand
Detecting and correcting WiFi positioning errors
TLDR
This paper designs a context-aware error detection method by employing an ensemble of predictors that have different strengths and weaknesses, and attempts to detect and correct errors caused by outlier detection in time series. Expand
SAIL: single access point-based indoor localization
TLDR
SAIL systematically addresses some of the common challenges towards dead-reckoning using smartphone sensors and achieves 2-5x accuracy improvements over existing techniques. Expand
Power-efficient access-point selection for indoor location estimation
TLDR
This paper presents a novel algorithm known as CaDet, which is able to use a small subset of the APs in the environment to detect a client's location with high accuracy by intelligently selecting the number of access points used for location estimation. Expand
Intelligent Dynamic Radio Tracking in Indoor Wireless Local Area Networks
TLDR
The experimental results conducted on measurements from a real office environment indicate that the combination of the intelligent design and the NI filter results in significant improvements over the Kalman and particle filters. Expand
On the RBF-based positioning using WLAN signal strength fingerprints
TLDR
This work exploits Received Signal Strength measurements from several WLAN Access Points and incorporates the RSS covariance matrix into the estimation method and couple that with a methodology that indicates which APs can be ignored during positioning without sacrificing accuracy. Expand
RADAR: an in-building RF-based user location and tracking system
  • P. Bahl, V. Padmanabhan
  • Computer Science
  • Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064)
  • 2000
TLDR
RADAR is presented, a radio-frequency (RF)-based system for locating and tracking users inside buildings that combines empirical measurements with signal propagation modeling to determine user location and thereby enable location-aware services and applications. Expand
...
1
2
...