Location-Based Services

@article{Dey2010LocationBasedS,
  title={Location-Based Services},
  author={Anind K. Dey and Jeffrey Hightower and Eyal de Lara and Nigel Davies},
  journal={IEEE Pervasive Computing},
  year={2010},
  volume={9},
  pages={11-12}
}
Today, location information is in the hands of the masses. The success of location in pervasive computing has exposed new challenges and opportunities for researchers including making location sensing more robust, accurate, deployable, secure, and developer-friendly. This special issue showcases papers that describe recent research that addresses these challenges. 
Towards practical location systems with privacy protection
TLDR
A series of techniques to protect user location privacy against location-based service providers are proposed, however, it is challenging to apply these theoretical and sophisticated techniques to the real world. Expand
Locating in Crowdsourcing-Based DataSpace: Wireless Indoor Localization without Special Devices
TLDR
This study first confirms the existence of crowd behavior and the fact that it can be recognized using location-based wireless mobility information, and designs “Locating in Crowdsourcing-based DataSpace” (LiCS), which is based on sensing and analyzing wireless information. Expand
Leveraging Spatial Diversity for Privacy-Aware Location-Based Services in Mobile Networks
TLDR
New ambient environment-dependent location privacy metrics are proposed in this paper, together with a stochastic model that can capture their spatial variations along the user’s route that allows mobile users to fully leverage the spatial diversity and achieve a substantially better performance. Expand
Beyond HTML5 geolocation: A flexible concept to enable and easily use advanced positioning technologies for mobile indoor location based service web applications
TLDR
It is shown how an established IMU-sensor based positioning system library could be used by web applications with a standard HTML hyperlink, which extends the applications of available, specialized indoor positioning modules greatly to the domain of existing and upcoming location based online-services. Expand
What is next for Indoor Localisation? Taxonomy, protocols, and patterns for advanced Location Based Services
TLDR
This is a first high-level attempt at defining a taxonomy of indoor positioning systems, at outlining the main phases of a protocol for the utilisation of different cooperating indoor localisation systems, and at drawing a vision of services and applications in the close future. Expand
Location Explorer with information services: A mobile application to deliver location-based web services
In this paper, we propose an approach to delivering location-based information (LBI) and location-based web services (LBWS) to users based on users' past behaviors. The service usage patterns minedExpand
Privacy-Preserving Large-Scale Location Monitoring Using Bluetooth Low Energy
TLDR
This work extends BLE privacy by enriching its privacy semantics with a comprehensive set of metrics, such as simple opt-in/out, k-anonymity, and granularity-based anonymity, to enable users to better control their privacy level while still providing monitoring and tracking service to authorized parties. Expand
A Unified Approach to Uncertainty-Aware Ubiquitous Localisation of Mobile Users
TLDR
The presented approach models the details of localisation systems and uses this model to create a unified view on localisation in which special attention is paid to uncertainty coming from different localisation conditions and to its presentation to the user. Expand
FUZIPS: Fuzzy v2 Based Algorithm for Automatic Switching from GPS Based Location Services to the Indoor Positioning Service
TLDR
An algorithm capable of automatic switching from traditional location services (GPS, A-GPS) to indoor positioning systems (WiFi based triangulation, Bluetooth LE beacons) and fuzzy logic algorithm based on the signal strength and the distance are presented. Expand
Positioning Methods and the Use of Location and Activity Data in Forests
TLDR
A hierarchical model for collecting and sharing data in forest and fire management, and more broadly in the field of natural resources is presented and reflects tradeoffs in range and bandwidth when recording, processing, and communicating large quantities of data in time and space. Expand
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