Journal article  Open Access

Discovering location based services: a unified approach for heterogeneous indoor localization systems

Furfari F., Crivello A., Baronti P., Barsocchi P., Girolami M., Palumbo F., Quezada-Gaibor D., Mendoza Silva G. M., Torres-Sospedra J.

Indoor localization  Location based services  Context-awareness  Service discovery protocol 

The technological solutions and communication capabilities offered by the Internet of Things paradigm, in terms of raising availability of wearable devices, the ubiquitous internet connection, and the presence on the market of service-oriented solutions, have allowed a wide proposal of Location Based Services (LBS). In a close future, we foresee that companies and service providers will have developed reliable solutions to address indoor positioning, as basis for useful location based services. These solutions will be different from each other and they will adopt different hardware and processing techniques. This paper describes the proposal of a unified approach for Indoor Localization Systems that enables the cooperation between heterogeneous solutions and their functional modules. To this end, we designed an integrated architecture that, abstracting its main components, allows a seamless interaction among them. Finally, we present a working prototype of such architecture, which is based on the popular Telegram application for Android, as an integration demonstrator. The integration of the three main phases -namely the discovery phase, the User Agent self-configuration, and the indoor map retrieval/rendering- demonstrates the feasibility of the proposed integrated architecture.

Source: Internet of Things 13 (2021): 1–14. doi:10.1016/j.iot.2020.100334

Publisher: Elsevier

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BibTeX entry
	title = {Discovering location based services: a unified approach for heterogeneous indoor localization systems},
	author = {Furfari F. and Crivello A. and Baronti P. and Barsocchi P. and Girolami M. and Palumbo F. and Quezada-Gaibor D. and Mendoza Silva G. M. and Torres-Sospedra J.},
	publisher = {Elsevier},
	doi = {10.1016/j.iot.2020.100334},
	journal = {Internet of Things},
	volume = {13},
	pages = {1–14},
	year = {2021}