PINSPOT: An oPen platform for INtelligent context-baSed Indoor POsiTioning

Raspopoulos, Marios orcid iconORCID: 0000-0003-1513-6018, Paspallis, Nearchos orcid iconORCID: 0000-0002-2636-7973 and Kaimakis, Paris (2019) PINSPOT: An oPen platform for INtelligent context-baSed Indoor POsiTioning. In: International Conference on Information System Development 2019, August 28-30, 2019, Tulon, France. (Unpublished)

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This work proposes PINSPOT; an open-access platform for collecting and sharing of context, algorithms and results in the cutting-edge area of indoor positioning. It is envisioned that this framework will become reference point for knowledge exchange which will bring the research community even closer and potentially enhance collaboration towards more effective and efficient creation of indoor positioning-related knowledge and innovation. Specifically, this platform facilitates the collection of sensor data useful for indoor positioning experimentation, the development of novel, self-learning, indoor positioning algorithms, as well as the enhancement and testing of existing ones and the dissemination and sharing of the proposed algorithms along with their configuration, the data used, and with their results.

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