Indoor positioning systems have gained a lot of attention in the last few years. With the introduction of the Internet of Things (IoT) paradigm, the knowledge of user's location has become crucial information to deliver the efficient and tailored Location Based Services (LBS), especially in indoor environments. In this paper we propose an AP (Access Point)-centred indoor positioning system that overcomes common limitations presented in conventional positioning systems, such as an excessive involvement of Mobile Devices (MDs). Our work merges ideas originally proposed in  and  to build an efficient, accurate and smart Probabilistic-FingerPrint (P-FP) algorithm that avoids the MD involvement and considers the signal strength measurements as a random variable in the positioning process. Numerical results, obtained in a real-world deployment, show better performance on positioning accuracy, energy consumption and latency with respect to the MD-based architecture.
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|Titolo:||An AP-Centred smart probabilistic fingerprint system for indoor positioning|
|Data di pubblicazione:||2018|
|Appare nelle tipologie:||04.01 - Contributo in atti di convegno|