Smartphone advances are leading to a class of Internet-based Indoor Navigation services. IIN services rely on geolocation databases that store indoor models, comprising floor maps and points of interest, along with wireless, light, and magnetic signals for localizing users. Developing IIN services creates new information management challenges - such as crowdsourcing indoor models, acquiring and fusing big data velocity signals, localization algorithms, and custodians' location privacy. Here, the authors classify current academic and industrial IIN services using a multidimensional taxonomy of emerging topics. They present the taxonomy as an open, modular, extensible, and scalable architecture, called Anyplace, and discuss open challenges.
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Zeinalipour-Yazti et al. (2017) studied this question.
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