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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a>
Indoor navigation and localization has gained a key attention of the researchers in the recent decades. Various technologies such as WiFi, Bluetooth, Ultra Wideband (UWB), and Radio-frequency identification (RFID) have been used for indoor navigation and localization. However, most of these existing methods often fail in providing a reasonable solution to the key challenges such as implementation cost, accuracy and extendibility. In this paper, we proposed a low-cost, and extendable framework<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs11243052">doi:10.3390/rs11243052</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ksdh3o3ekja7ximamb6vy2huui">fatcat:ksdh3o3ekja7ximamb6vy2huui</a> </span>
more »... r indoor navigation. We used simple markers printed on the paper, and placed on ceilings of the building. These markers are detected by a smartphone's camera, and the audio and visual information associated with these markers are used as a user guidance. The system finds shortest path between any two arbitrary nodes for user navigation. In addition, it is extendable having the capability to cover new sections by installing new nodes at any place in the building. The system can be used for guidance of the blind people, tourists and new visitors in an indoor environment. The evaluation results reveal that the proposed system can guide users toward their destination in an efficient and accurate manner.
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