Design and implementation of a smartphone-based positioning system

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Abstract

In this research study, we investigate feasibility of a smart phone based positioning system. The system allows users to get their current location information via their smartphones. The client software required for user smartphones can be distributed and installed easily through standard mobile Apps. Once the mobile App is ready in user smartphones, they just need to take one or two pictures at target objects around, and upload the pictures to the positioning system through Internet connection. The positioning system will identify the location, based on the upload pictures and other related information. We conducted a field test to identify locations among a building complex in a campus.We collected thousands of images taken from outward appearance of several buildings in a campus at different days. The images were classified into 17 classes, based on the location the picture images were taken. From the experiment results, we found that under well control of image quality for both training and testing images the correct classification rate can be as high as 98.3%. Even under the cases of large scope-of-view mismatching between the raining images and the tested images, the proposed scheme can still generate good correct classification rate (86.7% and 77.3% for both covering and covered cases respectively) compared with random guest (1/17=5.88%).

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APA

Yeh, C. C., Lo, Y. C., & Chang, C. C. (2016). Design and implementation of a smartphone-based positioning system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9799, pp. 995–1006). Springer Verlag. https://doi.org/10.1007/978-3-319-42007-3_84

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