Service-oriented Internet-of-Things (IoT) systems are being deployed to provide intelligent, personal indoor services that must be location-and context-aware. In this paper, we present an efficient localization technology that uses a single camera to inspect framed pictures in the surrounding environment to quickly identify the device's location. Our idea is motivated by the popular ArUco markers. By using simple transformation algorithms, our technology converts framed pictures into ArUco markers and then identifies their marker ID's and poses. We have used the technology to deploy indoor drones so that each drone can be location-aware. The drone camera also streams video frames back to edge servers for human face recognition in order to identify the locations of known individuals. We believe our work of using artistic pictures as location markers can offer an attractive and low-cost localization services for many smart indoor IoT applications.
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Yu et al. (2018) studied this question.
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