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- W2728643422 abstract "Site survey cost has become a major deployment challenge for large-scale wireless systems. Some previous approaches require explicit user inputs to label the locations of crowdsourced signals, which is inconvenient in practice. Others may rely on intensively-calibrated specialized sensors. Furthermore, the locations of crowdsourced signals are usually random and sparse, making it difficult to build a complete signal map. To address these, we propose Surecose, a novel signal map construction system by implicit crowdsourcing and interaction of low-cost cooperative sensors. Surecose is initialized with the light-weight sparse signal map collection. Having the background application on, the naive users are implicit surveyors unknowingly uploading crowdsourced signals. Phones may detect each other (mobile sensors), or beacons (fixed sensors). To label their locations, Surecose measures the mutual sensor proximity of the IoT devices. Via joint location labeling and sensor calibration, Surecose transparently locates the users despite devices used. Then Surecose constructs the database with a directionally and environmentally adapted Gaussian process, which scales the labeled locations and RSSIs anywhere into a complete signal map. Extensive experiments in diverse environments, including a campus hall, an international airport and a premium shopping mall, have validated that Surecose can adaptively and accurately construct the Wi-Fi signal map (often more than 20% reduction in RSSI construction error), with low survey cost (around 70% survey reduction) and little human intervention." @default.
- W2728643422 created "2017-07-14" @default.
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- W2728643422 date "2017-06-01" @default.
- W2728643422 modified "2023-10-01" @default.
- W2728643422 title "Towards Crowdsourced Signal Map Construction via Implicit Interaction of IoT Devices" @default.
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- W2728643422 doi "https://doi.org/10.1109/sahcn.2017.7964901" @default.
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