P2-Loc

نویسندگان

چکیده

On-demand delivery is a fast developing business where gig couriers deliver online orders within short time from merchants to customers. Couriers' accurate indoor locations play an essential role in the business. Most of existing localization methods cannot be applied practice due high cost or data unavailable on off-the-shelf smartphones. This paper explores new angle solve problem relative and infrastructure-free fashion. We design person-to-person system that can (1) detect encounter events via Bluetooth couriers' smartphones, (2) infer all deep learning graph neural network. The infrastructure-free, map-free, compatible for devices. deploy real-world industry platform. runs smartphones 4,075 around 79 month. evaluation mall area shows P2-Loc improves mean average error compared with state-of-art infrastructure-based, report-based, encounter-based methods. also use application analysis based trajectory show save $40,000 platform every day improved results.

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ژورنال

عنوان ژورنال: Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies

سال: 2022

ISSN: ['2474-9567']

DOI: https://doi.org/10.1145/3517238