Journal ArticleDOI
Pallas: Self-Bootstrapping Fine-Grained Passive Indoor Localization Using WiFi Monitors
TLDR
Pallas is a self-bootstrapping system for fine-grained passive indoor localization using non-intrusive WiFi monitors that uses off-the-shelf access point hardware to opportunistically capture WiFi packets to infer the location of smartphones in the indoor environment.Abstract:
Passive indoor localization for smartphones requires no explicit cooperation of the smartphone and enables a new spectrum of applications such as passive user tracking, mobility monitoring, social pattern analysis, etc. However, existing passive localization methods either achieve coarse-grained localization accuracy or require expensive infrastructure support. In this paper, we present Pallas, a self-bootstrapping system for fine-grained passive indoor localization using non-intrusive WiFi monitors. Pallas uses off-the-shelf access point hardware to opportunistically capture WiFi packets to infer the location of smartphones in the indoor environment. The key novelty of Pallas lies in that the passive fingerprint database for localization is automatically constructed and updated without any active participation of WiFi devices or manual calibration. To achieve this, Pallas first identifies passive landmarks that are present in WiFi RSS traces. Given the knowledge of the indoor floor plan and the location of WiFi monitors, Pallas statistically maps the collected RSS traces to specific indoor pathways. With sufficient mapping opportunistically detected, Pallas is able to bootstrap a fine-grained passive fingerprint database and build Gaussian processes for localization automatically without requiring any additional calibration effort.read more
Citations
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Journal ArticleDOI
A Survey of Indoor Localization Systems and Technologies
TL;DR: This paper aims to provide a detailed survey of different indoor localization techniques, such as angle of arrival (AoA), time of flight (ToF), return time ofFlight (RTOF), and received signal strength (RSS) based on technologies that have been proposed in the literature.
Journal ArticleDOI
A Review on the Use of Blockchain for the Internet of Things
TL;DR: A thorough review on how to adapt blockchain to the specific needs of IoT in order to develop Blockchain-based IoT (BIoT) applications is presented and some recommendations are enumerated with the aim of guiding future BIoT researchers and developers on some of the issues that will have to be tackled before deploying the next generation of BIeT applications.
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WiFi-SLAM Using G aussian Process Latent Variable Models
TL;DR: In this paper, the Gaussian Process Latent Variable Model (GPLVM) is used to reconstruct a topological connectivity graph from a signal strength sequence, which can be used to perform efficient WiFi SLAM.
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Industrial Internet: A Survey on the Enabling Technologies, Applications, and Challenges
TL;DR: The 5C architecture that is widely adopted to characterize the Industrial Internet systems is presented and the enabling technologies of each layer that cover from industrial networking, industrial intelligent sensing, cloud computing, big data, smart control, and security management are investigated.
Journal ArticleDOI
Differentially Private Location Protection for Worker Datasets in Spatial Crowdsourcing
TL;DR: This paper proposes a mechanism based on differential privacy and geocasting that achieves effective SC services while offering privacy guarantees to workers, and addresses scenarios with both static and dynamic datasets of workers.
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