arXiv subjects

Lu Su

Publications and source records attributed to Lu Su.

22 records · Page 2Linked to original sources

arXiv2017

VehSense: Slippery Road Detection Using Smartphones

This paper investigates a new application of vehicular sensing: detecting and reporting the slippery road conditions. We describe a system and associated algorithm to monitor vehicle skidding events using smartphones and OBD-II (On board Diagnostics) adaptors. This system, which we call the VehSense, gathers data from smartphone inertial sensors and vehicle wheel speed sensors, and processes the data to monitor slippery road conditions in real-time. Specifically, two speed readings are collected: 1) ground speed, which is estimated by vehicle acceleration and rotation, and 2) wheel speed, which is retrieved from the OBD-II interface. The mismatch between these two speeds is used to infer a skidding event. Without tapping into vehicle manufactures' proprietary data (e.g., antilock braking system), VehSense is compatible with most of the passenger vehicles, and thus can be easily deployed. We evaluate our system on snow-covered roads at Buffalo, and show that it can detect vehicle skidding effectively.

eess.SY↗

arXiv2017

CENTURION: Incentivizing Multi-Requester Mobile Crowd Sensing

The recent proliferation of increasingly capable mobile devices has given rise to mobile crowd sensing (MCS) systems that outsource the collection of sensory data to a crowd of participating workers that carry various mobile devices. Aware of the paramount importance of effectively incentivizing participation in such systems, the research community has proposed a wide variety of incentive mechanisms. However, different from most of these existing mechanisms which assume the existence of only one data requester, we consider MCS systems with multiple data requesters, which are actually more common in practice. Specifically, our incentive mechanism is based on double auction, and is able to stimulate the participation of both data requesters and workers. In real practice, the incentive mechanism is typically not an isolated module, but interacts with the data aggregation mechanism that aggregates workers' data. For this reason, we propose CENTURION, a novel integrated framework for multi-requester MCS systems, consisting of the aforementioned incentive and data aggregation mechanism. CENTURION's incentive mechanism satisfies truthfulness, individual rationality, computational efficiency, as well as guaranteeing non-negative social welfare, and its data aggregation mechanism generates highly accurate aggregated results. The desirable properties of CENTURION are validated through both theoretical analysis and extensive simulations.

cs.GT↗

arXiv2015

Joint Source Selection and Data Extrapolation in Social Sensing for Disaster Response

This paper complements the large body of social sensing literature by developing means for augmenting sensing data with inference results that "fill-in" missing pieces. It specifically explores the synergy between (i) inference techniques used for filling-in missing pieces and (ii) source selection techniques used to determine which pieces to retrieve in order to improve inference results. We focus on prediction in disaster scenarios, where disruptive trend changes occur. We first discuss our previous conference study that compared a set of prediction heuristics and developed a hybrid prediction algorithm. We then enhance the prediction scheme by considering algorithms for sensor selection that improve inference quality. Our proposed source selection and extrapolation algorithms are tested using data collected during the New York City crisis in the aftermath of Hurricane Sandy in November 2012. The evaluation results show that consistently good predictions are achieved. The work is notable for addressing the bi-modal nature of damage propagation in complex systems subjected to stress, where periods of calm are interspersed with periods of severe change. It is novel in offering a new solution to the problem that jointly leverages source selection and extrapolation components thereby improving the results.

cs.SI↗

arXiv2015

A Survey on Truth Discovery

Thanks to information explosion, data for the objects of interest can be collected from increasingly more sources. However, for the same object, there usually exist conflicts among the collected multi-source information. To tackle this challenge, truth discovery, which integrates multi-source noisy information by estimating the reliability of each source, has emerged as a hot topic. Several truth discovery methods have been proposed for various scenarios, and they have been successfully applied in diverse application domains. In this survey, we focus on providing a comprehensive overview of truth discovery methods, and summarizing them from different aspects. We also discuss some future directions of truth discovery research. We hope that this survey will promote a better understanding of the current progress on truth discovery, and offer some guidelines on how to apply these approaches in application domains.

cs.DB↗