FlierMeet: A Mobile Crowdsensing System for Cross-Space Public Information Reposting, Tagging, and Sharing

Abstract

Community bulletin boards serve an important function for public information sharing in modern society. Posted fliers advertise services, events, and other announcements. However, fliers posted offline suffer from problems such as limited spatial-temporal coverage and inefficient search support. In recent years, with the development of sensor-enhanced mobile devices, mobile crowd sensing (MCS) has been used in a variety of application areas. This paper presents FlierMeet, a crowdpowered sensing system for cross-space public information reposting, tagging and sharing. The tags learned are useful for flier sharing and preferred information retrieval and suggestion. Specifically, we utilize various contexts (e.g., spatio-temporal info, flier publishing/reposting behaviors, etc.) and textual features to group similar reposts and classify them into categories. We further identify a novel set of crowd-object interaction hints to predict the semantic tags of reposts. To evaluate our system, 38 participants were recruited and 2,035 reposts were captured during an eight-week period. Experiments on this dataset showed that our approach to flier grouping is effective and the proposed features are useful for flier category/semantic tagging.Index Terms-Participatory sensing, cross-space reposting, data grouping and selection, interaction-based semantic tagging, urban sensing.

ActiveCrowd: A Framework for Optimized Multitask Allocation in Mobile Crowdsensing Systems

“…In this work, the evaluation of our algorithms is based on a real-world human mobility dataset. We are now collaborating with the local government to build a city-level MCS platform for citizens to report municipal problems (e.g., road collapse, public facility damage, and noise disturbance), urban dynamics (e.g., traffic jams, accidents, public information [39]), etc. We intend to introduce our multi-task allocation framework in the platform and make large-scale user studies, which will help identify practical issues and improve our framework.…”

Embedded mobile crowd service systems based on opportunistic geological grid and dynamical segmentation

“…The complexity of the sequence of S C includes service description complexity SD C , service object space location complexity SS C , service object dynamic form complexity SF C , and computational complexity C C . Among them, it is the key factor to restrict the performance of the system, which can be described by the formula (9).…”

“…An incentive mechanism was proposed by Yutian Wen et al [8] based on a quality-driven auction, which is specifically for the mobile crowd sensing system. In an article [9], a crowd-powered sensing system was presented for crossspace public information reposting, tagging, and sharing.…”

A Generic Framework for Constraint-Driven Data Selection in Mobile Crowd Photographing

“…Previous research and applications, e.g. CreekWatch [2], GarbageWatch [3], SmartEye [4], PhotoCity [5], WreckWatch [6], FlierMeet [7], Mediascope [8], iMoon [9] and SakuraSensor [10], indicated that MCP is useful and superior to traditional approaches in visual sensing, e.g. deployment of static cameras for monitoring.…”

“…buildings [5], flyers [7] and event [28]) and coverage requirements (e.g. the target sensing area and time period, single-shot or multi-shots including different shooting directions [18]).…”