Spatial Data Quality in the Internet of Things: Management, Exploitation, and Prospects

Abstract

With the continued deployment of the Internet of Things (IoT) , increasing volumes of devices are being deployed that emit massive spatially referenced data. Due in part to the dynamic, decentralized, and heterogeneous architecture of the IoT, the varying and often low quality of spatial IoT data (SID) presents challenges to applications built on top of this data. This survey aims to provide unique insight to practitioners who intend to develop IoT-enabled applications and to researchers who wish to conduct research that relates to data quality in the IoT setting. The survey offers an inventory analysis of major data quality dimensions in SID and covers significant data characteristics and associated quality considerations. The survey summarizes data quality related technologies from both task and technique perspectives. Organizing the technologies from the task perspective, it covers recent progress in SID quality management, encompassing location refinement, uncertainty elimination, outlier removal, fault correction, data integration, and data reduction; and it covers low-quality SID exploitation, encompassing querying, analysis, and decision-making techniques. Finally, the survey covers emerging trends and open issues concerning the quality of SID.

Spatial Data Quality in the IoT Era: Management and Exploitation

“…The DQ tasks in the perception and transport layers optimize mainly the infrastructure (cf. our survey [59]). Taking into account the audience, we exclude these and focus on data handling for DQ in higher IoT layers.…”

“…Excellence. Building on a new ACM Computing Surveys paper [59], the tutorial provides a comprehensive introduction to cutting-edge developments in a good deal of sub-topics on multiple aspects of spatial IoT data quality. The tutorial spotlights the unique challenges of the IoT that are brought to spatial computing, and it expands substantially the techniques and methodology for handling trajectories and spatiotemporal data in IoT settings.…”

“…The tutorial utilizes the structure of our survey paper [59] in the ACM Computing Surveys. Due to the time limit, the tutorial will be a condensed version of our full survey paper, focusing on comparing the methodologies of representative works.…”