Distributed Inference and Query Processing for RFID Tracking and Monitoring

TL;DR

This paper introduces a scalable distributed system for RFID tracking that combines location inference with stream query processing, enhancing accuracy and efficiency in large-scale environments.

Contribution

It proposes a novel architecture integrating location inference with query processing and offers techniques for scalable distributed inference in RFID systems.

Findings

Demonstrates high accuracy in RFID data inference

Shows improved scalability and efficiency in large deployments

Validates techniques with real-world and synthetic data

Abstract

In this paper, we present the design of a scalable, distributed stream processing system for RFID tracking and monitoring. Since RFID data lacks containment and location information that is key to query processing, we propose to combine location and containment inference with stream query processing in a single architecture, with inference as an enabling mechanism for high-level query processing. We further consider challenges in instantiating such a system in large distributed settings and design techniques for distributed inference and query processing. Our experimental results, using both real-world data and large synthetic traces, demonstrate the accuracy, efficiency, and scalability of our proposed techniques.